Valid HTML 4.0! Valid CSS!
%%% -*-BibTeX-*-
%%% ====================================================================
%%% BibTeX-file{
%%%     author          = "Nelson H. F. Beebe",
%%%     version         = "1.43",
%%%     date            = "21 September 2024",
%%%     time            = "06:02:47 MDT",
%%%     filename        = "tmis.bib",
%%%     address         = "University of Utah
%%%                        Department of Mathematics, 110 LCB
%%%                        155 S 1400 E RM 233
%%%                        Salt Lake City, UT 84112-0090
%%%                        USA",
%%%     telephone       = "+1 801 581 5254",
%%%     FAX             = "+1 801 581 4148",
%%%     URL             = "https://www.math.utah.edu/~beebe",
%%%     checksum        = "31263 13033 65923 634860",
%%%     email           = "beebe at math.utah.edu, beebe at acm.org,
%%%                        beebe at computer.org (Internet)",
%%%     codetable       = "ISO/ASCII",
%%%     keywords        = "ACM Transactions on Management Information
%%%                        Systems (TMIS); bibliography; TMIS",
%%%     license         = "public domain",
%%%     supported       = "yes",
%%%     docstring       = "This is a COMPLETE BibTeX bibliography for
%%%                        ACM Transactions on Management Information
%%%                        Systems (TMIS) (CODEN none, ISSN 2158-656X
%%%                        (print), 2158-6578 (electronic)), covering
%%%                        all journal issues from 2010 -- date.
%%%
%%%                        At version 1.43, the COMPLETE journal
%%%                        coverage looked like this:
%%%
%%%                             2010 (   7)    2015 (  27)    2020 (  26)
%%%                             2011 (  26)    2016 (  12)    2021 (  37)
%%%                             2012 (  16)    2017 (  18)    2022 (  47)
%%%                             2013 (  24)    2018 (  13)    2023 (  32)
%%%                             2014 (   9)    2019 (  20)    2024 (  14)
%%%
%%%                             Article:        328
%%%
%%%                             Total entries:  328
%%%
%%%                        The journal Web page can be found at:
%%%
%%%                            http://www.acm.org/pubs/tmis.html
%%%
%%%                        The journal table of contents page is at:
%%%
%%%                            http://www.acm.org/tmis/
%%%                            http://portal.acm.org/browse_dl.cfm?idx=J1320
%%%
%%%                        Qualified subscribers can retrieve the full
%%%                        text of recent articles in PDF form.
%%%
%%%                        The initial draft was extracted from the ACM
%%%                        Web pages.
%%%
%%%                        ACM copyrights explicitly permit abstracting
%%%                        with credit, so article abstracts, keywords,
%%%                        and subject classifications have been
%%%                        included in this bibliography wherever
%%%                        available.  Article reviews have been
%%%                        omitted, until their copyright status has
%%%                        been clarified.
%%%
%%%                        bibsource keys in the bibliography entries
%%%                        below indicate the entry originally came
%%%                        from the computer science bibliography
%%%                        archive, even though it has likely since
%%%                        been corrected and updated.
%%%
%%%                        URL keys in the bibliography point to
%%%                        World Wide Web locations of additional
%%%                        information about the entry.
%%%
%%%                        BibTeX citation tags are uniformly chosen
%%%                        as name:year:abbrev, where name is the
%%%                        family name of the first author or editor,
%%%                        year is a 4-digit number, and abbrev is a
%%%                        3-letter condensation of important title
%%%                        words. Citation tags were automatically
%%%                        generated by software developed for the
%%%                        BibNet Project.
%%%
%%%                        In this bibliography, entries are sorted in
%%%                        publication order, using ``bibsort -byvolume.''
%%%
%%%                        The checksum field above contains a CRC-16
%%%                        checksum as the first value, followed by the
%%%                        equivalent of the standard UNIX wc (word
%%%                        count) utility output of lines, words, and
%%%                        characters.  This is produced by Robert
%%%                        Solovay's checksum utility."
%%%     }
%%% ====================================================================
@Preamble{"\input bibnames.sty" #
    "\def \TM {${}^{\sc TM}$}"
}

%%% ====================================================================
%%% Acknowledgement abbreviations:
@String{ack-nhfb = "Nelson H. F. Beebe,
                    University of Utah,
                    Department of Mathematics, 110 LCB,
                    155 S 1400 E RM 233,
                    Salt Lake City, UT 84112-0090, USA,
                    Tel: +1 801 581 5254,
                    FAX: +1 801 581 4148,
                    e-mail: \path|beebe@math.utah.edu|,
                            \path|beebe@acm.org|,
                            \path|beebe@computer.org| (Internet),
                    URL: \path|https://www.math.utah.edu/~beebe/|"}

%%% ====================================================================
%%% Journal abbreviations:
@String{j-TMIS                  = "ACM Transactions on Management Information
                                  Systems (TMIS)"}

%%% ====================================================================
%%% Bibliography entries:
@Article{Chen:2010:EWF,
  author =       "Hsinchun Chen",
  title =        "Editorial: {Welcome} to the first issue of {ACM
                 TMIS}",
  journal =      j-TMIS,
  volume =       "1",
  number =       "1",
  pages =        "1:1--1:??",
  month =        dec,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1877725.1877726",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 28 11:02:24 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "1",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Davis:2010:IFF,
  author =       "Gordon B. Davis and Paul Gray and Stuart Madnick and
                 Jay F. Nunamaker and Ralph Sprague and Andrew Whinston",
  title =        "Ideas for the future of the {IS} field",
  journal =      j-TMIS,
  volume =       "1",
  number =       "1",
  pages =        "2:1--2:??",
  month =        dec,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1877725.1877727",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 28 11:02:24 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "2",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Wang:2010:DIS,
  author =       "Jingguo Wang and Nan Xiao and H. Raghav Rao",
  title =        "Drivers of information security search behavior: an
                 investigation of network attacks and vulnerability
                 disclosures",
  journal =      j-TMIS,
  volume =       "1",
  number =       "1",
  pages =        "3:1--3:??",
  month =        dec,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1877725.1877728",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 28 11:02:24 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "3",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Ba:2010:WGS,
  author =       "Sulin Ba and Dan Ke and Jan Stallaert and Zhongju
                 Zhang",
  title =        "Why give away something for nothing? {Investigating}
                 virtual goods pricing and permission strategies",
  journal =      j-TMIS,
  volume =       "1",
  number =       "1",
  pages =        "4:1--4:??",
  month =        dec,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1877725.1877729",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 28 11:02:24 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "4",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Cao:2010:MDA,
  author =       "Lan Cao and Balasubramaniam Ramesh and Tarek
                 Abdel-Hamid",
  title =        "Modeling dynamics in agile software development",
  journal =      j-TMIS,
  volume =       "1",
  number =       "1",
  pages =        "5:1--5:??",
  month =        dec,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1877725.1877730",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 28 11:02:24 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "5",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Arazy:2010:SCW,
  author =       "Ofer Arazy and Arie Croitoru",
  title =        "The sustainability of corporate wikis: a time-series
                 analysis of activity patterns",
  journal =      j-TMIS,
  volume =       "1",
  number =       "1",
  pages =        "6:1--6:??",
  month =        dec,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1877725.1877731",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 28 11:02:24 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "6",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Fu:2010:PPT,
  author =       "Yu Fu and Zhiyuan Chen and Gunes Koru and Aryya
                 Gangopadhyay",
  title =        "A privacy protection technique for publishing data
                 mining models and research data",
  journal =      j-TMIS,
  volume =       "1",
  number =       "1",
  pages =        "7:1--7:??",
  month =        dec,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1877725.1877732",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 28 11:02:24 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "7",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Chen:2011:EDS,
  author =       "Hsinchun Chen",
  title =        "Editorial: {Design} science, grand challenges, and
                 societal impacts",
  journal =      j-TMIS,
  volume =       "2",
  number =       "1",
  pages =        "1:1--1:??",
  month =        mar,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1929916.1929917",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 28 11:02:25 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "1",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Chau:2011:VWS,
  author =       "Michael Chau",
  title =        "Visualizing {Web} search results using glyphs:
                 {Design} and evaluation of a flower metaphor",
  journal =      j-TMIS,
  volume =       "2",
  number =       "1",
  pages =        "2:1--2:??",
  month =        mar,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1929916.1929918",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 28 11:02:25 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "2",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Kuo:2011:LAG,
  author =       "Feng-Yang Kuo and Chun-Po Yin",
  title =        "A linguistic analysis of group support systems
                 interactions for uncovering social realities of
                 organizations",
  journal =      j-TMIS,
  volume =       "2",
  number =       "1",
  pages =        "3:1--3:??",
  month =        mar,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1929916.1929919",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 28 11:02:25 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "3",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Kane:2011:MSI,
  author =       "Gerald C. Kane",
  title =        "A multimethod study of information quality in wiki
                 collaboration",
  journal =      j-TMIS,
  volume =       "2",
  number =       "1",
  pages =        "4:1--4:??",
  month =        mar,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1929916.1929920",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 28 11:02:25 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "4",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Dawson:2011:UTA,
  author =       "Gregory S. Dawson and Richard T. Watson",
  title =        "Uncovering and testing archetypes of effective public
                 sector {CIOs}",
  journal =      j-TMIS,
  volume =       "2",
  number =       "1",
  pages =        "5:1--5:??",
  month =        mar,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1929916.1929921",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 28 11:02:25 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "5",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Dey:2011:CUW,
  author =       "Debabrata Dey and Ming Fan and Gang Peng",
  title =        "Computer use and wage returns: {The} complementary
                 roles of {IT}-related human capital and nonroutine
                 tasks",
  journal =      j-TMIS,
  volume =       "2",
  number =       "1",
  pages =        "6:1--6:??",
  month =        mar,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1929916.1929922",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 28 11:02:25 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "6",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Hu:2011:AIS,
  author =       "Paul Jen-Hwa Hu and Hsinchun Chen",
  title =        "Analyzing information systems researchers'
                 productivity and impacts: a perspective on the {$H$}
                 index",
  journal =      j-TMIS,
  volume =       "2",
  number =       "2",
  pages =        "7:1--7:??",
  month =        jun,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1985347.1985348",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Jul 22 08:37:49 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "7",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Bhattacharjee:2011:DGM,
  author =       "Sudip Bhattacharjee and Ram D. Gopal and James R.
                 Marsden and Ramesh Sankaranarayanan",
  title =        "Digital goods and markets: {Emerging} issues and
                 challenges",
  journal =      j-TMIS,
  volume =       "2",
  number =       "2",
  pages =        "8:1--8:??",
  month =        jun,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1985347.1985349",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Jul 22 08:37:49 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "8",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Uhl:2011:EUC,
  author =       "Matthias W. Uhl",
  title =        "Explaining {U.S.} consumer behavior with news
                 sentiment",
  journal =      j-TMIS,
  volume =       "2",
  number =       "2",
  pages =        "9:1--9:??",
  month =        jun,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1985347.1985350",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Jul 22 08:37:49 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "9",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Du:2011:RHS,
  author =       "Anna Ye Du and Sanjukta Das and Ram D. Gopal and R.
                 Ramesh",
  title =        "Risk hedging in storage grid markets: {Do} options add
                 value to forwards?",
  journal =      j-TMIS,
  volume =       "2",
  number =       "2",
  pages =        "10:1--10:??",
  month =        jun,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1985347.1985351",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Jul 22 08:37:49 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "10",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Liu:2011:WDW,
  author =       "Jun Liu and Sudha Ram",
  title =        "Who does what: {Collaboration} patterns in the
                 {Wikipedia} and their impact on article quality",
  journal =      j-TMIS,
  volume =       "2",
  number =       "2",
  pages =        "11:1--11:??",
  month =        jun,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1985347.1985352",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Jul 22 08:37:49 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "11",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Mcknight:2011:TST,
  author =       "D. Harrison Mcknight and Michelle Carter and Jason
                 Bennett Thatcher and Paul F. Clay",
  title =        "Trust in a specific technology: an investigation of
                 its components and measures",
  journal =      j-TMIS,
  volume =       "2",
  number =       "2",
  pages =        "12:1--12:??",
  month =        jun,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1985347.1985353",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Jul 22 08:37:49 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "12",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Tuzhilin:2011:KMR,
  author =       "Alexander Tuzhilin",
  title =        "Knowledge management revisited: {Old Dogs}, {New}
                 tricks",
  journal =      j-TMIS,
  volume =       "2",
  number =       "3",
  pages =        "13:1--13:??",
  month =        oct,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2019618.2019619",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sun Nov 6 07:18:27 MST 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "13",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Sutanto:2011:ESV,
  author =       "Juliana Sutanto and Atreyi Kankanhalli and Bernard
                 Cheng Yian Tan",
  title =        "Eliciting a sense of virtual community among knowledge
                 contributors",
  journal =      j-TMIS,
  volume =       "2",
  number =       "3",
  pages =        "14:1--14:??",
  month =        oct,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2019618.2019620",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sun Nov 6 07:18:27 MST 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "14",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Peng:2011:LSC,
  author =       "Jing Peng and Daniel D. Zeng and Zan Huang",
  title =        "Latent subject-centered modeling of collaborative
                 tagging: an application in social search",
  journal =      j-TMIS,
  volume =       "2",
  number =       "3",
  pages =        "15:1--15:??",
  month =        oct,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2019618.2019621",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sun Nov 6 07:18:27 MST 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "15",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Masud:2011:CBM,
  author =       "Mohammad M. Masud and Tahseen M. Al-Khateeb and Kevin
                 W. Hamlen and Jing Gao and Latifur Khan and Jiawei Han
                 and Bhavani Thuraisingham",
  title =        "Cloud-based malware detection for evolving data
                 streams",
  journal =      j-TMIS,
  volume =       "2",
  number =       "3",
  pages =        "16:1--16:??",
  month =        oct,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2019618.2019622",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sun Nov 6 07:18:27 MST 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "16",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Schmidt-Rauch:2011:TTA,
  author =       "Susanne Schmidt-Rauch and Gerhard Schwabe",
  title =        "From telesales to tele-advisory in travel agencies:
                 {Business} problems, generic design goals and
                 requirements",
  journal =      j-TMIS,
  volume =       "2",
  number =       "3",
  pages =        "17:1--17:??",
  month =        oct,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2019618.2019623",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sun Nov 6 07:18:27 MST 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "17",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Huang:2011:MTC,
  author =       "Ke-Wei Huang and Zhuolun Li",
  title =        "A multilabel text classification algorithm for
                 labeling risk factors in {SEC} form {10-K}",
  journal =      j-TMIS,
  volume =       "2",
  number =       "3",
  pages =        "18:1--18:??",
  month =        oct,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2019618.2019624",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sun Nov 6 07:18:27 MST 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "18",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Lin:2011:SPM,
  author =       "Ming-Chih Lin and Anthony J. T. Lee and Rung-Tai Kao
                 and Kuo-Tay Chen",
  title =        "Stock price movement prediction using representative
                 prototypes of financial reports",
  journal =      j-TMIS,
  volume =       "2",
  number =       "3",
  pages =        "19:1--19:??",
  month =        oct,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2019618.2019625",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sun Nov 6 07:18:27 MST 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "19",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Nunamaker:2011:TBV,
  author =       "Jay F. {Nunamaker, Jr.} and Robert O. Briggs",
  title =        "Toward a broader vision for {Information Systems}",
  journal =      j-TMIS,
  volume =       "2",
  number =       "4",
  pages =        "20:1--20:??",
  month =        dec,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2070710.2070711",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Mar 16 15:06:39 MDT 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "In December of 2009, several founders of the
                 Information Systems (IS) academic discipline gathered
                 for a panel discussion at the International Conference
                 on Information Systems to present their visions for the
                 future of the field, and their comments were summarized
                 in the inaugural issue of TMIS [Davis et al., 2010; J.
                 F. J. Nunamaker et al., 1991]. To assure a robust
                 future, they argued, IS journals, conferences,
                 reviewers, promotion committees, teachers, researchers,
                 and curriculum developers must broaden the scope of IS.
                 This article explores the need for a broader vision to
                 drive future development of the IS discipline.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "20",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Padmanabhan:2011:IOS,
  author =       "Balaji Padmanabhan and Alan Hevner and Michael Cuenco
                 and Crystal Shi",
  title =        "From information to operations: {Service} quality and
                 customer retention",
  journal =      j-TMIS,
  volume =       "2",
  number =       "4",
  pages =        "21:1--21:??",
  month =        dec,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2070710.2070712",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Mar 16 15:06:39 MDT 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "In business, information is abundant. Yet, effective
                 use of that information to inform and drive business
                 operations is a challenge. Our industry-university
                 collaborative project draws from a rich dataset of
                 commercial demographics, transaction history, product
                 features, and Service Quality Index (SQI) factors on
                 shipping transactions at FedEx. We apply inductive
                 methods to understand and predict customer churn in a
                 noncontractual setting. Results identify several SQI
                 variables as important determinants of churn across a
                 variety of analytic approaches. Building on this we
                 propose the design of a Business Intelligence (BI)
                 dashboard as an innovative approach for increasing
                 customer retention by identifying potential churners
                 based on combinations of predictor variables such as
                 demographics and SQI factors. This empirical study
                 contributes to BI research and practice by
                 demonstrating the application of data analytics to the
                 fundamental business operations problem of customer
                 churn.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "21",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Rui:2011:DSB,
  author =       "Huaxia Rui and Andrew Whinston",
  title =        "Designing a social-broadcasting-based business
                 intelligence system",
  journal =      j-TMIS,
  volume =       "2",
  number =       "4",
  pages =        "22:1--22:??",
  month =        dec,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2070710.2070713",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Mar 16 15:06:39 MDT 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "The rise of social media has fundamentally changed the
                 way information is produced, disseminated, and consumed
                 in the digital age, which has profound economic and
                 business effects. Among many different types of social
                 media, social broadcasting networks such as Twitter in
                 the U.S. and `Weibo' in China are particularly
                 interesting from a business perspective. In the case of
                 Twitter, the huge amounts of real-time data with
                 extremely rich text, along with valuable structural
                 information, makes Twitter a great platform to build
                 Business Intelligence (BI) systems. We propose a
                 framework of social-broadcasting-based BI systems that
                 utilizes real-time information extracted from these
                 data with text mining techniques. To demonstrate this
                 framework, we designed and implemented a Twitter-based
                 BI system that forecasts movie box office revenues
                 during the opening weekend and forecasts daily revenue
                 after 4 weeks. We found that incorporating information
                 from Twitter could reduce the Mean Absolute Percentage
                 Error (MAPE) by 44\% for the opening weekend and by
                 36\% for total revenue. For daily revenue forecasting,
                 including Twitter information into a baseline model
                 could reduce forecasting errors by 17.5\% on average.
                 On the basis of these results, we conclude that
                 social-broadcasting-based BI systems have great
                 potential and should be explored by both researchers
                 and practitioners.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "22",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Arora:2011:DSC,
  author =       "Hina Arora and T. S. Raghu and Ajay Vinze",
  title =        "Decision support for containing pandemic propagation",
  journal =      j-TMIS,
  volume =       "2",
  number =       "4",
  pages =        "23:1--23:??",
  month =        dec,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2070710.2070714",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Mar 16 15:06:39 MDT 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "This research addresses complexities inherent in
                 dynamic decision making settings represented by global
                 disasters such as influenza pandemics. By coupling a
                 theoretically grounded Equation-Based Modeling (EBM)
                 approach with more practically nuanced Agent-Based
                 Modeling (ABM) approach we address the inherent
                 heterogeneity of the `influenza pandemic' decision
                 space more effectively. In addition to modeling
                 contributions, results and findings of this study have
                 three important policy implications for pandemic
                 containment; first, an effective way of checking the
                 progression of a pandemic is a multipronged approach
                 that includes a combination of pharmaceutical and
                 non-pharmaceutical interventions. Second, mutual aid is
                 effective only when regions that have been affected by
                 the pandemic are sufficiently isolated from other
                 regions through non-pharmaceutical interventions. When
                 regions are not sufficiently isolated, mutual aid can
                 in fact be detrimental. Finally, intraregion
                 non-pharmaceutical interventions such as school
                 closures are more effective than interregion
                 nonpharmaceutical interventions such as border
                 closures.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "23",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Goes:2011:LCA,
  author =       "Paulo Goes and Noyan Ilk and Wei T. Yue and J. Leon
                 Zhao",
  title =        "Live-chat agent assignments to heterogeneous
                 e-customers under imperfect classification",
  journal =      j-TMIS,
  volume =       "2",
  number =       "4",
  pages =        "24:1--24:??",
  month =        dec,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2070710.2070715",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Mar 16 15:06:39 MDT 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Many e-commerce firms provide live-chat capability on
                 their Web sites to promote product sales and to offer
                 customer support. With increasing traffic on e-commerce
                 Web sites, providing such live-chat services requires a
                 good allocation of service resources to serve the
                 customers. When resources are limited, firms may
                 consider employing priority-processing and reserving
                 resources for high-value customers. In this article, we
                 model a reserve-based priority-processing policy for
                 e-commerce systems that have imperfect customer
                 classification. Two policy decisions considered in the
                 model are: (1) the number of agents exclusively
                 reserved for high-value customers, and (2) the
                 configuration of the classification system. We derive
                 explicit expressions for average waiting times of
                 high-value and low-value customer classes and define a
                 total waiting cost function. Through numerical
                 analysis, we study the impact of these two policy
                 decisions on average waiting times and total waiting
                 costs. Our analysis finds that reserving agents for
                 high-value customers may have negative consequences for
                 such customers under imperfect classification. Further,
                 we study the interaction between the two policy
                 decisions and discuss how one decision should be
                 modified with respect to a change in the other one in
                 order to keep the waiting costs minimized.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "24",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Lau:2011:TMP,
  author =       "Raymond Y. K. Lau and S. Y. Liao and Ron Chi-Wai Kwok
                 and Kaiquan Xu and Yunqing Xia and Yuefeng Li",
  title =        "Text mining and probabilistic language modeling for
                 online review spam detection",
  journal =      j-TMIS,
  volume =       "2",
  number =       "4",
  pages =        "25:1--25:??",
  month =        dec,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2070710.2070716",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Mar 16 15:06:39 MDT 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "In the era of Web 2.0, huge volumes of consumer
                 reviews are posted to the Internet every day. Manual
                 approaches to detecting and analyzing fake reviews
                 (i.e., spam) are not practical due to the problem of
                 information overload. However, the design and
                 development of automated methods of detecting fake
                 reviews is a challenging research problem. The main
                 reason is that fake reviews are specifically composed
                 to mislead readers, so they may appear the same as
                 legitimate reviews (i.e., ham). As a result,
                 discriminatory features that would enable individual
                 reviews to be classified as spam or ham may not be
                 available. Guided by the design science research
                 methodology, the main contribution of this study is the
                 design and instantiation of novel computational models
                 for detecting fake reviews. In particular, a novel text
                 mining model is developed and integrated into a
                 semantic language model for the detection of untruthful
                 reviews. The models are then evaluated based on a
                 real-world dataset collected from amazon.com. The
                 results of our experiments confirm that the proposed
                 models outperform other well-known baseline models in
                 detecting fake reviews. To the best of our knowledge,
                 the work discussed in this article represents the first
                 successful attempt to apply text mining methods and
                 semantic language models to the detection of fake
                 consumer reviews. A managerial implication of our
                 research is that firms can apply our design artifacts
                 to monitor online consumer reviews to develop effective
                 marketing or product design strategies based on genuine
                 consumer feedback posted to the Internet.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "25",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Marx:2011:SPR,
  author =       "Frederik Marx and J{\"o}rg H. Mayer and Robert
                 Winter",
  title =        "Six principles for redesigning executive information
                 systems-findings of a survey and evaluation of a
                 prototype",
  journal =      j-TMIS,
  volume =       "2",
  number =       "4",
  pages =        "26:1--26:??",
  month =        dec,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2070710.2070717",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Mar 16 15:06:39 MDT 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Information Systems (IS) meant to help senior managers
                 are known as Executive Information Systems (EIS).
                 Despite a five-decade tradition of such IS, many
                 executives still complain that they bear little
                 relevance to managing a company and, even more, fail to
                 accommodate their working style. The increasing
                 acceptance of IS among today's executives and
                 technological advances of the Internet era make the
                 present moment favorable for redesigning EIS. Following
                 the design science paradigm in IS research, this
                 article provides six principles for such a redesign. To
                 do so, we survey executives regarding their
                 requirements and the IS they currently use. We then
                 derive principles for a redesign to fill the gaps. They
                 address diverse areas: a comprehensive information
                 model, functions to better analyze and process
                 information, easy-to-use IS handling, a more flexible
                 IS architecture and data model, a proper information
                 management, and fast prototype implementation. Finally
                 a field test demonstrates and evaluates the utility of
                 our proposal by means of a prototype.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "26",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Niederman:2012:DSA,
  author =       "Fred Niederman and Salvatore T. March",
  title =        "Design science and the accumulation of knowledge in
                 the information systems discipline",
  journal =      j-TMIS,
  volume =       "3",
  number =       "1",
  pages =        "1:1--1:??",
  month =        apr,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2151163.2151164",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Nov 6 19:02:08 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Design science has emerged as an important research
                 paradigm in the information systems (IS) discipline,
                 and much has been written on how it should be conducted
                 and evaluated (e.g., Hevner et al. [2004]; Walls et al.
                 [1992]; Vaishnavi and Kuechler [2007]; Kuechler and
                 Vaishnavi [2008]; Peffers et al. [2007]; Iivari [2010];
                 Pigneur [2011]). We contend that, as a socio-technical
                 discipline, IS research must address the interaction
                 between design and behavior. We begin with a background
                 discussion of what we mean by IS research and the
                 nature of the relationship between design and
                 behavioral approaches to IS research. We discuss the
                 nature of design, design science, and IT artifacts
                 within information systems research and describe the
                 importance of linking design and behavioral
                 perspectives. We illustrate several key points using
                 selected articles recently published in ACM
                 Transactions on Management Information Systems
                 [Schmidt-Rauch and Schwabe 2011; Lau et al. 2011]. We
                 conclude with a vision of IS research in which the
                 capabilities and affordances of IT artifacts are
                 incorporated into behavioral studies; the results of
                 behavioral studies are utilized in the development and
                 evaluation of IT artifacts; and both behavioral and
                 design perspectives are used to address the important
                 problems of our constituent community.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "1",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Basoglu:2012:ERW,
  author =       "K. Asli Basoglu and Mark A. Fuller and Joseph S.
                 Valacich",
  title =        "Enhancement of recall within technology-mediated teams
                 through the use of online visual artifacts",
  journal =      j-TMIS,
  volume =       "3",
  number =       "1",
  pages =        "2:1--2:??",
  month =        apr,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2151163.2151165",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Nov 6 19:02:08 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Given the distributed nature of modern organizations,
                 the use of technology-mediated teams is a critical
                 aspect of their success. These teams use various media
                 that are arguably less personal than face-to-face
                 communication. One factor influencing the success of
                 these teams is their ability to develop an
                 understanding of who knows what during the initial team
                 development stage. However, this development of
                 understanding within dispersed teams may be impeded
                 because of the limitations of technology-enabled
                 communication environments. Past research has found
                 that a limited understanding of team member
                 capabilities hinders team performance. As such, this
                 article investigates mechanisms for improving the
                 recall of individuals within dispersed teams. Utilizing
                 the input-process-output model to conceptualize the
                 group interaction process, three input factors-visual
                 artifacts (i.e., a computer-generated image of each
                 team member), team size, and work interruptions-are
                 manipulated to assess their influence on a person's
                 ability to recall important characteristics of their
                 virtual team members. Results show that visual
                 artifacts significantly increase the recall of
                 individuals' information. However, high-urgency
                 interruptions significantly deteriorate the recall of
                 individuals, regardless of the visual artifact or team
                 size. These findings provide theoretical and practical
                 implications on knowledge acquisition and project
                 success within technology-mediated teams.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "2",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Adomavicius:2012:IDC,
  author =       "Gediminas Adomavicius and Jingjing Zhang",
  title =        "Impact of data characteristics on recommender systems
                 performance",
  journal =      j-TMIS,
  volume =       "3",
  number =       "1",
  pages =        "3:1--3:??",
  month =        apr,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2151163.2151166",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Nov 6 19:02:08 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "This article investigates the impact of rating data
                 characteristics on the performance of several popular
                 recommendation algorithms, including user-based and
                 item-based collaborative filtering, as well as matrix
                 factorization. We focus on three groups of data
                 characteristics: rating space, rating frequency
                 distribution, and rating value distribution. A sampling
                 procedure was employed to obtain different rating data
                 subsamples with varying characteristics; recommendation
                 algorithms were used to estimate the predictive
                 accuracy for each sample; and linear regression-based
                 models were used to uncover the relationships between
                 data characteristics and recommendation accuracy.
                 Experimental results on multiple rating datasets show
                 the consistent and significant effects of several data
                 characteristics on recommendation accuracy.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "3",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Robinson:2012:DDB,
  author =       "William N. Robinson and Arash Akhlaghi and Tianjie
                 Deng and Ali Raza Syed",
  title =        "Discovery and diagnosis of behavioral transitions in
                 patient event streams",
  journal =      j-TMIS,
  volume =       "3",
  number =       "1",
  pages =        "4:1--4:??",
  month =        apr,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2151163.2151167",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Nov 6 19:02:08 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Users with cognitive impairments use assistive
                 technology (AT) as part of a clinical treatment plan.
                 As the AT interface is manipulated, data stream mining
                 techniques are used to monitor user goals. In this
                 context, real-time data mining aids clinicians in
                 tracking user behaviors as they attempt to achieve
                 their goals. Quality metrics over stream-mined models
                 identify potential changes in user goal attainment, as
                 the user learns his or her personalized emailing
                 system. When the quality of some data-mined models
                 varies significantly from nearby models-as defined by
                 quality metrics-the user's behavior is then flagged as
                 a significant behavioral change. The specific changes
                 in user behavior are then characterized by differencing
                 the data-mined decision tree models. This article
                 describes how model quality monitoring and decision
                 tree differencing can aid in recognition and diagnoses
                 of behavioral changes in a case study of cognitive
                 rehabilitation via emailing. The technique may be more
                 widely applicable to other real-time data-intensive
                 analysis problems.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "4",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Zhang:2012:DWM,
  author =       "Zhu Zhang and Xin Li and Yubo Chen",
  title =        "Deciphering word-of-mouth in social media: Text-based
                 metrics of consumer reviews",
  journal =      j-TMIS,
  volume =       "3",
  number =       "1",
  pages =        "5:1--5:??",
  month =        apr,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2151163.2151168",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Nov 6 19:02:08 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Enabled by Web 2.0 technologies, social media provide
                 an unparalleled platform for consumers to share their
                 product experiences and opinions through word-of-mouth
                 (WOM) or consumer reviews. It has become increasingly
                 important to understand how WOM content and metrics
                 influence consumer purchases and product sales. By
                 integrating marketing theories with text mining
                 techniques, we propose a set of novel measures that
                 focus on sentiment divergence in consumer product
                 reviews. To test the validity of these metrics, we
                 conduct an empirical study based on data from
                 Amazon.com and BN.com (Barnes {\&} Noble). The results
                 demonstrate significant effects of our proposed
                 measures on product sales. This effect is not fully
                 captured by nontextual review measures such as
                 numerical ratings. Furthermore, in capturing the sales
                 effect of review content, our divergence metrics are
                 shown to be superior to and more appropriate than some
                 commonly used textual measures the literature. The
                 findings provide important insights into the business
                 impact of social media and user-generated content, an
                 emerging problem in business intelligence research.
                 From a managerial perspective, our results suggest that
                 firms should pay special attention to textual content
                 information when managing social media and, more
                 importantly, focus on the right measures.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "5",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Malhotra:2012:HVT,
  author =       "Arvind Malhotra and Ann Majchrzak",
  title =        "How virtual teams use their virtual workspace to
                 coordinate knowledge",
  journal =      j-TMIS,
  volume =       "3",
  number =       "1",
  pages =        "6:1--6:??",
  month =        apr,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2151163.2151169",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Nov 6 19:02:08 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Virtual team members increasingly rely on virtual
                 workspace tools to coordinate knowledge that each
                 individual brings to the team. How the use of these
                 tools affects knowledge coordination within virtual
                 teams is not well understood. We distinguish between
                 tools as features and the use of the virtual workspace
                 as providing affordances for behaviors. Using
                 situational awareness theory, we hypothesized two
                 affordances of virtual workspaces that facilitate
                 knowledge coordination. Using trading zone theory, we
                 hypothesized two forms of trading zones created by
                 features of virtual workspaces and the impact of these
                 trading zones on the creation of affordances for team
                 members. Members of 54 teams were asked about the
                 affordances of the virtual workspace, and team leaders
                 were asked about specific tools provided to the team.
                 Our hypothesized model was supported: the different
                 forms of trading zones were differentially related to
                 the different affordances and on affordances were
                 related to knowledge coordination satisfaction.
                 Theoretical implications focus on the distinction
                 between features and affordances and on the
                 identification of specific features that affect
                 specific affordances. Practical implications for
                 managers and engineers supporting virtual teams include
                 the utility of becoming knowledgeable about different
                 forms of trading zones that virtual workspaces can
                 provide and understanding the relationship between
                 trading zones and different affordances.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "6",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{vanderAalst:2012:PMO,
  author =       "Wil van der Aalst",
  title =        "Process Mining: Overview and Opportunities",
  journal =      j-TMIS,
  volume =       "3",
  number =       "2",
  pages =        "7:1--7:??",
  month =        jul,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2229156.2229157",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Nov 6 19:02:09 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Over the last decade, process mining emerged as a new
                 research field that focuses on the analysis of
                 processes using event data. Classical data mining
                 techniques such as classification, clustering,
                 regression, association rule learning, and
                 sequence/episode mining do not focus on business
                 process models and are often only used to analyze a
                 specific step in the overall process. Process mining
                 focuses on end-to-end processes and is possible because
                 of the growing availability of event data and new
                 process discovery and conformance checking techniques.
                 Process models are used for analysis (e.g., simulation
                 and verification) and enactment by BPM/WFM systems.
                 Previously, process models were typically made by hand
                 without using event data. However, activities executed
                 by people, machines, and software leave trails in
                 so-called event logs. Process mining techniques use
                 such logs to discover, analyze, and improve business
                 processes. Recently, the Task Force on Process Mining
                 released the Process Mining Manifesto. This manifesto
                 is supported by 53 organizations and 77 process mining
                 experts contributed to it. The active involvement of
                 end-users, tool vendors, consultants, analysts, and
                 researchers illustrates the growing significance of
                 process mining as a bridge between data mining and
                 business process modeling. The practical relevance of
                 process mining and the interesting scientific
                 challenges make process mining one of the ``hot''
                 topics in Business Process Management (BPM). This
                 article introduces process mining as a new research
                 field and summarizes the guiding principles and
                 challenges described in the manifesto.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "7",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Shan:2012:OAC,
  author =       "Zhe Shan and Akhil Kumar",
  title =        "Optimal Adapter Creation for Process Composition in
                 Synchronous vs. Asynchronous Communication",
  journal =      j-TMIS,
  volume =       "3",
  number =       "2",
  pages =        "8:1--8:??",
  month =        jul,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2229156.2229160",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Nov 6 19:02:09 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "A key issue in process-aware e-commerce collaboration
                 is to orchestrate business processes of multiple
                 business partners throughout a supply chain network in
                 an automated and seamless way. Since each partner has
                 its own internal processes with different control flow
                 structures and message interfaces, the real challenge
                 lies in verifying the correctness of process
                 collaboration, and reconciling conflicts in an
                 automated manner to make collaboration successful. The
                 purpose of business process adaptation is to mediate
                 the communication between independent processes to
                 overcome their mismatches and incompatibilities. The
                 goal of this article is to develop and compare
                 efficient approaches of optimal adapter (i.e. one that
                 minimizes the number of messages to be adapted)
                 creation for multiple interacting processes under both
                 synchronous and asynchronous communication. We start
                 with an analysis of interactions of each message pair,
                 and show how to identify incompatible cases and their
                 adaptation elements for both types of communication.
                 Then, we show how to extend this analysis into more
                 general cases involving M messages and N processes ( M,
                 N {$>$} 2). Further, we present optimal adapter
                 creation algorithms for both scenarios based on our
                 analysis technique. The algorithms were implemented in
                 a Java-based prototype system, and results of two
                 experiments are reported. We compare and discuss the
                 insights gained about adapter creation in these two
                 scenarios.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "8",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Huang:2012:TNP,
  author =       "Zan Huang and Huimin Zhao and Dan Zhu",
  title =        "Two New Prediction-Driven Approaches to Discrete
                 Choice Prediction",
  journal =      j-TMIS,
  volume =       "3",
  number =       "2",
  pages =        "9:1--9:??",
  month =        jul,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2229156.2229159",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Nov 6 19:02:09 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "The ability to predict consumer choices is essential
                 in understanding the demand structure of products and
                 services. Typical discrete choice models that are
                 targeted at providing an understanding of the
                 behavioral process leading to choice outcomes are
                 developed around two main assumptions: the existence of
                 a utility function that represents the preferences over
                 a choice set and the relatively simple and
                 interpretable functional form for the utility function
                 with respect to attributes of alternatives and decision
                 makers. These assumptions lead to models that can be
                 easily interpreted to provide insights into the effects
                 of individual variables, such as price and promotion,
                 on consumer choices. However, these restrictive
                 assumptions might impede the ability of such
                 theory-driven models to deliver accurate predictions
                 and forecasts. In this article, we develop novel
                 approaches targeted at providing more accurate choice
                 predictions. Specifically, we propose two
                 prediction-driven approaches: pairwise preference
                 learning using classification techniques and ranking
                 function learning using evolutionary computation. We
                 compare our proposed approaches with a multiclass
                 classification approach, as well as a standard discrete
                 choice model. Our empirical results show that the
                 proposed approaches achieved significantly higher
                 choice prediction accuracy.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "9",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Ngo-Ye:2012:AOR,
  author =       "Thomas L. Ngo-Ye and Atish P. Sinha",
  title =        "Analyzing Online Review Helpfulness Using a
                 Regressional {ReliefF}-Enhanced Text Mining Method",
  journal =      j-TMIS,
  volume =       "3",
  number =       "2",
  pages =        "10:1--10:??",
  month =        jul,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2229156.2229158",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Nov 6 19:02:09 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Within the emerging context of Web 2.0 social media,
                 online customer reviews are playing an increasingly
                 important role in disseminating information,
                 facilitating trust, and promoting commerce in the
                 e-marketplace. The sheer volume of customer reviews on
                 the web produces information overload for readers.
                 Developing a system that can automatically identify the
                 most helpful reviews would be valuable to businesses
                 that are interested in gathering informative and
                 meaningful customer feedback. Because the target
                 variable---review helpfulness---is continuous, common
                 feature selection techniques from text classification
                 cannot be applied. In this article, we propose and
                 investigate a text mining model, enhanced using the
                 Regressional ReliefF (RReliefF) feature selection
                 method, for predicting the helpfulness of online
                 reviews from Amazon.com. We find that RReliefF
                 significantly outperforms two popular dimension
                 reduction methods. This study is the first to
                 investigate and compare different dimension reduction
                 techniques in the context of applying text regression
                 for predicting online review helpfulness. Another
                 contribution is that our analysis of the keywords
                 selected by RReliefF reveals meaningful feature
                 groupings.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "10",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Nussbaumer:2012:EVC,
  author =       "Philipp Nussbaumer and Inu Matter and Gerhard
                 Schwabe",
  title =        "``Enforced'' vs. ``Casual'' Transparency --- Findings
                 from {IT}-Supported Financial Advisory Encounters",
  journal =      j-TMIS,
  volume =       "3",
  number =       "2",
  pages =        "11:1--11:??",
  month =        jul,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2229156.2229161",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Nov 6 19:02:09 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "In sales-oriented service encounters like financial
                 advice, the client may perceive information and
                 interest asymmetries as a lack of transparency
                 regarding the advisor's activities. In this article, we
                 will discuss two design iterations of a supportive
                 tabletop application that we built to increase process
                 and information transparency as compared to the
                 traditional pen and paper encounters. While the first
                 iteration's design was ``enforcing'' transparency and
                 therefore proved to be a failure [Nussbaumer et al.
                 2011], we built the second iteration on design
                 rationales enabling more ``casual'' transparency.
                 Experimental evaluations show that the redesigned
                 system significantly increases the client's perceived
                 transparency, her perceived control of the encounter
                 and improves her perceived trustworthiness of and
                 satisfaction with the encounter. With these findings,
                 we contribute to (1) insight into the role of
                 transparency advisory encounter design; (2) design
                 solutions for establishing particular facets of
                 transparency and their potential instantiations in
                 tabletop systems; and (3) insight into the process of
                 designing for transparency with socio-technical
                 artifacts that are emergent as a result of design
                 activities.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "11",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Chiang:2012:BIA,
  author =       "Roger H. L. Chiang and Paulo Goes and Edward A.
                 Stohr",
  title =        "Business Intelligence and Analytics Education, and
                 Program Development: a Unique Opportunity for the
                 Information Systems Discipline",
  journal =      j-TMIS,
  volume =       "3",
  number =       "3",
  pages =        "12:1--12:??",
  month =        oct,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2361256.2361257",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Nov 6 19:02:10 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "``Big Data,'' huge volumes of data in both structured
                 and unstructured forms generated by the Internet,
                 social media, and computerized transactions, is
                 straining our technical capacity to manage it. More
                 importantly, the new challenge is to develop the
                 capability to understand and interpret the burgeoning
                 volume of data to take advantage of the opportunities
                 it provides in many human endeavors, ranging from
                 science to business. Data Science, and in business
                 schools, Business Intelligence and Analytics (BI{\&}A)
                 are emerging disciplines that seek to address the
                 demands of this new era. Big Data and BI{\&}A present
                 unique challenges and opportunities not only for the
                 research community, but also for Information Systems
                 (IS) programs at business schools. In this essay, we
                 provide a brief overview of BI{\&}A, speculate on the
                 role of BI{\&}A education in business schools, present
                 the challenges facing IS departments, and discuss the
                 role of IS curricula and program development, in
                 delivering BI{\&}A education. We contend that a new
                 vision for the IS discipline should address these
                 challenges.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "12",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Achananuparp:2012:WRT,
  author =       "Palakorn Achananuparp and Ee-Peng Lim and Jing Jiang
                 and Tuan-Anh Hoang",
  title =        "Who is Retweeting the Tweeters? {Modeling},
                 Originating, and Promoting Behaviors in the {Twitter}
                 Network",
  journal =      j-TMIS,
  volume =       "3",
  number =       "3",
  pages =        "13:1--13:??",
  month =        oct,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2361256.2361258",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Nov 6 19:02:10 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Real-time microblogging systems such as Twitter offer
                 users an easy and lightweight means to exchange
                 information. Instead of writing formal and lengthy
                 messages, microbloggers prefer to frequently broadcast
                 several short messages to be read by other users. Only
                 when messages are interesting, are they propagated
                 further by the readers. In this article, we examine
                 user behavior relevant to information propagation
                 through microblogging. We specifically use retweeting
                 activities among Twitter users to define and model
                 originating and promoting behavior. We propose a basic
                 model for measuring the two behaviors, a mutual
                 dependency model, which considers the mutual
                 relationships between the two behaviors, and a
                 range-based model, which considers the depth and reach
                 of users' original tweets. Next, we compare the three
                 behavior models and contrast them with the existing
                 work on modeling influential Twitter users. Last, to
                 demonstrate their applicability, we further employ the
                 behavior models to detect interesting events from
                 sudden changes in aggregated information propagation
                 behavior of Twitter users. The results will show that
                 the proposed behavior models can be effectively applied
                 to detect interesting events in the Twitter stream,
                 compared to the baseline tweet-based approaches.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "13",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Lu:2012:CRC,
  author =       "Hsin-Min Lu and Feng-Tse Tsai and Hsinchun Chen and
                 Mao-Wei Hung and Shu-Hsing Li",
  title =        "Credit Rating Change Modeling Using News and Financial
                 Ratios",
  journal =      j-TMIS,
  volume =       "3",
  number =       "3",
  pages =        "14:1--14:??",
  month =        oct,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2361256.2361259",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Nov 6 19:02:10 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Credit ratings convey credit risk information to
                 participants in financial markets, including investors,
                 issuers, intermediaries, and regulators. Accurate
                 credit rating information plays a crucial role in
                 supporting sound financial decision-making processes.
                 Most previous studies on credit rating modeling are
                 based on accounting and market information. Text data
                 are largely ignored despite the potential benefit of
                 conveying timely information regarding a firm's
                 outlook. To leverage the additional information in news
                 full-text for credit rating prediction, we designed and
                 implemented a news full-text analysis system that
                 provides firm-level coverage, topic, and sentiment
                 variables. The novel topic-specific sentiment variables
                 contain a large fraction of missing values because of
                 uneven news coverage. The missing value problem creates
                 a new challenge for credit rating prediction
                 approaches. We address this issue by developing a
                 missing-tolerant multinomial probit (MT-MNP) model,
                 which imputes missing values based on the Bayesian
                 theoretical framework. Our experiments using seven and
                 a half years of real-world credit ratings and news
                 full-text data show that (1) the overall news coverage
                 can explain future credit rating changes while the
                 aggregated news sentiment cannot; (2) topic-specific
                 news coverage and sentiment have statistically
                 significant impact on future credit rating changes; (3)
                 topic-specific negative sentiment has a more salient
                 impact on future credit rating changes compared to
                 topic-specific positive sentiment; (4) MT-MNP performs
                 better in predicting future credit rating changes
                 compared to support vector machines (SVM). The
                 performance gap as measured by macroaveraging F-measure
                 is small but consistent.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "14",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Wei:2012:UNA,
  author =       "Wei Wei and Sudha Ram",
  title =        "Using a Network Analysis Approach for Organizing
                 Social Bookmarking Tags and Enabling {Web} Content
                 Discovery",
  journal =      j-TMIS,
  volume =       "3",
  number =       "3",
  pages =        "15:1--15:??",
  month =        oct,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2361256.2361260",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Nov 6 19:02:10 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "This article describes an innovative approach to
                 reorganizing the tag space generated by social
                 bookmarking services. The objective of this work is to
                 enable effective search and discovery of Web content
                 using social bookmarking tags. Tags are metadata
                 generated by users for Web content annotation. Their
                 potential as effective Web search and discovery tool is
                 hindered by challenges such as, the tag space being
                 untidy due to ambiguity, and hidden or implicit
                 semantics. Using a novel analytics approach, we
                 conducted network analyses on tags and discovered that
                 tags are generated for different purposes and that
                 there are inherent relationships among tags. Our
                 approach can be used to extract the purposes of tags
                 and relationships among the tags and this information
                 can be used as facets to add structure and hierarchy to
                 reorganize the flat tag space. The semantics of
                 relationships and hierarchy in our proposed faceted
                 model of tags enable searches on annotated Web content
                 in an effective manner. We describe the implementation
                 of a prototype system called FASTS to demonstrate
                 feasibility and effectiveness of our approach.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "15",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Hu:2012:DVP,
  author =       "Nan Hu and Hasan Cavusoglu and Ling Liu and Chenkai
                 Ni",
  title =        "Do Vendors' Pricing Decisions Fully Reflect
                 Information in Online Reviews?",
  journal =      j-TMIS,
  volume =       "3",
  number =       "3",
  pages =        "16:1--16:??",
  month =        oct,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2361256.2361261",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Nov 6 19:02:10 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "By using online retail data collected from Amazon,
                 Barnes {\&} Nobel, and Pricegrabber, this paper
                 investigates whether online vendors' pricing decisions
                 fully reflect the information contained in various
                 components of customers' online reviews. The findings
                 suggest that there is inefficiency in vendors' pricing
                 decisions. Specifically, vendors do not appear to fully
                 understand the incremental predictive power of online
                 reviews in forecasting future sales when they adjust
                 their prices. However, they do understand demand
                 persistence. Interestingly, vendors reduce price if the
                 actual demand is higher than the expected demand
                 (positive demand shock). This phenomenon is attributed
                 to the advertising effect suggested in previous
                 literature and the intense competitiveness of
                 e-Commerce. Finally, we document that vendors do not
                 change their prices directly in response to online
                 reviews; their response to online reviews is through
                 forecasting consumer's future demand.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "16",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Lim:2013:BIA,
  author =       "Ee-Peng Lim and Hsinchun Chen and Guoqing Chen",
  title =        "Business Intelligence and Analytics: Research
                 Directions",
  journal =      j-TMIS,
  volume =       "3",
  number =       "4",
  pages =        "17:1--17:??",
  month =        jan,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2407740.2407741",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Apr 30 18:40:39 MDT 2013",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Business intelligence and analytics (BIA) is about the
                 development of technologies, systems, practices, and
                 applications to analyze critical business data so as to
                 gain new insights about business and markets. The new
                 insights can be used for improving products and
                 services, achieving better operational efficiency, and
                 fostering customer relationships. In this article, we
                 will categorize BIA research activities into three
                 broad research directions: (a) big data analytics, (b)
                 text analytics, and (c) network analytics. The article
                 aims to review the state-of-the-art techniques and
                 models and to summarize their use in BIA applications.
                 For each research direction, we will also determine a
                 few important questions to be addressed in future
                 research.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "17",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Zhang:2013:CMS,
  author =       "Bin Zhang and Andrew C. Thomas and Patrick Doreian and
                 David Krackhardt and Ramayya Krishnan",
  title =        "Contrasting Multiple Social Network Autocorrelations
                 for Binary Outcomes, With Applications To Technology
                 Adoption",
  journal =      j-TMIS,
  volume =       "3",
  number =       "4",
  pages =        "18:1--18:??",
  month =        jan,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2407740.2407742",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Apr 30 18:40:39 MDT 2013",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "The rise of socially targeted marketing suggests that
                 decisions made by consumers can be predicted not only
                 from their personal tastes and characteristics, but
                 also from the decisions of people who are close to them
                 in their networks. One obstacle to consider is that
                 there may be several different measures for closeness
                 that are appropriate, either through different types of
                 friendships, or different functions of distance on one
                 kind of friendship, where only a subset of these
                 networks may actually be relevant. Another is that
                 these decisions are often binary and more difficult to
                 model with conventional approaches, both conceptually
                 and computationally. To address these issues, we
                 present a hierarchical auto-probit model for individual
                 binary outcomes that uses and extends the machinery of
                 the auto-probit method for binary data. We demonstrate
                 the behavior of the parameters estimated by the
                 multiple network-regime auto-probit model (m-NAP) under
                 various sensitivity conditions, such as the impact of
                 the prior distribution and the nature of the structure
                 of the network. We also demonstrate several examples of
                 correlated binary data outcomes in networks of interest
                 to information systems, including the adoption of
                 caller ring-back tones, whose use is governed by direct
                 connection but explained by additional network
                 topologies.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "18",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Pervin:2013:FSC,
  author =       "Nargis Pervin and Fang Fang and Anindya Datta and
                 Kaushik Dutta and Debra Vandermeer",
  title =        "Fast, Scalable, and Context-Sensitive Detection of
                 Trending Topics in Microblog Post Streams",
  journal =      j-TMIS,
  volume =       "3",
  number =       "4",
  pages =        "19:1--19:??",
  month =        jan,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2407740.2407743",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Apr 30 18:40:39 MDT 2013",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Social networks, such as Twitter, can quickly and
                 broadly disseminate news and memes across both
                 real-world events and cultural trends. Such networks
                 are often the best sources of up-to-the-minute
                 information, and are therefore of considerable
                 commercial and consumer interest. The trending topics
                 that appear first on these networks represent an answer
                 to the age-old query ``what are people talking about?''
                 Given the incredible volume of posts (on the order of
                 45,000 or more per minute), and the vast number of
                 stories about which users are posting at any given
                 time, it is a formidable problem to extract trending
                 stories in real time. In this article, we describe a
                 method and implementation for extracting trending
                 topics from a high-velocity real-time stream of
                 microblog posts. We describe our approach and
                 implementation, and a set of experimental results that
                 show that our system can accurately find ``hot''
                 stories from high-rate Twitter-scale text streams.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "19",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Zhang:2013:PCN,
  author =       "Zhu Zhang and Chenhui Guo and Paulo Goes",
  title =        "Product Comparison Networks for Competitive Analysis
                 of Online Word-of-Mouth",
  journal =      j-TMIS,
  volume =       "3",
  number =       "4",
  pages =        "20:1--20:??",
  month =        jan,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2407740.2407744",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Apr 30 18:40:39 MDT 2013",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Enabled by Web 2.0 technologies social media provide
                 an unparalleled platform for consumers to share their
                 product experiences and opinions---through
                 word-of-mouth (WOM) or consumer reviews. It has become
                 increasingly important to understand how WOM content
                 and metrics thereof are related to consumer purchases
                 and product sales. By integrating network analysis with
                 text sentiment mining techniques, we propose product
                 comparison networks as a novel construct, computed from
                 consumer product reviews. To test the validity of these
                 product ranking measures, we conduct an empirical study
                 based on a digital camera dataset from Amazon.com. The
                 results demonstrate significant linkage between
                 network-based measures and product sales, which is not
                 fully captured by existing review measures such as
                 numerical ratings. The findings provide important
                 insights into the business impact of social media and
                 user-generated content, an emerging problem in business
                 intelligence research. From a managerial perspective,
                 our results suggest that WOM in social media also
                 constitutes a competitive landscape for firms to
                 understand and manipulate.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "20",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Yaraghi:2013:NEH,
  author =       "Niam Yaraghi and Anna Ye Du and Raj Sharman and Ram D.
                 Gopal and R. Ramesh",
  title =        "Network Effects in Health Information Exchange
                 Growth",
  journal =      j-TMIS,
  volume =       "4",
  number =       "1",
  pages =        "1:1--1:??",
  month =        apr,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2445560.2445561",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Apr 30 18:40:41 MDT 2013",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "The importance of the Healthcare Information Exchange
                 (HIE) in increasing healthcare quality and reducing
                 risks and costs has led to greater interest in
                 identifying factors that enhance adoption and
                 meaningful use of HIE by healthcare providers. In this
                 research we study the interlinked network effects
                 between two different groups of physicians --- primary
                 care physicians and specialists --- as significant
                 factors in increasing the growth of each group in an
                 exchange. An analytical model of interlinked and
                 intragroup influences on adoption is developed using
                 the Bass diffusion model as a basis. Adoption data on
                 1,060 different primary and secondary care physicians
                 over 32 consecutive months was used to test the model.
                 The results indicate not only the presence of
                 interlinked effects, but also that their influence is
                 stronger than that of the intragroup. Further, the
                 influence of primary care physicians on specialists is
                 stronger than that of specialists on primary care
                 physicians. We also provide statistical evidence that
                 the new model performs better than the conventional
                 Bass model, and the assumptions of diffusion symmetry
                 in the market are statistically valid. Together, the
                 findings provide important guidelines on triggers that
                 enhance the overall growth of HIE and potential
                 marketing strategies for HIE services.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "1",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Valecha:2013:DMC,
  author =       "Rohit Valecha and Raj Sharman and H. Raghav Rao and
                 Shambhu Upadhyaya",
  title =        "A Dispatch-Mediated Communication Model for Emergency
                 Response Systems",
  journal =      j-TMIS,
  volume =       "4",
  number =       "1",
  pages =        "2:1--2:??",
  month =        apr,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2445560.2445562",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Apr 30 18:40:41 MDT 2013",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "The current state of emergency communication is
                 dispatch-mediated (the messages from the scene are
                 directed towards the responders and agencies through
                 the dispatch agency). These messages are logged in
                 electronic documents called incident reports, which are
                 useful in monitoring the incident, off-site
                 supervision, resource allocation, and post-incident
                 analysis. However, these messages do not adhere to any
                 particular structure, and there is no set format. The
                 lack of standards creates a problem for sharing
                 information among systems and responders and has a
                 detrimental impact on systems interoperability. In this
                 article, we develop a National Information Exchange
                 Model (NIEM) and Universal Core (UCORE) compliant
                 messaging model, considering message structures and
                 formats, to foster message standardization.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "2",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Choi:2013:ISI,
  author =       "Jae Choi and Derek L. Nazareth and Hemant K. Jain",
  title =        "The Impact of {SOA} Implementation on {IT}-Business
                 Alignment: a System Dynamics Approach",
  journal =      j-TMIS,
  volume =       "4",
  number =       "1",
  pages =        "3:1--3:??",
  month =        apr,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2445560.2445563",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Apr 30 18:40:41 MDT 2013",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "With firms facing intense rivalry, globalization, and
                 time-to-market pressures, the need for organizational
                 agility assumes greater importance. One of the primary
                 vehicles for achieving organizational agility is the
                 use of agile information systems [IS] and the close
                 alignment of information technologies [IT] with
                 business. However, IS is often viewed as an impediment
                 to organization agility. Recently, service-oriented
                 architecture [SOA] has emerged as a prominent IS
                 agility-enhancing technology. The fundamental question
                 of how SOA can enhance organization agility and foster
                 closer alignment between IT and business has not been
                 adequately addressed. The dynamic interaction among
                 external business environmental factors, organizational
                 agility, and IS architecture makes the process of
                 keeping IT and business aligned more complex. This
                 study uses a design science approach to build a system
                 dynamics model to examine the effect of employing
                 alternative SOA implementation strategies in various
                 organizational and external business environments on
                 the IT business alignment and IS cost. The results
                 provide insights into the shaping of IT-business
                 alignment. Additionally, the system dynamics model
                 serves as a tool for supporting managerial decisions
                 related to SOA implementation.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "3",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Ullah:2013:SRB,
  author =       "Azmat Ullah and Richard Lai",
  title =        "A Systematic Review of Business and Information
                 Technology Alignment",
  journal =      j-TMIS,
  volume =       "4",
  number =       "1",
  pages =        "4:1--4:??",
  month =        apr,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2445560.2445564",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Apr 30 18:40:41 MDT 2013",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Business organizations have become heavily dependent
                 on information technology (IT) services. The process of
                 alignment is defined as the mutual synchronization of
                 business goals and IT services. However, achieving
                 mature alignment between business and IT is difficult
                 due to the rapid changes in the business and IT
                 environments. This article provides a systematic review
                 of studies on the alignment of business and IT. The
                 research articles reviewed are based on topics of
                 alignment, the definition of alignment, history,
                 alignment challenges, phases of alignment, alignment
                 measurement approaches, the importance of alignment in
                 business industries, how software engineering helps in
                 better alignment, and the role of the business
                 environment in aligning business with IT. It aims to
                 present a thorough understanding of business-IT
                 alignment and to provide a list of future research
                 directions regarding alignment. To perform the
                 systematic review, we used the guidelines developed by
                 Kitchenham for reviewing the available research papers
                 relevant to our topic.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "4",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Gill:2013:FUM,
  author =       "T. Grandon Gill and Alan R. Hevner",
  title =        "A Fitness-Utility Model for Design Science Research",
  journal =      j-TMIS,
  volume =       "4",
  number =       "2",
  pages =        "5:1--5:??",
  month =        aug,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2499962.2499963",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 13 06:54:56 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Current thinking in design science research (DSR)
                 defines the usefulness of the design artifact in a
                 relevant problem environment as the primary research
                 goal. Here we propose a complementary evaluation model
                 for DSR. Drawing from evolutionary economics, we define
                 a fitness-utility model that better captures the
                 evolutionary nature of design improvements and the
                 essential DSR nature of searching for a satisfactory
                 design across a fitness landscape. Our goal is to move
                 DSR to more meaningful evaluations of design artifacts
                 for sustainable impacts. A key premise of this new
                 thinking is that the evolutionary fitness of a design
                 artifact is more valuable than its immediate
                 usefulness. We conclude with a discussion of the
                 strengths and challenges of the fitness-utility model
                 for the performance of rigorous and relevant DSR.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "5",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Wu:2013:DKM,
  author =       "Jiming Wu and Clyde W. Holsapple",
  title =        "Does Knowledge Management Matter? {The} Empirical
                 Evidence from Market-Based Valuation",
  journal =      j-TMIS,
  volume =       "4",
  number =       "2",
  pages =        "6:1--6:??",
  month =        aug,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2500750",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 13 06:54:56 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Information technology is inseparable from
                 contemporary knowledge management (KM). Although
                 anecdotal evidence and individual case studies suggest
                 that effective knowledge management initiatives
                 contribute to superior firm performance, other kinds of
                 empirical investigations are scarce, and more to the
                 point, most of them are based on perceptions of survey
                 participants embedded in the firms being studied.
                 Moreover, studies analyzing the question of whether
                 superior KM performance can predict superior
                 market-based valuation appear to be virtually
                 nonexistent. Findings of such studies would be of value
                 to those who champion and direct a firm's KM efforts,
                 and to the firm's strategists, planners, and
                 operational managers. Here, we empirically examine the
                 relationship between KM performance and firm valuation;
                 the former is assessed by international panels of
                 independent KM experts and the latter is evaluated in
                 terms of market-based measures. Based on data spanning
                 eight years, the results show that superior KM
                 performance has a statistically significant positive
                 association with firm valuation in terms of Tobin's q,
                 price-to-book ratio, and price-to-sales ratio. This
                 study contributes to the management literature by using
                 independent expert judges and archival data to
                 substantiate the notion that KM competencies are an
                 important ingredient in a firm's performance as
                 indicated by market-based valuation.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "6",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Orman:2013:BIT,
  author =       "Levent V. Orman",
  title =        "{Bayesian} Inference in Trust Networks",
  journal =      j-TMIS,
  volume =       "4",
  number =       "2",
  pages =        "7:1--7:??",
  month =        aug,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2489790",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 13 06:54:56 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Trust has emerged as a major impediment to the success
                 of electronic markets and communities where interaction
                 with the strangers is the norm. Social Networks and
                 Online Communities enable interaction with complete
                 strangers, and open up new commercial, political, and
                 social possibilities. But those promises are rarely
                 achieved because it is difficult to trust the online
                 contacts. A common approach to remedy this problem is
                 to compute trust values for the new contacts from the
                 existing trust values in the network. There are two
                 main methods: aggregation and transitivity. Yet,
                 neither method provides satisfactory results because
                 trust networks are sparse and transitivity may not
                 hold. This article develops a Bayesian formulation of
                 the problem, where trust is defined as a conditional
                 probability, and a Bayesian Network analysis is
                 employed to compute the unknown trust values in terms
                 of the known trust values. The algorithms used to
                 propagate conditional probabilities through the network
                 are theoretically sound and based on a long-standing
                 literature on probability propagation in Bayesian
                 networks. Moreover, the context information that is
                 typically ignored in trust literature is included here
                 as a major factor in computing new trust values. These
                 changes have led to significant improvements over
                 existing approaches in the accuracy of computed trust,
                 and with some modifications to the algorithm, in its
                 reach. Real data acquired from Advogato network is used
                 to do extensive testing, and the results confirm the
                 practical value of a theoretically sound Bayesian
                 approach.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "7",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Zhang:2013:RWM,
  author =       "Zhu Zhang and Daniel D. Zeng and Ahmed Abbasi and Jing
                 Peng and Xiaolong Zheng",
  title =        "A Random Walk Model for Item Recommendation in Social
                 Tagging Systems",
  journal =      j-TMIS,
  volume =       "4",
  number =       "2",
  pages =        "8:1--8:??",
  month =        aug,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2490860",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 13 06:54:56 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Social tagging, as a novel approach to information
                 organization and discovery, has been widely adopted in
                 many Web 2.0 applications. Tags contributed by users to
                 annotate a variety of Web resources or items provide a
                 new type of information that can be exploited by
                 recommender systems. Nevertheless, the sparsity of the
                 ternary interaction data among users, items, and tags
                 limits the performance of tag-based recommendation
                 algorithms. In this article, we propose to deal with
                 the sparsity problem in social tagging by applying
                 random walks on ternary interaction graphs to explore
                 transitive associations between users and items. The
                 transitive associations in this article refer to the
                 path of the link between any two nodes whose length is
                 greater than one. Taking advantage of these transitive
                 associations can allow more accurate measurement of the
                 relevance between two entities (e.g., user-item,
                 user-user, and item-item). A PageRank-like algorithm
                 has been developed to explore these transitive
                 associations by spreading users' preferences on an item
                 similarity graph and spreading items' influences on a
                 user similarity graph. Empirical evaluation on three
                 real-world datasets demonstrates that our approach can
                 effectively alleviate the sparsity problem and improve
                 the quality of item recommendation.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "8",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Derrick:2013:DDC,
  author =       "Douglas C. Derrick and Thomas O. Meservy and Jeffrey
                 L. Jenkins and Judee K. Burgoon and Jay F. {Nunamaker,
                 Jr.}",
  title =        "Detecting Deceptive Chat-Based Communication Using
                 Typing Behavior and Message Cues",
  journal =      j-TMIS,
  volume =       "4",
  number =       "2",
  pages =        "9:1--9:??",
  month =        aug,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2499962.2499967",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 13 06:54:56 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Computer-mediated deception is prevalent and may have
                 serious consequences for individuals, organizations,
                 and society. This article investigates several metrics
                 as predictors of deception in synchronous chat-based
                 environments, where participants must often
                 spontaneously formulate deceptive responses. Based on
                 cognitive load theory, we hypothesize that deception
                 influences response time, word count, lexical
                 diversity, and the number of times a chat message is
                 edited. Using a custom chatbot to conduct interviews in
                 an experiment, we collected 1,572 deceitful and 1,590
                 truthful chat-based responses. The results of the
                 experiment confirm that deception is positively
                 correlated with response time and the number of edits
                 and negatively correlated to word count. Contrary to
                 our prediction, we found that deception is not
                 significantly correlated with lexical diversity.
                 Furthermore, the age of the participant moderates the
                 influence of deception on response time. Our results
                 have implications for understanding deceit in
                 chat-based communication and building
                 deception-detection decision aids in chat-based
                 systems.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "9",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Sarker:2013:MOB,
  author =       "Suprateek Sarker and Suranjan Chakraborty and Patriya
                 Silpakit Tansuhaj and Mark Mulder and Kivilcim
                 Dogerlioglu-Demir",
  title =        "The {``Mail-Order-Bride'' (MOB)} Phenomenon in the
                 Cyberworld: an Interpretive Investigation",
  journal =      j-TMIS,
  volume =       "4",
  number =       "3",
  pages =        "10:1--10:??",
  month =        oct,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2524263",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 13 06:54:58 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Information technology (IT) is often an enabler in
                 bringing people together. In the context of this study,
                 IT helps connect matchmaking service providers with
                 those looking for love, particularly when a male seeks
                 to meet and possibly marry a female from another
                 country: a process which results in over 16,500 such
                 `mail-order-bride' (MOB) marriages a year in the United
                 States alone. Past research in business disciplines has
                 been largely silent about the way in which this process
                 unfolds, the perspectives of the participants at
                 different points of time, and the role of IT underlying
                 the MOB matchmaking service. Adopting an interpretivist
                 stance, and utilizing some of the methodological
                 guidelines associated with the Grounded Theory
                 Methodology (GTM), we develop a process model which
                 highlights: (a) the key states of the process through
                 which the relationship between the MOB seeker (the man)
                 and the MOB (the woman) unfolds, (b) the transitions
                 between states, and (c) the triggering conditions for
                 the transitions from one state to another. This study
                 also highlights key motivations of the individuals
                 participating in the MOB process, the effect of power
                 and the role it plays in the dynamics of the
                 relationships, the status of women and how their status
                 evolves during the MOB process, and the unique
                 affordance provided by IT as the relationships
                 evolve.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "10",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Kasiri:2013:ROS,
  author =       "Narges Kasiri and Ramesh Sharda",
  title =        "Real Options and System Dynamics for Information
                 Technology Investment Decisions: Application to {RFID}
                 Adoption in Retail",
  journal =      j-TMIS,
  volume =       "4",
  number =       "3",
  pages =        "11:1--11:??",
  month =        oct,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2517309",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 13 06:54:58 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "We propose a unique combination of system dynamics and
                 real options into a robust and innovative model for
                 analyzing return on investments in IT. Real options
                 modeling allows a cost benefit analysis to take into
                 account managerial flexibilities when there is
                 uncertainty in the investment, while system dynamics
                 can build a predictive model, in which one can simulate
                 different real-life and hypothetical scenarios in order
                 to provide measurements that can be used in the real
                 options model. Our return on the investment model
                 combines these long-established quantitative techniques
                 in a novel manner. This study applies this robust
                 hybrid model to a challenging IT investment problem:
                 adoption of RFID in retail. Item-level RFID is the next
                 generation of identification technology in the retail
                 sector. Our method can help managers to overcome the
                 complexity and uncertainties in the investment timing
                 of this technology. We analyze the RFID considerations
                 in retail decision-making using real data compiled from
                 a Delphi study. Our model demonstrates how the cost and
                 benefits of such an investment change over time. The
                 results highlight the variable cost of RFID tags as the
                 key factor in the decision process concerning whether
                 to immediately adopt or postpone the use of RFID in
                 retail. Our exploratory work suggests that it is
                 possible to combine merchandising and pricing issues in
                 addition to the traditional supply chain management
                 issues in studying any multifaceted problem in
                 retail.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "11",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Mathew:2013:DPP,
  author =       "George Mathew and Zoran Obradovic",
  title =        "Distributed Privacy-Preserving Decision Support System
                 for Highly Imbalanced Clinical Data",
  journal =      j-TMIS,
  volume =       "4",
  number =       "3",
  pages =        "12:1--12:??",
  month =        oct,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2517310",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 13 06:54:58 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "When a medical practitioner encounters a patient with
                 rare symptoms that translates to rare occurrences in
                 the local database, it is quite valuable to draw
                 conclusions collectively from such occurrences in other
                 hospitals. However, for such rare conditions, there
                 will be a huge imbalance in classes among the relevant
                 base population. Due to regulations and privacy
                 concerns, collecting data from other hospitals will be
                 problematic. Consequently, distributed decision support
                 systems that can use just the statistics of data from
                 multiple hospitals are valuable. We present a system
                 that can collectively build a distributed
                 classification model dynamically without the need of
                 patient data from each site in the case of imbalanced
                 data. The system uses a voting ensemble of experts for
                 the decision model. The imbalance condition and number
                 of experts can be determined by the system. Since only
                 statistics of the data and no raw data are required by
                 the system, patient privacy issues are addressed. We
                 demonstrate the outlined principles using the
                 Nationwide Inpatient Sample (NIS) database. Results of
                 experiments conducted on 7,810,762 patients from 1050
                 hospitals show improvement of 13.68\% to 24.46\% in
                 balanced prediction accuracy using our model over the
                 baseline model, illustrating the effectiveness of the
                 proposed methodology.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "12",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Sakata:2013:IEE,
  author =       "Masato Sakata and Zeynep Y{\"u}cel and Kazuhiko
                 Shinozawa and Norihiro Hagita and Michita Imai and
                 Michiko Furutani and Rumiko Matsuoka",
  title =        "An Inference Engine for Estimating Outside States of
                 Clinical Test Items",
  journal =      j-TMIS,
  volume =       "4",
  number =       "3",
  pages =        "13:1--13:??",
  month =        oct,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2517084",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 13 06:54:58 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Common periodical health check-ups include several
                 clinical test items with affordable cost. However,
                 these standard tests do not directly indicate signs of
                 most lifestyle diseases. In order to detect such
                 diseases, a number of additional specific clinical
                 tests are required, which increase the cost of the
                 health check-up. This study aims to enrich our
                 understanding of the common health check-ups and
                 proposes a way to estimate the signs of several
                 lifestyle diseases based on the standard tests in
                 common examinations without performing any additional
                 specific tests. In this manner, we enable a diagnostic
                 process, where the physician may prefer to perform or
                 avoid a costly test according to the estimation carried
                 out through a set of common affordable tests. To that
                 end, the relation between standard and specific test
                 results is modeled with a multivariate kernel density
                 estimate. The condition of the patient regarding a
                 specific test is assessed following a Bayesian
                 framework. Our results indicate that the proposed
                 method achieves an overall estimation accuracy of 84\%.
                 In addition, an outstanding estimation accuracy is
                 achieved for a subset of high-cost tests. Moreover,
                 comparison with standard artificial intelligence
                 methods suggests that our algorithm outperforms the
                 conventional methods. Our contributions are as follows:
                 (i) promotion of affordable health check-ups, (ii) high
                 estimation accuracy in certain tests, (iii)
                 generalization capability due to ease of implementation
                 on different platforms and institutions, (iv)
                 flexibility to apply to various tests and potential to
                 improve early detection rates.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "13",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Edgcomb:2013:AEA,
  author =       "Alex Edgcomb and Frank Vahid",
  title =        "Accurate and Efficient Algorithms that Adapt to
                 Privacy-Enhanced Video for Improved Assistive
                 Monitoring",
  journal =      j-TMIS,
  volume =       "4",
  number =       "3",
  pages =        "14:1--14:??",
  month =        oct,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2523025.2523026",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 13 06:54:58 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Automated monitoring algorithms operating on live
                 video streamed from a home can effectively aid in
                 several assistive monitoring goals, such as detecting
                 falls or estimating daily energy expenditure. Use of
                 video raises obvious privacy concerns. Several privacy
                 enhancements have been proposed such as modifying a
                 person in video by introducing blur, silhouette, or
                 bounding-box. Person extraction is fundamental in
                 video-based assistive monitoring and degraded in the
                 presence of privacy enhancements; however, privacy
                 enhancements have characteristics that can
                 opportunistically be adapted to. We propose two
                 adaptive algorithms for improving assistive monitoring
                 goal performance with privacy-enhanced video:
                 specific-color hunter and edge-void filler. A
                 nonadaptive algorithm, foregrounding, is used as the
                 default algorithm for the adaptive algorithms. We
                 compare nonadaptive and adaptive algorithms with 5
                 common privacy enhancements on the effectiveness of 8
                 automated monitoring goals. The nonadaptive algorithm
                 performance on privacy-enhanced video is degraded from
                 raw video. However, adaptive algorithms can compensate
                 for the degradation. Energy estimation accuracy in our
                 tests degraded from 90.9\% to 83.9\%, but the adaptive
                 algorithms significantly compensated by bringing the
                 accuracy up to 87.1\%. Similarly, fall detection
                 accuracy degraded from 1.0 sensitivity to 0.86 and from
                 1.0 specificity to 0.79, but the adaptive algorithms
                 compensated accuracy back to 0.92 sensitivity and 0.90
                 specificity. Additionally, the adaptive algorithms were
                 computationally more efficient than the nonadaptive
                 algorithm, averaging 1.7\% more frames processed per
                 second.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "14",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Yang:2013:SHW,
  author =       "Christopher C. Yang and Gondy Leroy and Sophia
                 Ananiadou",
  title =        "Smart Health and Wellbeing",
  journal =      j-TMIS,
  volume =       "4",
  number =       "4",
  pages =        "15:1--15:??",
  month =        dec,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2555810.2555811",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 13 06:54:59 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Healthcare informatics has drawn substantial attention
                 in recent years. Current work on healthcare informatics
                 is highly interdisciplinary involving methodologies
                 from computing, engineering, information science,
                 behavior science, management science, social science,
                 as well as many different areas in medicine and public
                 health. Three major tracks, (i) systems, (ii)
                 analytics, and (iii) human factors, can be identified.
                 The systems track focuses on healthcare system
                 architecture, framework, design, engineering, and
                 application; the analytics track emphasizes
                 data/information processing, retrieval, mining,
                 analytics, as well as knowledge discovery; the human
                 factors track targets the understanding of users or
                 context, interface design, and user studies of
                 healthcare applications. In this article, we discuss
                 some of the latest development and introduce several
                 articles selected for this special issue. We envision
                 that the development of computing-oriented healthcare
                 informatics research will continue to grow rapidly. The
                 integration of different disciplines to advance the
                 healthcare and wellbeing of our society will also be
                 accelerated.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "15",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Wang:2013:MTE,
  author =       "Zidong Wang and Julie Eatock and Sally McClean and
                 Dongmei Liu and Xiaohui Liu and Terry Young",
  title =        "Modeling Throughput of Emergency Departments via Time
                 Series: an Expectation Maximization Algorithm",
  journal =      j-TMIS,
  volume =       "4",
  number =       "4",
  pages =        "16:1--16:??",
  month =        dec,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2544105",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 13 06:54:59 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "In this article, the expectation maximization (EM)
                 algorithm is applied for modeling the throughput of
                 emergency departments via available time-series data.
                 The dynamics of emergency department throughput is
                 developed and evaluated, for the first time, as a
                 stochastic dynamic model that consists of the noisy
                 measurement and first-order autoregressive (AR)
                 stochastic dynamic process. By using the EM algorithm,
                 the model parameters, the actual throughput, as well as
                 the noise intensity, can be identified simultaneously.
                 Four real-world time series collected from an emergency
                 department in West London are employed to demonstrate
                 the effectiveness of the introduced algorithm. Several
                 quantitative indices are proposed to evaluate the
                 inferred models. The simulation shows that the
                 identified model fits the data very well.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "16",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Zhang:2013:MDP,
  author =       "He Zhang and Sanjay Mehotra and David Liebovitz and
                 Carl A. Gunter and Bradley Malin",
  title =        "Mining Deviations from Patient Care Pathways via
                 Electronic Medical Record System Audits",
  journal =      j-TMIS,
  volume =       "4",
  number =       "4",
  pages =        "17:1--17:??",
  month =        dec,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2544102",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 13 06:54:59 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "In electronic medical record (EMR) systems,
                 administrators often provide EMR users with broad
                 access privileges, which may leave the system
                 vulnerable to misuse and abuse. Given that patient care
                 is based on a coordinated workflow, we hypothesize that
                 care pathways can be represented as the progression of
                 a patient through a system and introduce a strategy to
                 model the patient's flow as a sequence of accesses
                 defined over a graph. Elements in the sequence
                 correspond to features associated with the access
                 transaction (e.g., reason for access). Based on this
                 motivation, we model patterns of patient record usage,
                 which may indicate deviations from care workflows. We
                 evaluate our approach using several months of data from
                 a large academic medical center. Empirical results show
                 that this framework finds a small portion of accesses
                 constitute outliers from such flows. We also observe
                 that the violation patterns deviate for different types
                 of medical services. Analysis of our results suggests
                 greater deviation from normal access patterns by
                 nonclinical users. We simulate anomalies in the context
                 of real accesses to illustrate the efficiency of the
                 proposed method for different medical services. As an
                 illustration of the capabilities of our method, it was
                 observed that the area under the receiver operating
                 characteristic (ROC) curve for the Pediatrics service
                 was found to be 0.9166. The results suggest that our
                 approach is competitive with, and often better than,
                 the existing state-of-the-art in its outlier detection
                 performance. At the same time, our method is more
                 efficient, by orders of magnitude, than previous
                 approaches, allowing for detection of thousands of
                 accesses in seconds.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "17",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Khosla:2013:ECM,
  author =       "Rajiv Khosla and Mei-Tai Chu",
  title =        "Embodying Care in {Matilda}: an Affective
                 Communication Robot for Emotional Wellbeing of Older
                 People in {Australian} Residential Care Facilities",
  journal =      j-TMIS,
  volume =       "4",
  number =       "4",
  pages =        "18:1--18:??",
  month =        dec,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2544104",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 13 06:54:59 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Ageing population is at the center of the looming
                 healthcare crisis in most parts of the developed and
                 developing world. Australia, like most of the western
                 world, is bracing up for the looming ageing population
                 crisis, spiraling healthcare costs, and expected
                 serious shortage of healthcare workers. Assistive
                 service and companion (social) robots are being seen as
                 one of the ways for supporting aged care facilities to
                 meet this challenge and improve the quality of care of
                 older people including mental and physical health
                 outcomes, as well as to support healthcare workers in
                 personalizing care. In this article, the authors report
                 on the design and implementation of first-ever field
                 trials of Matilda, a human-like assistive communication
                 (service and companion) robot for improving the
                 emotional well-being of older people in three
                 residential care facilities in Australia involving 70
                 participants. The research makes several unique
                 contributions including Matilda's ability to break
                 technology barriers, positively engage older people in
                 group and one-to-one activities, making these older
                 people productive and useful, helping them become
                 resilient and cope better through personalization of
                 care, and finally providing them sensory enrichment
                 through Matilda's multimodal communication
                 capabilities.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "18",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Lisetti:2013:CHY,
  author =       "Christine Lisetti and Reza Amini and Ugan Yasavur and
                 Naphtali Rishe",
  title =        "{I} Can Help You Change! {An} Empathic Virtual Agent
                 Delivers Behavior Change Health Interventions",
  journal =      j-TMIS,
  volume =       "4",
  number =       "4",
  pages =        "19:1--19:??",
  month =        dec,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2544103",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 13 06:54:59 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "We discuss our approach to developing a novel modality
                 for the computer-delivery of Brief Motivational
                 Interventions (BMIs) for behavior change in the form of
                 a personalized On-Demand VIrtual Counselor (ODVIC),
                 accessed over the internet. ODVIC is a multimodal
                 Embodied Conversational Agent (ECA) that empathically
                 delivers an evidence-based behavior change intervention
                 by adapting, in real-time, its verbal and nonverbal
                 communication messages to those of the user's during
                 their interaction. We currently focus our work on
                 excessive alcohol consumption as a target behavior, and
                 our approach is adaptable to other target behaviors
                 (e.g., overeating, lack of exercise, narcotic drug use,
                 non-adherence to treatment). We based our current
                 approach on a successful existing patient-centered
                 brief motivational intervention for behavior
                 change---the Drinker's Check-Up (DCU)---whose
                 computer-delivery with a text-only interface has been
                 found effective in reducing alcohol consumption in
                 problem drinkers. We discuss the results of users'
                 evaluation of the computer-based DCU intervention
                 delivered with a text-only interface compared to the
                 same intervention delivered with two different ECAs (a
                 neutral one and one with some empathic abilities).
                 Users rate the three systems in terms of acceptance,
                 perceived enjoyment, and intention to use the system,
                 among other dimensions. We conclude with a discussion
                 of how our positive results encourage our long-term
                 goals of on-demand conversations, anytime, anywhere,
                 with virtual agents as personal health and well-being
                 helpers.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "19",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Mirani:2013:BBI,
  author =       "Rajesh Mirani and Anju Harpalani",
  title =        "Business Benefits or Incentive Maximization? Impacts
                 of the {Medicare} {EHR} Incentive Program at Acute Care
                 Hospitals",
  journal =      j-TMIS,
  volume =       "4",
  number =       "4",
  pages =        "20:1--20:??",
  month =        dec,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2543900",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 13 06:54:59 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "This study investigates the influence of the Medicare
                 EHR Incentive Program on EHR adoption at acute care
                 hospitals and the impact of EHR adoption on operational
                 and financial efficiency/effectiveness. It finds that
                 even before joining the incentive program, adopter
                 hospitals had more efficient and effective Medicare
                 operations than those of non-adopters. Adopters were
                 also financially more efficient. After joining the
                 program, adopter hospitals treated significantly more
                 Medicare patients by shortening their stay durations,
                 relative to their own non-Medicare patients and also to
                 patients at non-adopter hospitals, even as their
                 overall capacity utilization remained relatively
                 unchanged. The study concludes that many of these
                 hospitals had implemented EHR even before the
                 initiation of the incentive program. It further infers
                 that they joined this program with opportunistic
                 intentions of tapping into incentive payouts which they
                 maximized by taking on more Medicare patients. These
                 findings give credence to critics of the program who
                 have questioned its utility and alleged that it serves
                 only to reward existing users of EHR technologies.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "20",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Ho:2014:SSP,
  author =       "Joyce C. Ho and Cheng H. Lee and Joydeep Ghosh",
  title =        "Septic Shock Prediction for Patients with Missing
                 Data",
  journal =      j-TMIS,
  volume =       "5",
  number =       "1",
  pages =        "1:1--1:??",
  month =        apr,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2591676",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Apr 15 17:44:19 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Sepsis and septic shock are common and potentially
                 fatal conditions that often occur in intensive care
                 unit (ICU) patients. Early prediction of patients at
                 risk for septic shock is therefore crucial to
                 minimizing the effects of these complications.
                 Potential indications for septic shock risk span a wide
                 range of measurements, including physiological data
                 gathered at different temporal resolutions and gene
                 expression levels, leading to a nontrivial prediction
                 problem. Previous works on septic shock prediction have
                 used small, carefully curated datasets or clinical
                 measurements that may not be available for many ICU
                 patients. The recent availability of a large, rich ICU
                 dataset called MIMIC-II has provided the opportunity
                 for more extensive modeling of this problem. However,
                 such a large clinical dataset inevitably contains a
                 substantial amount of missing data. We investigate how
                 different imputation selection criteria and methods can
                 overcome the missing data problem. Our results show
                 that imputation methods in conjunction with predictive
                 modeling can lead to accurate septic shock prediction,
                 even if the features are restricted primarily to
                 noninvasive measurements. Our models provide a
                 generalized approach for predicting septic shock in any
                 ICU patient.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "1",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Yang:2014:PDS,
  author =       "Christopher C. Yang and Haodong Yang and Ling Jiang",
  title =        "Postmarketing Drug Safety Surveillance Using Publicly
                 Available Health-Consumer-Contributed Content in Social
                 Media",
  journal =      j-TMIS,
  volume =       "5",
  number =       "1",
  pages =        "2:1--2:??",
  month =        apr,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2576233",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Apr 15 17:44:19 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Postmarketing drug safety surveillance is important
                 because many potential adverse drug reactions cannot be
                 identified in the premarketing review process. It is
                 reported that about 5\% of hospital admissions are
                 attributed to adverse drug reactions and many deaths
                 are eventually caused, which is a serious concern in
                 public health. Currently, drug safety detection relies
                 heavily on voluntarily reporting system, electronic
                 health records, or relevant databases. There is often a
                 time delay before the reports are filed and only a
                 small portion of adverse drug reactions experienced by
                 health consumers are reported. Given the popularity of
                 social media, many health social media sites are now
                 available for health consumers to discuss any
                 health-related issues, including adverse drug reactions
                 they encounter. There is a large volume of
                 health-consumer-contributed content available, but
                 little effort has been made to harness this information
                 for postmarketing drug safety surveillance to
                 supplement the traditional approach. In this work, we
                 propose the association rule mining approach to
                 identify the association between a drug and an adverse
                 drug reaction. We use the alerts posted by Food and
                 Drug Administration as the gold standard to evaluate
                 the effectiveness of our approach. The result shows
                 that the performance of harnessing health-related
                 social media content to detect adverse drug reaction is
                 good and promising.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "2",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Bouktif:2014:PSO,
  author =       "Salah Bouktif and Houari Sahraoui and Faheem Ahmed",
  title =        "Predicting Stability of Open-Source Software Systems
                 Using Combination of {Bayesian} Classifiers",
  journal =      j-TMIS,
  volume =       "5",
  number =       "1",
  pages =        "3:1--3:??",
  month =        apr,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2555596",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Apr 15 17:44:19 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/gnu.bib;
                 https://www.math.utah.edu/pub/tex/bib/java2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "The use of free and Open-Source Software (OSS) systems
                 is gaining momentum. Organizations are also now
                 adopting OSS, despite some reservations, particularly
                 about the quality issues. Stability of software is one
                 of the main features in software quality management
                 that needs to be understood and accurately predicted.
                 It deals with the impact resulting from software
                 changes and argues that stable components lead to a
                 cost-effective software evolution. Changes are most
                 common phenomena present in OSS in comparison to
                 proprietary software. This makes OSS system evolution a
                 rich context to study and predict stability. Our
                 objective in this work is to build stability prediction
                 models that are not only accurate but also
                 interpretable, that is, able to explain the link
                 between the architectural aspects of a software
                 component and its stability behavior in the context of
                 OSS. Therefore, we propose a new approach based on
                 classifiers combination capable of preserving
                 prediction interpretability. Our approach is
                 classifier-structure dependent. Therefore, we propose a
                 particular solution for combining Bayesian classifiers
                 in order to derive a more accurate composite classifier
                 that preserves interpretability. This solution is
                 implemented using a genetic algorithm and applied in
                 the context of an OSS large-scale system, namely the
                 standard Java API. The empirical results show that our
                 approach outperforms state-of-the-art approaches from
                 both machine learning and software engineering.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "3",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Huang:2014:BOT,
  author =       "Lihua Huang and Sulin Ba and Xianghua Lu",
  title =        "Building Online Trust in a Culture of {Confucianism}:
                 The Impact of Process Flexibility and Perceived
                 Control",
  journal =      j-TMIS,
  volume =       "5",
  number =       "1",
  pages =        "4:1--4:??",
  month =        apr,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2576756",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Apr 15 17:44:19 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "The success of e-commerce companies in a Confucian
                 cultural context takes more than advanced IT and
                 process design that have proven successful in Western
                 countries. The example of eBay's failure in China
                 indicates that earning the trust of Chinese consumers
                 is essential to success, yet the process of building
                 that trust requires something different from that in
                 the Western culture. This article attempts to build a
                 theoretical model to explore the relationship between
                 the Confucian culture and online trust. We introduce
                 two new constructs, namely process flexibility and
                 perceived control, as particularly important factors in
                 online trust formation in the Chinese cultural context.
                 A survey was conducted to test the proposed theoretical
                 model. This study offers a new explanation for online
                 trust formation in the Confucian context. The findings
                 of this article can provide guidance for companies
                 hoping to successfully navigate the Chinese online
                 market in the future.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "4",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Yeo:2014:RMD,
  author =       "M. Lisa Yeo and Erik Rolland and Jackie Rees Ulmer and
                 Raymond A. Patterson",
  title =        "Risk Mitigation Decisions for {IT} Security",
  journal =      j-TMIS,
  volume =       "5",
  number =       "1",
  pages =        "5:1--5:??",
  month =        apr,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2576757",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Apr 15 17:44:19 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Enterprises must manage their information risk as part
                 of their larger operational risk management program.
                 Managers must choose how to control for such
                 information risk. This article defines the flow risk
                 reduction problem and presents a formal model using a
                 workflow framework. Three different control placement
                 methods are introduced to solve the problem, and a
                 comparative analysis is presented using a robust test
                 set of 162 simulations. One year of simulated attacks
                 is used to validate the quality of the solutions. We
                 find that the math programming control placement method
                 yields substantial improvements in terms of risk
                 reduction and risk reduction on investment when
                 compared to heuristics that would typically be used by
                 managers to solve the problem. The contribution of this
                 research is to provide managers with methods to
                 substantially reduce information and security risks,
                 while obtaining significantly better returns on their
                 security investments. By using a workflow approach to
                 control placement, which guides the manager to examine
                 the entire infrastructure in a holistic manner, this
                 research is unique in that it enables information risk
                 to be examined strategically.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "5",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Goodman:2014:BNC,
  author =       "S. E. Goodman",
  title =        "Building the Nation's Cyber Security Workforce:
                 Contributions from the {CAE} Colleges and
                 Universities",
  journal =      j-TMIS,
  volume =       "5",
  number =       "2",
  pages =        "6:1--6:??",
  month =        jul,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2629636",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Aug 8 11:44:01 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "This article presents a view of the necessary size and
                 composition of the US national cyber security
                 workforce, and considers some of the contributions that
                 the government-designated Centers of Academic
                 Excellence (CAE) might make to it. Over the last dozen
                 years about 200 million taxpayer dollars have gone into
                 funding many of these CAEs, with millions explicitly
                 targeted to help them build capacity. The most visible
                 intended output has been in the form of around 125
                 Scholarship for Service (SFS) students per year going
                 mostly into the workforce of the federal government.
                 Surely the output capacity of these 181 colleges and
                 universities is greater than that, and should be
                 helping to protect the rest of US citizens and
                 taxpayers. We take a need-based look at what the
                 nation's workforce should look like, and then consider
                 some possibilities of what the CAE schools could be
                 doing to help to close the gaps between that perceived
                 need and the supply and demand.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "6",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Deodhar:2014:IWB,
  author =       "Suruchi Deodhar and Keith R. Bisset and Jiangzhuo Chen
                 and Yifei Ma and Madhav V. Marathe",
  title =        "An Interactive, {Web}-Based High Performance Modeling
                 Environment for Computational Epidemiology",
  journal =      j-TMIS,
  volume =       "5",
  number =       "2",
  pages =        "7:1--7:??",
  month =        jul,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2629692",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Aug 8 11:44:01 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "We present an integrated interactive modeling
                 environment to support public health epidemiology. The
                 environment combines a high resolution individual-based
                 model with a user-friendly Web-based interface that
                 allows analysts to access the models and the analytics
                 backend remotely from a desktop or a mobile device. The
                 environment is based on a loosely coupled
                 service-oriented-architecture that allows analysts to
                 explore various counterfactual scenarios. As the
                 modeling tools for public health epidemiology are
                 getting more sophisticated, it is becoming increasingly
                 difficult for noncomputational scientists to
                 effectively use the systems that incorporate such
                 models. Thus an important design consideration for an
                 integrated modeling environment is to improve ease of
                 use such that experimental simulations can be driven by
                 the users. This is achieved by designing intuitive and
                 user-friendly interfaces that allow users to design and
                 analyze a computational experiment and steer the
                 experiment based on the state of the system. A key
                 feature of a system that supports this design goal is
                 the ability to start, stop, pause, and roll back the
                 disease propagation and intervention application
                 process interactively. An analyst can access the state
                 of the system at any point in time and formulate
                 dynamic interventions based on additional information
                 obtained through state assessment. In addition, the
                 environment provides automated services for experiment
                 set-up and management, thus reducing the overall time
                 for conducting end-to-end experimental studies. We
                 illustrate the applicability of the system by
                 describing computational experiments based on realistic
                 pandemic planning scenarios. The experiments are
                 designed to demonstrate the system's capability and
                 enhanced user productivity.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "7",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Kostkova:2014:SUT,
  author =       "Patty Kostkova and Martin Szomszor and Connie {St.
                 Luis}",
  title =        "\#swineflu: The Use of {Twitter} as an Early Warning
                 and Risk Communication Tool in the 2009 Swine Flu
                 Pandemic",
  journal =      j-TMIS,
  volume =       "5",
  number =       "2",
  pages =        "8:1--8:??",
  month =        jul,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2597892",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Aug 8 11:44:01 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "The need to improve population monitoring and enhance
                 surveillance of infectious diseases has never been more
                 pressing. Factors such as air travel act as a catalyst
                 in the spread of new and existing viruses. The
                 unprecedented user-generated activity on social
                 networks over the last few years has created real-time
                 streams of personal data that provide an invaluable
                 tool for monitoring and sampling large populations.
                 Epidemic intelligence relies on constant monitoring of
                 online media sources for early warning, detection, and
                 rapid response; however, the real-time information
                 available in social networks provides a new paradigm
                 for the early warning function. The communication of
                 risk in any public health emergency is a complex task
                 for governments and healthcare agencies. This task is
                 made more challenging in the current situation when the
                 public has access to a wide range of online resources,
                 ranging from traditional news channels to information
                 posted on blogs and social networks. Twitter's strength
                 is its two-way communication nature --- both as an
                 information source but also as a central hub for
                 publishing, disseminating and discovering online media.
                 This study addresses these two challenges by
                 investigating the role of Twitter during the 2009 swine
                 flu pandemic by analysing data collected from the SN,
                 and by Twitter using the opposite way for dissemination
                 information through the network. First, we demonstrate
                 the role of the social network for early warning by
                 detecting an upcoming spike in an epidemic before the
                 official surveillance systems by up to two weeks in the
                 U.K. and up to two to three weeks in the U.S. Second,
                 we illustrate how online resources are propagated
                 through Twitter at the time of the WHO's declaration of
                 the swine flu ``pandemic''. Our findings indicate that
                 Twitter does favour reputable t bogus information can
                 still leak into the network.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "8",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Tsai:2014:SPS,
  author =       "Chih-Fong Tsai and Zen-Yu Quan",
  title =        "Stock Prediction by Searching for Similarities in
                 Candlestick Charts",
  journal =      j-TMIS,
  volume =       "5",
  number =       "2",
  pages =        "9:1--9:??",
  month =        jul,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2591672",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Aug 8 11:44:01 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "The aim of stock prediction is to effectively predict
                 future stock market trends (or stock prices), which can
                 lead to increased profit. One major stock analysis
                 method is the use of candlestick charts. However,
                 candlestick chart analysis has usually been based on
                 the utilization of numerical formulas. There has been
                 no work taking advantage of an image processing
                 technique to directly analyze the visual content of the
                 candlestick charts for stock prediction. Therefore, in
                 this study we apply the concept of image retrieval to
                 extract seven different wavelet-based texture features
                 from candlestick charts. Then, similar historical
                 candlestick charts are retrieved based on different
                 texture features related to the query chart, and the
                 ``future'' stock movements of the retrieved charts are
                 used for stock prediction. To assess the applicability
                 of this approach to stock prediction, two datasets are
                 used, containing 5-year and 10-year training and
                 testing sets, collected from the Dow Jones Industrial
                 Average Index (INDU) for the period between 1990 and
                 2009. Moreover, two datasets (2010 and 2011) are used
                 to further validate the proposed approach. The
                 experimental results show that visual content
                 extraction and similarity matching of candlestick
                 charts is a new and useful analytical method for stock
                 prediction. More specifically, we found that the
                 extracted feature vectors of 30, 90, and 120, the
                 number of textual features extracted from the
                 candlestick charts in the BMP format, are more suitable
                 for predicting stock movements, while the 90 feature
                 vector offers the best performance for predicting
                 short- and medium-term stock movements. That is, using
                 the 90 feature vector provides the lowest MAPE
                 (3.031\%) and Theil's U (1.988\%) rates in the
                 twenty-year dataset, and the best MAPE (2.625\%,
                 2.945\%) and Theil's U (1.622\%, 1.972\%) rates in the
                 two validation datasets (2010 and 2011).",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "9",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Jarke:2015:ECS,
  author =       "Matthias Jarke and Kalle Lyytinen",
  title =        "Editorial: {``Complexity of Systems Evolution:
                 Requirements Engineering Perspective''}",
  journal =      j-TMIS,
  volume =       "5",
  number =       "3",
  pages =        "11:1--11:??",
  month =        jan,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2629597",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Feb 11 13:49:27 MST 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Walking on water, and programming according to
                 specifications is easy-as long as both of them are
                 frozen. --Robert Glass This introduction discusses the
                 changing nature of complexity associated with
                 requirements engineering (RE) tasks and how it has
                 shifted from managing internal complexity to adapting
                 and leveraging upon external and dynamic complexity. We
                 note several significant drivers in the requirements
                 knowledge that have resulted in this change and discuss
                 in light of complexity theory how the RE research
                 community can respond to this. We observe several
                 research challenges associated with ``new complexity''
                 and highlight how the articles included in the special
                 issue advance the field by defining complexity more
                 accurately, observing more vigilantly new sources of
                 complexity, and suggesting new ways to manage
                 complexity in terms of economic assessments, knowledge
                 flows, and modeling for adaptability.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "11",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Fridgen:2015:IBV,
  author =       "Gilbert Fridgen and Julia Klier and Martina Beer and
                 Thomas Wolf",
  title =        "Improving Business Value Assurance in Large-Scale {IT}
                 Projects --- a Quantitative Method Based on Founded
                 Requirements Assessment",
  journal =      j-TMIS,
  volume =       "5",
  number =       "3",
  pages =        "12:1--12:??",
  month =        jan,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2638544",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Feb 11 13:49:27 MST 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "The probability of IT project failures can be
                 mitigated more successfully when discovered early. To
                 support a more insightful management of IT projects,
                 which may also facilitate an early detection of IT
                 project failures, transparency regarding a project's
                 cash flows shall be increased. Therefore, an
                 appropriate analysis of a project's benefits, costs,
                 requirements, their respective risks and
                 interdependencies is inevitable. However, to date, in
                 requirements engineering only few methods exist that
                 appropriately consider these factors when estimating
                 the ex ante project business case. Furthermore,
                 empirical studies reveal that a lot of risk factors
                 emerge during the runtime of projects why the ex ante
                 valuation of IT projects even with respect to
                 requirements seems insufficient. Therefore, using the
                 Action Design Research approach, we design, apply, and
                 evaluate a practicable method for value-based
                 continuous IT project steering especially for
                 large-scale IT projects.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "12",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{King:2015:CCR,
  author =       "John Leslie King and Carl P. Simon",
  title =        "Complications with Complexity in Requirements",
  journal =      j-TMIS,
  volume =       "5",
  number =       "3",
  pages =        "13:1--13:??",
  month =        jan,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2629375",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Feb 11 13:49:27 MST 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Requirements engineering must recognize the difference
                 between complicated and complex problems. The former
                 can lead to successful solutions. The latter should be
                 avoided because they often lead to failure. As a
                 starting point for distinguishing between complicated
                 and complex, this article offers six characteristics of
                 complex problems, with examples from economics,
                 logistics, forecasting, among others. These
                 characteristics make it easier and more systematic to
                 recognize complexity during requirements elicitation
                 and formulation.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "13",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Chakraborty:2015:GSF,
  author =       "Suranjan Chakraborty and Christoph Rosenkranz and Josh
                 Dehlinger",
  title =        "Getting to the Shalls: Facilitating Sensemaking in
                 Requirements Engineering",
  journal =      j-TMIS,
  volume =       "5",
  number =       "3",
  pages =        "14:1--14:??",
  month =        jan,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2629351",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Feb 11 13:49:27 MST 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Sensemaking in Requirements Engineering (RE) relies on
                 knowledge transfer, communication, and negotiation of
                 project stakeholders. It is a critical and challenging
                 aspect of Information Systems (IS) development. One of
                 the most fundamental aspects of RE is the specification
                 of traceable, unambiguous, and operationalizable
                 functional and nonfunctional requirements. This remains
                 a nontrivial task in the face of the complexity
                 inherent in RE due to the lack of well-documented,
                 systematic procedures that facilitate a structured
                 analysis of the qualitative data from stakeholder
                 interviews, observations, and documents that are
                 typically the input to this activity. This research
                 develops a systematic and traceable procedure, for
                 non-functional requirements the Grounded and
                 Linguistic-Based Requirements Analysis Procedure
                 (GLAP), which can fill this gap by incorporating
                 perspectives from Grounded Theory Method, linguistic
                 analysis of language quality, Volere typology, and the
                 Nonfunctional Requirements Framework without
                 significantly deviating from existing practice. The
                 application of GLAP is described along with empirical
                 illustrations using RE data from a redesign initiative
                 of a library website of a public university in the
                 United States. An outlook is given on further work and
                 necessary evaluation steps.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "14",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Nekvi:2015:IRC,
  author =       "Md Rashed I. Nekvi and Nazim H. Madhavji",
  title =        "Impediments to Regulatory Compliance of Requirements
                 in Contractual Systems Engineering Projects: a Case
                 Study",
  journal =      j-TMIS,
  volume =       "5",
  number =       "3",
  pages =        "15:1--15:??",
  month =        jan,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2629432",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Feb 11 13:49:27 MST 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Large-scale contractual systems engineering projects
                 often need to comply with myriad government regulations
                 and standards as part of contractual obligations. A key
                 activity in the requirements engineering (RE) process
                 for such a project is to demonstrate that all relevant
                 requirements have been elicited from the regulatory
                 documents and have been traced to the contract as well
                 as to the target system components. That is, the
                 requirements have met regulatory compliance. However,
                 there are impediments to achieving this level of
                 compliance due to such complexity factors as voluminous
                 contract, large number of regulatory documents, and
                 multiple domains of the system. Little empirical
                 research has been conducted in the scientific community
                 on identifying these impediments. Knowing these
                 impediments is a driver for change in the solutions
                 domain (i.e., creating improved or new methods, tools,
                 processes, etc.) to deal with such impediments. Through
                 a case study of an industrial RE project, we have
                 identified a number of key impediments to achieving
                 regulatory compliance in a large-scale, complex,
                 systems engineering project. This project is an upgrade
                 of a rail infrastructure system. The key contribution
                 of the article is a number of hitherto uncovered
                 impediments described in qualitative and quantitative
                 terms. The article also describes an artefact model,
                 depicting key artefacts and relationships involved in
                 such a compliance project. This model was created from
                 data gathered and observations made in this compliance
                 project. In addition, the article describes emergent
                 metrics on regulatory compliance of requirements that
                 can possibly be used for estimating the effort needed
                 to achieve regulatory compliance of system
                 requirements.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "15",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Jain:2015:SBS,
  author =       "Radhika Jain and Lan Cao and Kannan Mohan and
                 Balasubramaniam Ramesh",
  title =        "Situated Boundary Spanning: an Empirical Investigation
                 of Requirements Engineering Practices in Product Family
                 Development",
  journal =      j-TMIS,
  volume =       "5",
  number =       "3",
  pages =        "16:1--16:??",
  month =        jan,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2629395",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Feb 11 13:49:27 MST 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Requirements Engineering (RE) faces considerable
                 challenges that are often related to boundaries between
                 various stakeholders involved in the software
                 development process. These challenges may be addressed
                 by boundary spanning practices. We examine how boundary
                 spanning can be adapted to address RE challenges in
                 Product Family Development (PFD), a context that
                 involves complex RE. We study two different development
                 approaches, namely, conventional and agile PFD, because
                 these present considerably different challenges. Our
                 findings from a multisite case study present boundary
                 spanning as a solution to improve the quality of RE
                 processes and highlight interesting differences in how
                 boundary spanner roles and boundary objects are adapted
                 in conventional and agile PFD.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "16",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Jureta:2015:RPA,
  author =       "Ivan J. Jureta and Alexander Borgida and Neil A. Ernst
                 and John Mylopoulos",
  title =        "The Requirements Problem for Adaptive Systems",
  journal =      j-TMIS,
  volume =       "5",
  number =       "3",
  pages =        "17:1--17:??",
  month =        jan,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2629376",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Feb 11 13:49:27 MST 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Requirements Engineering (RE) focuses on eliciting,
                 modeling, and analyzing the requirements and
                 environment of a system-to-be in order to design its
                 specification. The design of the specification, known
                 as the Requirements Problem (RP), is a complex
                 problem-solving task because it involves, for each new
                 system, the discovery and exploration of, and decision
                 making in a new problem space. A system is adaptive if
                 it can detect deviations between its runtime behavior
                 and its requirements, specifically situations where its
                 behavior violates one or more of its requirements.
                 Given such a deviation, an Adaptive System uses
                 feedback mechanisms to analyze these changes and
                 decide, with or without human intervention, how to
                 adjust its behavior as a result. We are interested in
                 defining the Requirements Problem for Adaptive Systems
                 (RPAS). In our case, we are looking for a configurable
                 specification such that whenever requirements fail to
                 be fulfilled, the system can go through a series of
                 adaptations that change its configuration and
                 eventually restore fulfilment of the requirements. From
                 a theoretical perspective, this article formally shows
                 the fundamental differences between standard RE
                 (notably Zave and Jackson [1997]) and RE for Adaptive
                 Systems (see the seminal work by Fickas and Feather
                 [1995], to Letier and van Lamsweerde [2004], and up to
                 Whittle et al. [2010]). The main contribution of this
                 article is to introduce the RPAS as a new RP class that
                 is specific to Adaptive Systems. We relate the RPAS to
                 RE research on the relaxation of requirements, the
                 evaluation of their partial satisfaction, and the
                 monitoring and control of requirements, all topics of
                 particular interest in research on adaptive systems [de
                 Lemos et al. 2013]. From an engineering perspective, we
                 define a proto-framework for solving RPAS, which
                 illustrates features needed in future frameworks for
                 adaptive software systems.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "17",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Wang:2015:AFU,
  author =       "G. Alan Wang and Harry Jiannan Wang and Jiexun Li and
                 Alan S. Abrahams and Weiguo Fan",
  title =        "An Analytical Framework for Understanding
                 Knowledge-Sharing Processes in Online {Q\&A}
                 Communities",
  journal =      j-TMIS,
  volume =       "5",
  number =       "4",
  pages =        "18:1--18:??",
  month =        jan,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2629445",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Feb 11 13:49:27 MST 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Online communities have become popular knowledge
                 sources for both individuals and organizations.
                 Computer-mediated communication research shows that
                 communication patterns play an important role in the
                 collaborative efforts of online knowledge-sharing
                 activities. Existing research is mainly focused on
                 either user egocentric positions in communication
                 networks or communication patterns at the community
                 level. Very few studies examine thread-level
                 communication and process patterns and their impacts on
                 the effectiveness of knowledge sharing. In this study,
                 we fill this research gap by proposing an innovative
                 analytical framework for understanding thread-level
                 knowledge sharing in online Q{\&}A communities based on
                 dialogue act theory, network analysis, and process
                 mining. More specifically, we assign a dialogue act tag
                 for each post in a discussion thread to capture its
                 conversation purpose and then apply graph and process
                 mining algorithms to examine knowledge-sharing
                 processes. Our results, which are based on a real
                 support forum dataset, show that the proposed
                 analytical framework is effective in identifying
                 important communication, conversation, and process
                 patterns that lead to helpful knowledge sharing in
                 online Q{\&}A communities.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "18",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Partington:2015:PMC,
  author =       "Andrew Partington and Moe Wynn and Suriadi Suriadi and
                 Chun Ouyang and Jonathan Karnon",
  title =        "Process Mining for Clinical Processes: a Comparative
                 Analysis of Four {Australian} Hospitals",
  journal =      j-TMIS,
  volume =       "5",
  number =       "4",
  pages =        "19:1--19:??",
  month =        jan,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2629446",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Feb 11 13:49:27 MST 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Business process analysis and process mining,
                 particularly within the health care domain, remain
                 under-utilized. Applied research that employs such
                 techniques to routinely collected health care data
                 enables stakeholders to empirically investigate care as
                 it is delivered by different health providers. However,
                 cross-organizational mining and the comparative
                 analysis of processes present a set of unique
                 challenges in terms of ensuring population and activity
                 comparability, visualizing the mined models, and
                 interpreting the results. Without addressing these
                 issues, health providers will find it difficult to use
                 process mining insights, and the potential benefits of
                 evidence-based process improvement within health will
                 remain unrealized. In this article, we present a brief
                 introduction on the nature of health care processes, a
                 review of process mining in health literature, and a
                 case study conducted to explore and learn how health
                 care data and cross-organizational comparisons with
                 process-mining techniques may be approached. The case
                 study applies process-mining techniques to
                 administrative and clinical data for patients who
                 present with chest pain symptoms at one of four public
                 hospitals in South Australia. We demonstrate an
                 approach that provides detailed insights into clinical
                 (quality of patient health) and fiscal (hospital
                 budget) pressures in the delivery of health care. We
                 conclude by discussing the key lessons learned from our
                 experience in conducting business process analysis and
                 process mining based on the data from four different
                 hospitals.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "19",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Yan:2015:MAG,
  author =       "Jiaqi Yan and Daning Hu and Stephen S. Liao and
                 Huaiqing Wang",
  title =        "Mining Agents' Goals in Agent-Oriented Business
                 Processes",
  journal =      j-TMIS,
  volume =       "5",
  number =       "4",
  pages =        "20:1--20:??",
  month =        jan,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2629448",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Feb 11 13:49:27 MST 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "When designing a business process, individual agents
                 are assigned to perform tasks based on certain goals
                 (i.e., designed process goals). However, based on their
                 own interests, real-world agents often have different
                 goals (i.e., agents' goals) and thus may behave
                 differently than designed, often resulting in reduced
                 effectiveness or efficiencies of the executed process.
                 Moreover, existing business process research lacks
                 effective methods for discovering agents' goals in the
                 actual execution of the designed business processes. To
                 address this problem, we propose an agent-oriented goal
                 mining approach to modeling, discovering, and analyzing
                 agents' goals in executed business processes using
                 historical event logs and domain data. To the best of
                 our knowledge, our research is the first to adopt the
                 agents' goal perspective to study inconsistencies
                 between the design and execution of business processes.
                 Moreover, it also provides a useful tool for
                 stakeholders to discover real-world agents' actual
                 goals and thus provides insights for improving the task
                 assignment mechanism or business process design in
                 general.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "20",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Silva:2015:PAA,
  author =       "Thushari Silva and Ma Jian and Yang Chen",
  title =        "Process Analytics Approach for {R\&D} Project
                 Selection",
  journal =      j-TMIS,
  volume =       "5",
  number =       "4",
  pages =        "21:1--21:??",
  month =        jan,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2629436",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Feb 11 13:49:27 MST 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "R{\&}D project selection plays an important role in
                 government funding agencies, as allocation of billions
                 of dollars among the proposals deemed highly
                 influential and contributive solely depend on it.
                 Efficacious assignment of reviewers is one of the most
                 critical processes that controls the quality of the
                 entire project selection and also has a serious
                 implication on business profit. Current methods that
                 focus on workflow automation are more efficient than
                 manual assignment; however, they are not effective, as
                 they fail to consider the real insight of core tasks.
                 Other decision models that analyze core tasks are
                 effective but inefficient when handling large amounts
                 of submissions, and they suffer from irrelevant
                 assignment. Furthermore, they largely ignore real deep
                 insight of back-end data such as quality of the
                 reviewers (e.g., quality and citation impact of their
                 produced research) and the effect of social
                 relationships in project selection processes that are
                 essential for identifying reviewers for
                 interdisciplinary proposal evaluation. In light of
                 these deficiencies, this research proposes a novel
                 hybrid process analytics approach to decompose the
                 complex reviewer assignment process into manageable
                 subprocesses and applies data-driven decision models
                 cum process analytics systematically from a triangular
                 perspective via the research analytics framework to
                 achieve high operational efficiencies and high-quality
                 assignment. It also analyzes big data from scientific
                 databases and generates visualized decision-ready
                 information to support effective decision making. The
                 proposed approach has been implemented to aid the
                 project selection process of the largest funding agency
                 in China and has been tested. The test results show
                 that the proposed approach has the potential to add
                 great benefits, including cost saving, improved
                 effectiveness, and increased business value.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "21",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Guo:2015:DPB,
  author =       "Xitong Guo and Sherry X. Sun and Doug Vogel",
  title =        "A Dataflow Perspective for Business Process
                 Integration",
  journal =      j-TMIS,
  volume =       "5",
  number =       "4",
  pages =        "22:1--22:??",
  month =        jan,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2629450",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Feb 11 13:49:27 MST 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Business process integration has become prevalent as
                 business increasingly crosses organizational
                 boundaries. To address the issue of protecting
                 organizations' competitive knowledge and private
                 information while also enabling business-to-business
                 (B2B) collaboration, past research has focused mainly
                 on customized public and private process design, as
                 well as structural correctness of the integrated
                 workflow. However, a dataflow perspective is important
                 for business process integration. This article presents
                 a data-flow perspective using workflow management and
                 mathematical techniques to address data exchange
                 problems in independent multistakeholder business
                 process integration in dynamic circumstances. The
                 research is conducted following a design science
                 paradigm. We build artifacts that include
                 interorganizational workflow concepts, a workflow
                 model, and a public dataset calculation method. The use
                 of the proposed artifacts is illustrated by applying
                 them to a real-world case in the Shenzhen (Chaiwan)
                 port. The utility of the artifacts is evaluated through
                 interviews with practitioners in industry. We conclude
                 that this research complements the control-flow
                 perspective in the interorganizational workflow
                 management area and also contributes to B2B
                 information-sharing literature; further, the dataflow
                 formalism can help practitioners to formally provide
                 the right data at the right time in dynamic
                 circumstances.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "22",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Jiang:2015:CCO,
  author =       "Jie Jiang and Huib Aldewereld and Virginia Dignum and
                 Yao-Hua Tan",
  title =        "Compliance Checking of Organizational Interactions",
  journal =      j-TMIS,
  volume =       "5",
  number =       "4",
  pages =        "23:1--23:??",
  month =        jan,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2629630",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Feb 11 13:49:27 MST 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "In business environments, different sorts of
                 regulations are imposed to restrict the behavior of
                 both public and private organizations, ranging from
                 legal regulations to internal policies. Regulatory
                 compliance is important for the safety of individual
                 actors as well as the overall business environment.
                 However, complexity derives from not only the contents
                 of the regulations but also their interdependencies. As
                 such, the verification of whether actors are able to
                 comply with the combined regulations cannot be done by
                 checking each regulation separately. To these ends, we
                 introduce a normative structure Norm Nets (NNs) for
                 modeling sets of interrelated regulations and setting a
                 basis for compliance checking of organizational
                 interactions against interrelated regulations. NNs
                 support a modular design by providing the constructs to
                 represent regulations and the relationships between
                 them. Additionally, we propose a computational
                 mechanism to reason about regulatory compliance by
                 mapping NNs to Colored Petri Nets (CPNs). We show that
                 compliance checking of both individual actors' behavior
                 and the collective behavior of the business environment
                 can be achieved automatically using state space
                 analysis techniques of CPNs. The approach is
                 illustrated with a case study from the domain of
                 international trade.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "23",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Ciccio:2015:DDC,
  author =       "Claudio {Di Ciccio} and Massimo Mecella",
  title =        "On the Discovery of Declarative Control Flows for
                 Artful Processes",
  journal =      j-TMIS,
  volume =       "5",
  number =       "4",
  pages =        "24:1--24:??",
  month =        jan,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2629447",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Feb 11 13:49:27 MST 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Artful processes are those processes in which the
                 experience, intuition, and knowledge of the actors are
                 the key factors in determining the decision making.
                 They are typically carried out by the ``knowledge
                 workers,'' such as professors, managers, and
                 researchers. They are often scarcely formalized or
                 completely unknown a priori. Throughout this article,
                 we discuss how we addressed the challenge of
                 discovering declarative control flows in the context of
                 artful processes. To this extent, we devised and
                 implemented a two-phase algorithm, named MINERful. The
                 first phase builds a knowledge base, where statistical
                 information extracted from logs is represented. During
                 the second phase, queries are evaluated on that
                 knowledge base, in order to infer the constraints that
                 constitute the discovered process. After outlining the
                 overall approach and offering insight on the adopted
                 process modeling language, we describe in detail our
                 discovery technique. Thereupon, we analyze its
                 performances, both from a theoretical and an
                 experimental perspective. A user-driven evaluation of
                 the quality of results is also reported on the basis of
                 a real case study. Finally, a study on the fitness of
                 discovered models with respect to synthetic and real
                 logs is presented.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "24",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Keller:2015:CMR,
  author =       "Thorben Keller and Fr{\'e}d{\'e}ric Thiesse and Elgar
                 Fleisch",
  title =        "Classification Models for {RFID}-Based Real-Time
                 Detection of Process Events in the Supply Chain: an
                 Empirical Study",
  journal =      j-TMIS,
  volume =       "5",
  number =       "4",
  pages =        "25:1--25:??",
  month =        jan,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2629449",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Feb 11 13:49:27 MST 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "RFID technology allows the collecting of fine-grained
                 real-time information on physical processes in the
                 supply chain that often cannot be monitored using
                 conventional approaches. However, because of the
                 phenomenon of false-positive reads, RFID data streams
                 resemble noisy analog measurements rather than the
                 desired recordings of activities within a business
                 process. The present study investigates the use of data
                 mining techniques for filtering and aggregating raw
                 RFID data. We consider classifiers based on logistic
                 regression, decision trees, and artificial neural
                 networks using attributes derived from low-level reader
                 data. In addition, we present a custom-made algorithm
                 for generating decision rules using artificial
                 attributes and an iterative training procedure. We
                 evaluate the classifiers using a massive set of data on
                 pallet movements collected under real-world conditions
                 at one of the largest retailers worldwide. The results
                 clearly indicate high classification performance of the
                 classification models, with the rule-based classifier
                 outperforming all others. Moreover, we show that
                 utilizing the full spectrum of data generated by the
                 reader hardware leads to superior performance compared
                 with the approaches based on timestamp and antenna
                 information proposed in prior research.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "25",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Berndt:2015:CSD,
  author =       "Donald J. Berndt and James A. McCart and Dezon K.
                 Finch and Stephen L. Luther",
  title =        "A Case Study of Data Quality in Text Mining Clinical
                 Progress Notes",
  journal =      j-TMIS,
  volume =       "6",
  number =       "1",
  pages =        "1:1--1:??",
  month =        feb,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2669368",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Apr 3 16:18:04 MDT 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Text analytic methods are often aimed at extracting
                 useful information from the vast array of unstructured,
                 free format text documents that are created by almost
                 all organizational processes. The success of any text
                 mining application rests on the quality of the
                 underlying data being analyzed, including both
                 predictive features and outcome labels. In this case
                 study, some focused experiments regarding data quality
                 are used to assess the robustness of Statistical Text
                 Mining (STM) algorithms when applied to clinical
                 progress notes. In particular, the experiments consider
                 the impacts of task complexity (by removing signals),
                 training set size, and target outcome quality. While
                 this research is conducted using a dataset drawn from
                 the medical domain, the data quality issues explored
                 are of more general interest.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "1",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Zimbra:2015:SAF,
  author =       "David Zimbra and Hsinchun Chen and Robert F. Lusch",
  title =        "Stakeholder Analyses of Firm-Related {Web} Forums:
                 Applications in Stock Return Prediction",
  journal =      j-TMIS,
  volume =       "6",
  number =       "1",
  pages =        "2:1--2:??",
  month =        feb,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2675693",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Apr 3 16:18:04 MDT 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "In this study, we present stakeholder analyses of
                 firm-related web forums. Prior analyses of firm-related
                 forums have considered all participants in the
                 aggregate, failing to recognize the potential for
                 diversity within the populations. However, distinctive
                 groups of forum participants may represent various
                 interests and stakes in a firm worthy of consideration.
                 To perform the stakeholder analyses, the Stakeholder
                 Analyzer system for firm-related web forums is
                 developed following the design science paradigm of
                 information systems research. The design of the system
                 and its approach to stakeholder analysis is guided by
                 two kernel theories, the stakeholder theory of the firm
                 and the systemic functional linguistic theory. A
                 stakeholder analysis identifies distinctive groups of
                 forum participants with shared characteristics
                 expressed in discussion and evaluates their specific
                 opinions and interests in the firm. Stakeholder
                 analyses are performed in six major firm-related forums
                 hosted on Yahoo Finance over a 3-month period. The
                 relationships between measures extracted from the
                 forums and subsequent daily firm stock returns are
                 examined using multiple linear regression models,
                 revealing statistically significant indicators of firm
                 stock returns in the discussions of the stakeholder
                 groups of each firm with stakeholder-model-adjusted
                 R$^2$ values reaching 0.83. Daily stock return
                 prediction is also performed for 31 trading days, and
                 stakeholder models correctly predicted the direction of
                 return on 67\% of trading days and generated an
                 impressive 17\% return in simulated trading of the six
                 firm stocks. These evaluations demonstrate that the
                 stakeholder analyses provided more refined assessments
                 of the firm-related forums, yielding measures at the
                 stakeholder group level that better explain and predict
                 daily firm stock returns than aggregate forum-level
                 information.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "2",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Li:2015:NBB,
  author =       "Shing-Han Li and Yu-Cheng Kao and Zong-Cyuan Zhang and
                 Ying-Ping Chuang and David C. Yen",
  title =        "A Network Behavior-Based {Botnet} Detection Mechanism
                 Using {PSO} and {$K$}-means",
  journal =      j-TMIS,
  volume =       "6",
  number =       "1",
  pages =        "3:1--3:??",
  month =        feb,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2676869",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Apr 3 16:18:04 MDT 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "In today's world, Botnet has become one of the
                 greatest threats to network security. Network
                 attackers, or Botmasters, use Botnet to launch the
                 Distributed Denial of Service (DDoS) to paralyze
                 large-scale websites or steal confidential data from
                 infected computers. They also employ ``phishing''
                 attacks to steal sensitive information (such as users'
                 accounts and passwords), send bulk email advertising,
                 and/or conduct click fraud. Even though detection
                 technology has been much improved and some solutions to
                 Internet security have been proposed and improved, the
                 threat of Botnet still exists. Most of the past studies
                 dealing with this issue used either packet contents or
                 traffic flow characteristics to identify the invasion
                 of Botnet. However, there still exist many problems in
                 the areas of packet encryption and data privacy, simply
                 because Botnet can easily change the packet contents
                 and flow characteristics to circumvent the Intrusion
                 Detection System (IDS). This study combines Particle
                 Swarm Optimization (PSO) and $K$-means algorithms to
                 provide a solution to remedy those problems and
                 develop, step by step, a mechanism for Botnet
                 detection. First, three important network behaviors are
                 identified: long active communication behavior
                 (ActBehavior), connection failure behavior
                 (FailBehavior), and network scanning behavior
                 (ScanBehavior). These behaviors are defined according
                 to the relevant prior studies and used to analyze the
                 communication activities among the infected computers.
                 Second, the features of network behaviors are extracted
                 from the flow traces in the network layer and transport
                 layer of the network equipment. Third, PSO and
                 $K$-means techniques are used to uncover the host
                 members of Botnet in the organizational network. This
                 study mainly utilizes the flow traces of a campus
                 network as an experiment. The experimental findings
                 show that this proposed approach can be employed to
                 detect the suspicious Botnet members earlier than the
                 detection application systems. In addition, this
                 proposed approach is easy to implement and can be
                 further used and extended in the campus dormitory
                 network, home networks, and the mobile 3G network.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "3",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Lee:2015:OBM,
  author =       "Yen-Hsien Lee and Paul Jen-Hwa Hu and Ching-Yi Tu",
  title =        "Ontology-Based Mapping for Automated Document
                 Management: a Concept-Based Technique for Word Mismatch
                 and Ambiguity Problems in Document Clustering",
  journal =      j-TMIS,
  volume =       "6",
  number =       "1",
  pages =        "4:1--4:??",
  month =        mar,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2688488",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 5 07:57:33 MST 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Document clustering is crucial to automated document
                 management, especially for the fast-growing volume of
                 textual documents available digitally. Traditional
                 lexicon-based approaches depend on document content
                 analysis and measure overlap of the feature vectors
                 representing different documents, which cannot
                 effectively address word mismatch or ambiguity
                 problems. Alternative query expansion and local context
                 discovery approaches are developed but suffer from
                 limited efficiency and effectiveness, because the large
                 number of expanded terms create noise and increase the
                 dimensionality and complexity of the overall feature
                 space. Several techniques extend lexicon-based analysis
                 by incorporating latent semantic indexing but produce
                 less comprehensible clustering results and questionable
                 performance. We instead propose a concept-based
                 document representation and clustering (CDRC) technique
                 and empirically examine its effectiveness using 433
                 articles concerning information systems and technology,
                 randomly selected from a popular digital library. Our
                 evaluation includes two widely used benchmark
                 techniques and shows that CDRC outperforms them.
                 Overall, our results reveal that clustering documents
                 at an ontology-based, concept-based level is more
                 effective than techniques using lexicon-based document
                 features and can generate more comprehensible
                 clustering results.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "4",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Sutanto:2015:ITC,
  author =       "Juliana Sutanto and Atreyi Kankanhalli and Bernard
                 Cheng Yian Tan",
  title =        "Investigating Task Coordination in Globally Dispersed
                 Teams: a Structural Contingency Perspective",
  journal =      j-TMIS,
  volume =       "6",
  number =       "2",
  pages =        "5:1--5:??",
  month =        jul,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2688489",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Aug 7 09:26:12 MDT 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Task coordination poses significant challenges for
                 globally dispersed teams (GDTs). Although various task
                 coordination mechanisms have been proposed for such
                 teams, there is a lack of systematic examination of the
                 appropriate coordination mechanisms for different teams
                 based on the nature of their task and the context under
                 which they operate. Prior studies on collocated teams
                 suggest matching their levels of task dependence to
                 specific task coordination mechanisms for effective
                 coordination. This research goes beyond the earlier
                 work by also considering additional contextual factors
                 of GDT (i.e., temporal dispersion and time constraints)
                 in deriving their optimal IT-mediated task coordination
                 mechanisms. Adopting the structural contingency theory,
                 we propose optimal IT-mediated task coordination
                 portfolios to fit the different levels of task
                 dependence, temporal dispersion, and perceived time
                 constraint of GDTs. The proposed fit is tested through
                 a survey and profile analysis of 95 globally dispersed
                 software development teams in a large financial
                 organization. We find, as hypothesized, that the extent
                 of fit between the actual IT-mediated task coordination
                 portfolios used by the surveyed teams and their optimal
                 portfolios proposed here is positively related to their
                 task coordination effectiveness that in turn impacts
                 the team's efficiency and effectiveness. The
                 implications for theory and practice are discussed.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "5",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Basole:2015:UBE,
  author =       "Rahul C. Basole and Martha G. Russell and Jukka
                 Huhtam{\"a}ki and Neil Rubens and Kaisa Still and
                 Hyunwoo Park",
  title =        "Understanding Business Ecosystem Dynamics: a
                 Data-Driven Approach",
  journal =      j-TMIS,
  volume =       "6",
  number =       "2",
  pages =        "6:1--6:??",
  month =        jul,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2724730",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Aug 7 09:26:12 MDT 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Business ecosystems consist of a heterogeneous and
                 continuously evolving set of entities that are
                 interconnected through a complex, global network of
                 relationships. However, there is no well-established
                 methodology to study the dynamics of this network.
                 Traditional approaches have primarily utilized a single
                 source of data of relatively established firms;
                 however, these approaches ignore the vast number of
                 relevant activities that often occur at the individual
                 and entrepreneurial levels. We argue that a data-driven
                 visualization approach, using both institutionally and
                 socially curated datasets, can provide important
                 complementary, triangulated explanatory insights into
                 the dynamics of interorganizational networks in general
                 and business ecosystems in particular. We develop novel
                 visualization layouts to help decision makers
                 systemically identify and compare ecosystems. Using
                 traditionally disconnected data sources on deals and
                 alliance relationships (DARs), executive and funding
                 relationships (EFRs), and public opinion and discourse
                 (POD), we empirically illustrate our data-driven method
                 of data triangulation and visualization techniques
                 through three cases in the mobile industry Google's
                 acquisition of Motorola Mobility, the coopetitive
                 relation between Apple and Samsung, and the strategic
                 partnership between Nokia and Microsoft. The article
                 concludes with implications and future research
                 opportunities.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "6",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Zhao:2015:RBP,
  author =       "Xiaohui Zhao and Chengfei Liu and Sira Yongchareon and
                 Marek Kowalkiewicz and Wasim Sadiq",
  title =        "Role-Based Process View Derivation and Composition",
  journal =      j-TMIS,
  volume =       "6",
  number =       "2",
  pages =        "7:1--7:??",
  month =        jul,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2744207",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Aug 7 09:26:12 MDT 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "The process view concept deploys a partial and
                 temporal representation to adjust the visible view of a
                 business process according to various perception
                 constraints of users. Process view technology is of
                 practical use for privacy protection and authorization
                 control in process-oriented business management. Owing
                 to complex organizational structure, it is challenging
                 for large companies to accurately specify the diverse
                 perception of different users over business processes.
                 Aiming to tackle this issue, this article presents a
                 role-based process view model to incorporate role
                 dependencies into process view derivation. Compared to
                 existing process view approaches, ours particularly
                 supports runtime updates to the process view
                 perceivable to a user with specific view merging
                 operations, thereby enabling the dynamic tracing of
                 process perception. A series of rules and theorems are
                 established to guarantee the structural consistency and
                 validity of process view transformation. A hypothetical
                 case is conducted to illustrate the feasibility of our
                 approach, and a prototype is developed for the
                 proof-of-concept purpose.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "7",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Liu:2015:WNS,
  author =       "Dengpan Liu and Sumit Sarkar and Chelliah
                 Sriskandarajah",
  title =        "Who's Next? {Scheduling} Personalization Services with
                 Variable Service Times",
  journal =      j-TMIS,
  volume =       "6",
  number =       "2",
  pages =        "8:1--8:??",
  month =        jul,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2764920",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Aug 7 09:26:12 MDT 2015",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Online personalization has become quite prevalent in
                 recent years, with firms able to derive additional
                 profits from such services. As the adoption of such
                 services grows, firms implementing such practices face
                 some operational challenges. One important challenge
                 lies in the complexity associated with the
                 personalization process and how to deploy available
                 resources to handle such complexity. The complexity is
                 exacerbated when a site faces a large volume of
                 requests in a short amount of time, as is often the
                 case for e-commerce and content delivery sites. In such
                 situations, it is generally not possible for a site to
                 provide perfectly personalized service to all requests.
                 Instead, a firm can provide differentiated service to
                 requests based on the amount of profiling information
                 available about the visitor. We consider a scenario
                 where the revenue function is concave, capturing the
                 diminishing returns from personalization effort. Using
                 a batching approach, we determine the optimal
                 scheduling policy (i.e., time allocation and sequence
                 of service) for a batch that accounts for the
                 externality cost incurred when a request is provided
                 service before other waiting requests. The batching
                 approach leads to sunk costs incurred when visitors
                 wait for the next batch to begin. An optimal admission
                 control policy is developed to prescreen new request
                 arrivals. We show how the policy can be implemented
                 efficiently when the revenue function is complex and
                 there are a large number of requests that can be served
                 in a batch. Numerical experiments show that the
                 proposed approach leads to substantial improvements
                 over a linear approximation of the concave revenue
                 function. Interestingly, we find that the improvements
                 in firm profits are not only (or primarily) due to the
                 different service times that are obtained when using
                 the nonlinear personalization function-there is a
                 ripple effect on the admission control policy that
                 incorporates these optimized service times, which
                 contributes even more to the additional profits than
                 the service time optimization by itself.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "8",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Bai:2015:RAM,
  author =       "Xue Bai and James R. Marsden and William T. {Ross,
                 Jr.} and Gang Wang",
  title =        "Relationships Among Minimum Requirements, {Facebook}
                 Likes, and {Groupon} Deal Outcomes",
  journal =      j-TMIS,
  volume =       "6",
  number =       "3",
  pages =        "9:1--9:??",
  month =        oct,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2764919",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Jan 25 07:36:47 MST 2016",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Daily deal coupons have gained a prominent foothold on
                 the web. The earliest and largest player is Groupon.
                 Originally, Groupon deals were a mix of deals with a
                 minimum requirement (MR) of coupon sales before a
                 deal became effective and of deals without a minimum
                 requirement (NMR). Eventually, Groupon stopped using
                 MR deals. For Groupon and its retailer customers, might
                 this decision have actually resulted in negative
                 impacts for both parties (fewer coupons sold and lower
                 revenue)? The structure of Groupon deals (including a
                 ``Facebook like'' option) together with electronic
                 access to the necessary data offered the opportunity to
                 empirically investigate these questions. We analyzed
                 relationships among MR, Facebook likes (FL), quantity
                 of coupons sold, and total revenue, performing the
                 analysis across the four largest retail categories.
                 Using timestamped empirical data, we completed a
                 propensity score analysis of causal effects. We find
                 that the presence of MR increases Facebook likes,
                 quantity of coupons sold, and total revenue at the time
                 point when the MR is met and at subsequent 2-hour
                 intervals over the horizon of deals. A key finding is
                 that the initial differences observed when MR is met
                 not only continue but also actually increase over the
                 life of the deals.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "9",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Bhowmik:2015:RSH,
  author =       "Tanmay Bhowmik and Nan Niu and Prachi Singhania and
                 Wentao Wang",
  title =        "On the Role of Structural Holes in Requirements
                 Identification: an Exploratory Study on Open-Source
                 Software Development",
  journal =      j-TMIS,
  volume =       "6",
  number =       "3",
  pages =        "10:1--10:??",
  month =        oct,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2795235",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Jan 25 07:36:47 MST 2016",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/gnu.bib;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Requirements identification is a human-centric
                 activity that involves interaction among multiple
                 stakeholders. Traditional requirements engineering (RE)
                 techniques addressing stakeholders' social interaction
                 are mainly part of a centralized process intertwined
                 with a specific phase of software development. However,
                 in open-source software (OSS) development,
                 stakeholders' social interactions are often
                 decentralized, iterative, and dynamic. Little is known
                 about new requirements identification in OSS and the
                 stakeholders' organizational arrangements supporting
                 such an activity. In this article, we investigate the
                 theory of structural hole from the context of
                 contributing new requirements in OSS projects.
                 Structural hole theory suggests that stakeholders
                 positioned in the structural holes in their social
                 network are able to produce new ideas. In this study,
                 we find that structural hole positions emerge in
                 stakeholders' social network and these positions are
                 positively related to contributing a higher number of
                 new requirements. We find that along with structural
                 hole positions, stakeholders' role is also an important
                 part in identifying new requirements. We further
                 observe that structural hole positions evolve over
                 time, thereby identifying requirements to realize
                 enriched features. Our work advances the fundamental
                 understanding of the RE process in a decentralized
                 environment and opens avenues for improved techniques
                 supporting this process.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "10",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Bhattacharya:2015:RNA,
  author =       "Devipsita Bhattacharya and Sudha Ram",
  title =        "{RT @News}: an Analysis of News Agency Ego Networks in
                 a Microblogging Environment",
  journal =      j-TMIS,
  volume =       "6",
  number =       "3",
  pages =        "11:1--11:??",
  month =        oct,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2811270",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Jan 25 07:36:47 MST 2016",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "News agencies regularly use Twitter to publicize and
                 increase readership of their articles. Although
                 substantial research on the spread of news on Twitter
                 exists, there hasn't been much focus on the study of
                 the spread of news articles. In this study, we present
                 an innovative methodology involving weighted ego
                 networks to understand how news agencies propagate news
                 articles using their Twitter handle. We propose a set
                 of measures to compare the propagation process of
                 different news agencies by studying important aspects
                 such as volume, extent of spread, conversion rate,
                 multiplier effect, lifespan, hourly response, and
                 audience participation. Using a dataset of tweets
                 collected over a period of 6 months, we apply our
                 methodology and suggest a framework to help news
                 agencies gauge their performance on social media and
                 also provide critical insights into the phenomenon of
                 news article propagation on Twitter.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "11",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Roy:2015:MOU,
  author =       "Arindam Roy and Shamik Sural and Arun Kumar Majumdar
                 and Jaideep Vaidya and Vijayalakshmi Atluri",
  title =        "Minimizing Organizational User Requirement while
                 Meeting Security Constraints",
  journal =      j-TMIS,
  volume =       "6",
  number =       "3",
  pages =        "12:1--12:??",
  month =        oct,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2811269",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Jan 25 07:36:47 MST 2016",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Large systems are complex and typically need automatic
                 configuration to be managed effectively. In any
                 organization, numerous tasks have to be carried out by
                 employees. However, due to security needs, it is not
                 feasible to directly assign any existing task to the
                 first available employee. In order to meet many
                 additional security requirements, constraints such as
                 separation of duty, cardinality and binding have to be
                 taken into consideration. Meeting these requirements
                 imposes extra burden on organizations, which, however,
                 is unavoidable in order to ensure security. While a
                 trivial way of ensuring security is to assign each user
                 to a single task, business organizations would
                 typically like to minimize their costs and keep
                 staffing requirements to a minimum. To meet these
                 contradictory goals, we define the problem of
                 Cardinality Constrained-Mutually Exclusive Task Minimum
                 User Problem (CMUP), which aims to find the minimum
                 users that can carry out a set of tasks while
                 satisfying the given security constraints. We show that
                 the CMUP problem is equivalent to a constrained version
                 of the weak chromatic number problem in hypergraphs,
                 which is NP-hard. We, therefore, propose a greedy
                 solution. Our experimental evaluation shows that the
                 proposed algorithm is both efficient and effective.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "12",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Gomez-Uribe:2016:NRS,
  author =       "Carlos A. Gomez-Uribe and Neil Hunt",
  title =        "The {Netflix} Recommender System: Algorithms, Business
                 Value, and Innovation",
  journal =      j-TMIS,
  volume =       "6",
  number =       "4",
  pages =        "13:1--13:??",
  month =        jan,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2843948",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Jan 25 07:36:48 MST 2016",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "This article discusses the various algorithms that
                 make up the Netflix recommender system, and describes
                 its business purpose. We also describe the role of
                 search and related algorithms, which for us turns into
                 a recommendations problem as well. We explain the
                 motivations behind and review the approach that we use
                 to improve the recommendation algorithms, combining A/B
                 testing focused on improving member retention and
                 medium term engagement, as well as offline
                 experimentation using historical member engagement
                 data. We discuss some of the issues in designing and
                 interpreting A/B tests. Finally, we describe some
                 current areas of focused innovation, which include
                 making our recommender system global and language
                 aware.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "13",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Krishnamurthy:2016:PDP,
  author =       "Rajiv Krishnamurthy and Varghese Jacob and Suresh
                 Radhakrishnan and Kutsal Dogan",
  title =        "Peripheral Developer Participation in Open Source
                 Projects: an Empirical Analysis",
  journal =      j-TMIS,
  volume =       "6",
  number =       "4",
  pages =        "14:1--14:??",
  month =        jan,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2820618",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Jan 25 07:36:48 MST 2016",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/gnu.bib;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "The success of the Open Source model of software
                 development depends on the voluntary participation of
                 external developers (the peripheral developers), a
                 group that can have distinct motivations from that of
                 project founders (the core developers). In this study,
                 we examine peripheral developer participation by
                 empirically examining approximately 2,600 open source
                 projects. In particular, we hypothesize that peripheral
                 developer participation is higher when the potential
                 for building reputation by gaining recognition from
                 project stakeholders is higher. We consider recognition
                 by internal stakeholders (such as core developers) and
                 external stakeholders (such as end-users and peers). We
                 find a positive association between peripheral
                 developer participation and the potential of
                 stakeholder recognition after controlling for bug
                 reports, feature requests, and other key factors. Our
                 findings provide important insights for OSS founders
                 and corporate managers for open sourcing or OSS
                 adoption decisions.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "14",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Liaskos:2016:SRO,
  author =       "Christos Liaskos and Ageliki Tsioliaridou",
  title =        "Service Ratio-Optimal, Content Coherence-Aware Data
                 Push Systems",
  journal =      j-TMIS,
  volume =       "6",
  number =       "4",
  pages =        "15:1--15:??",
  month =        jan,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2850423",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Jan 25 07:36:48 MST 2016",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Advertising new information to users via push is the
                 trigger of operation for many contemporary information
                 systems. Furthermore, passive optical networks are
                 expected to extend the reachability of high-quality
                 push services to thousands of clients. The efficiency
                 of a push service is the ratio of successfully informed
                 users. However, pushing only data of high popularity
                 can degrade the thematic coherency of the content. The
                 present work offers a novel, analysis-derived, tunable
                 way for selecting data for push services. The proposed
                 scheme can maximize the service ratio of a push system
                 with regard to data coherence constraints. Extensive
                 simulations demonstrate the efficiency of the scheme
                 compared to alternative solutions. The proposed scheme
                 is the first to tackle the problem of data
                 coherence-aware, service ratio optimization of push
                 services.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "15",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Lu:2016:CCB,
  author =       "Xianghua Lu and Xia Zhao and Ling Xue",
  title =        "Is Combining Contextual and Behavioral Targeting
                 Strategies Effective in Online Advertising?",
  journal =      j-TMIS,
  volume =       "7",
  number =       "1",
  pages =        "1:1--1:??",
  month =        mar,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2883816",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Jun 20 11:28:19 MDT 2016",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Online targeting has been increasingly used to deliver
                 ads to consumers. But discovering how to target the
                 most valuable web visitors and generate a high response
                 rate is still a challenge for advertising
                 intermediaries and advertisers. The purpose of this
                 study is to examine how behavioral targeting (BT)
                 impacts users' responses to online ads and particularly
                 whether BT works better in combination with contextual
                 targeting (CT). Using a large, individual-level
                 clickstream data set of an automobile advertising
                 campaign from an Internet advertising intermediary,
                 this study examines the impact of BT and CT strategies
                 on users' click behavior. The results show that (1)
                 targeting a user with behavioral characteristics that
                 are closely related to ads does not necessarily
                 increase the click through rates (CTRs); whereas,
                 targeting a user with behavioral characteristics that
                 are loosely related to ads leads to a higher CTR, and
                 (2) BT and CT work better in combination. Our study
                 contributes to online advertising design literature and
                 provides important managerial implications for
                 advertising intermediaries and advertisers on targeting
                 individual users.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "1",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Lui:2016:EMC,
  author =       "Tsz-Wai Lui and Gabriele Piccoli",
  title =        "The Effect of a Multichannel Customer Service System
                 on Customer Service and Financial Performance",
  journal =      j-TMIS,
  volume =       "7",
  number =       "1",
  pages =        "2:1--2:??",
  month =        mar,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2875444",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Jun 20 11:28:19 MDT 2016",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Customer service is an important competitive lever for
                 the modern firm. At the same time, the continuous
                 evolution and performance improvements in information
                 technology (IT) capabilities have enabled the
                 utilization of multichannel service delivery
                 strategies. Our research focuses on IT-enabled customer
                 service systems (CSS) and their effect on firm
                 performance. Previous studies have failed to find a
                 consensus on the effect of a new self-service channel
                 on the firm's performance. We argue that the embedded
                 assumptions underpinning the previous research are
                 responsible for these mixed findings. Consequently,
                 using archival data from 169 hotels affiliated with a
                 hotel chain, we designed a longitudinal multichannel
                 study to resolve some of these inconsistencies. Our
                 results illustrate that when firms implement an
                 IT-enabled self-service channel to complement their
                 existing customer service infrastructure, they
                 experience an early negative effect on financial
                 performance due to the disruption of the service
                 processes. Thus, the multichannel CSS generates a
                 positive effect only when the new process becomes a
                 stable part of the organizational procedures. Our
                 findings suggest that researchers evaluate the effect
                 of a technological initiative after the new business
                 process has been stabilized and consider that an
                 additional IT-enabled self-service channel rarely
                 operates in isolation.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "2",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Sun:2016:UAN,
  author =       "Yutian Sun and Jianwen Su and Jian Yang",
  title =        "Universal Artifacts: a New Approach to Business
                 Process Management {(BPM)} Systems",
  journal =      j-TMIS,
  volume =       "7",
  number =       "1",
  pages =        "3:1--3:??",
  month =        mar,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2886104",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Jun 20 11:28:19 MDT 2016",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "In most BPM systems (a.k.a. workflow systems), the
                 data for process execution is scattered across
                 databases for enterprise, auxiliary local data stores
                 within the BPM systems, and even file systems (e.g.,
                 specification of process models). The interleaving
                 nature of data management and BP execution and the lack
                 of a coherent conceptual data model for all data needed
                 for execution make it hard for (1) providing
                 Business-Process-as-a-Service (BPaaS) and (2) effective
                 support for collaboration between business processes.
                 The primary reason is that an enormous effort is
                 required for maintaining both the engines and the data
                 for the client applications. In particular, different
                 modeling languages and different BPM systems make
                 process interoperation one of the toughest challenges.
                 In this article, we formulate a concept of a
                 ``universal artifact,'' which extends artifact-centric
                 models by capturing all needed data for a process
                 instance throughout its execution. A framework called
                 SeGA based on universal artifacts is developed to
                 support separation of data and BP execution, a key
                 principle for BPM systems. We demonstrate in this
                 article that SeGA is versatile enough to fully
                 facilitate not only executions of individual processes
                 (to support BPaaS) but also various collaboration
                 models. Moreover, SeGA reduces the complexity in
                 runtime management including runtime querying,
                 constraints enforcement, and dynamic modification upon
                 collaboration across possibly different BPM systems.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "3",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Li:2016:RTA,
  author =       "Shing-Han Li and David C. Yen and Ying-Ping Chuang",
  title =        "A Real-Time Audit Mechanism Based on the Compression
                 Technique",
  journal =      j-TMIS,
  volume =       "7",
  number =       "2",
  pages =        "4:1--4:??",
  month =        aug,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2629569",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 16 15:48:29 MDT 2017",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/datacompression.bib;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Log management and log auditing have become
                 increasingly crucial for enterprises in this era of
                 information and technology explosion. The log analysis
                 technique is useful for discovering possible problems
                 in business processes and preventing illegal-intrusion
                 attempts and data-tampering attacks. Because of the
                 complexity of the dynamically changing environment,
                 auditing a tremendous number of data is a challenging
                 issue. We provide a real-time audit mechanism to
                 improve the aforementioned problems in log auditing.
                 This mechanism was developed based on the
                 Lempel--Ziv--Welch (LZW) compression technique to
                 facilitate effective compression and provide reliable
                 auditing log entries. The mechanism can be used to
                 predict unusual activities when compressing the log
                 data according to pre-defined auditing rules. Auditors
                 using real-time and continuous monitoring can perceive
                 instantly the most likely anomalies or exceptions that
                 could cause problems. We also designed a user interface
                 that allows auditors to define the various compression
                 and audit parameters, using real log cases in the
                 experiment to verify the feasibility and effectiveness
                 of this proposed audit mechanism. In summary, this
                 mechanism changes the log access method and improves
                 the efficiency of log analysis. This mechanism greatly
                 simplifies auditing so that auditors must only trace
                 the sources and causes of the problems related to the
                 detected anomalies. This greatly reduces the processing
                 time of analytical audit procedures and the manual
                 checking time, and improves the log audit efficiency.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "4",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Hashmi:2016:WSN,
  author =       "Khayyam Hashmi and Zaki Malik and Erfan Najmi and Amal
                 Alhosban and Brahim Medjahed",
  title =        "A {Web} Service Negotiation Management and {QoS}
                 Dependency Modeling Framework",
  journal =      j-TMIS,
  volume =       "7",
  number =       "2",
  pages =        "5:1--5:??",
  month =        aug,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2893187",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 16 15:48:29 MDT 2017",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Information Management Systems that outsource part of
                 the functionality to other (likely unknown) services
                 need an effective way to communicate with these
                 services, so that a mutually beneficial solution can be
                 generated. This includes bargaining for their optimal
                 customizations and the discovery of overlooked
                 potential solutions. In this article, we present an
                 automated negotiation framework for information systems
                 (denoted as WebNeg ) that can be used by both the
                 parties for conducting negotiations. WebNeg uses a
                 Genetic Algorithm (GA)-based approach for finding
                 acceptable solutions in multiparty and multiobjective
                 scenarios. The GA is enhanced using a new operator
                 called Norm, which represents the cumulative knowledge
                 of all the parties involved in the negotiation process.
                 Norm incorporates the dependencies of different quality
                 attributes of independently developed component
                 services for the system composition. This enables
                 WebNeg to find a better solution in the context of the
                 current requirements. Experiment results indicate the
                 applicability and improved performance of WebNeg (in
                 comparison with existing similar works) in facilitating
                 the negotiation management involved in a web
                 service-based information composition process.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "5",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Gupta:2016:SCS,
  author =       "Agam Gupta and Biswatosh Saha and Uttam K. Sarkar",
  title =        "Systemic Concentration in Sponsored Search Markets:
                 The Role of Time Window in Click-Through-Rate
                 Computation",
  journal =      j-TMIS,
  volume =       "7",
  number =       "2",
  pages =        "6:1--6:??",
  month =        aug,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2934695",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 16 15:48:29 MDT 2017",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Keyword-based search engine advertising markets on the
                 Internet, referred to as Sponsored Search Markets
                 (SSMs), have reduced entry barriers to advertising for
                 niche players. Known empirical research, though scant
                 and emerging, suggests that while these markets
                 provided niche firms with greater access, they do
                 exhibit high levels of concentration-a phenomenon that
                 warrants further study. This research, using
                 agent-based simulation of SSM, investigates the role of
                 ``market rules'' and ``advertiser practices'' in
                 generating emergent click share heterogeneity among
                 advertisers in an industry. SSMs often rank ads based
                 on the click-through rate (CTR) that gives rise to
                 reinforcing dynamics at an individual keyword level. In
                 the presence of spillovers arising from advertisers'
                 practice of managing keyword bids with a cost cap
                 operating on the keyword portfolio, these reinforcing
                 dynamics can endogenously generate industry-level
                 concentration. Analysis of counterfactual markets with
                 different window sizes used to compute CTR reveals that
                 industry-level concentration bears an inverted-``U''
                 relationship with window size.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "6",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Tsai:2016:DFK,
  author =       "Ming-Feng Tsai and Chuan-Ju Wang and Po-Chuan Chien",
  title =        "Discovering Finance Keywords via Continuous-Space
                 Language Models",
  journal =      j-TMIS,
  volume =       "7",
  number =       "3",
  pages =        "7:1--7:??",
  month =        oct,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2948072",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 16 15:48:30 MDT 2017",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "The growing amount of public financial data makes it
                 increasingly important to learn how to discover
                 valuable information for financial decision making.
                 This article proposes an approach to discovering
                 financial keywords from a large number of financial
                 reports. In particular, we apply the continuous
                 bag-of-words (CBOW) model, a well-known
                 continuous-space language model, to the textual
                 information in 10-K financial reports to discover new
                 finance keywords. In order to capture word meanings to
                 better locate financial terms, we also present a novel
                 technique to incorporate syntactic information into the
                 CBOW model. Experimental results on four prediction
                 tasks using the discovered keywords demonstrate that
                 our approach is effective for discovering
                 predictability keywords for post-event volatility,
                 stock volatility, abnormal trading volume, and excess
                 return predictions. We also analyze the discovered
                 keywords that attest to the ability of the proposed
                 method to capture both syntactic and contextual
                 information between words. This shows the success of
                 this method when applied to the field of finance.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "7",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Burnay:2016:SOS,
  author =       "Corentin Burnay",
  title =        "Are Stakeholders the Only Source of Information for
                 Requirements Engineers? {Toward} a Taxonomy of
                 Elicitation Information Sources",
  journal =      j-TMIS,
  volume =       "7",
  number =       "3",
  pages =        "8:1--8:??",
  month =        oct,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2965085",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 16 15:48:30 MDT 2017",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Requirements elicitation consists in collecting and
                 documenting information about the requirements from a
                 system-to-be and about the environment of that system.
                 Elicitation forms a critical step in the design of any
                 information system, subject to many challenges like
                 information incompleteness, variability, or ambiguity.
                 To deal with these challenges, requirements engineers
                 heavily rely on stakeholders, who turn out to be one of
                 the most significant provider of information during
                 elicitation. Sometimes, this comes at the cost of less
                 attention being paid by engineers to other sources of
                 information accessible in a business. In this article,
                 we try to deal with this issue by studying the
                 different sources of information that can be used by
                 engineers when designing a system. We propose TELIS (a
                 Taxonomy of Elicitation Sources), which can be used
                 during elicitation to review more systematically the
                 sources of information about a system-to-be. TELIS was
                 produced through a series of empirical studies and was
                 partially validated through a real-world case study.
                 Our objective in this article is to increase the
                 awareness of engineers about the other information
                 providers within a business. Ultimately, we believe our
                 taxonomy may help in better dealing with classical
                 elicitation challenges and increase the chances of
                 successful information systems design.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "8",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Xu:2016:RMB,
  author =       "Jiajie Xu and Chengfei Liu and Xiaohui Zhao and Sira
                 Yongchareon and Zhiming Ding",
  title =        "Resource Management for Business Process Scheduling in
                 the Presence of Availability Constraints",
  journal =      j-TMIS,
  volume =       "7",
  number =       "3",
  pages =        "9:1--9:??",
  month =        oct,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2990197",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 16 15:48:30 MDT 2017",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "In the context of business process management, the
                 resources required by business processes, such as
                 workshop staff, manufacturing machines, etc., tend to
                 follow certain availability patterns, due to
                 maintenance cycles, work shifts and other factors. Such
                 availability patterns heavily influence the efficiency
                 and effectiveness of enterprise resource management.
                 Most existing process scheduling and resource
                 management approaches tend to tune the process
                 structure to seek better resource utilisation, yet
                 neglect the constraints on resource availability. In
                 this article, we investigate the scheduling of business
                 process instances in accordance with resource
                 availability patterns, to find out how enterprise
                 resources can be rationally and sufficiently used.
                 Three heuristic-based planning strategies are proposed
                 to maximise the process instance throughput together
                 with another strategy based on a genetic algorithm. The
                 performance of these strategies has been evaluated by
                 conducting experiments of different settings and
                 analysing the strategy characteristics.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "9",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Roy:2017:OEA,
  author =       "Arindam Roy and Shamik Sural and Arun Kumar Majumdar
                 and Jaideep Vaidya and Vijayalakshmi Atluri",
  title =        "On Optimal Employee Assignment in Constrained
                 Role-Based Access Control Systems",
  journal =      j-TMIS,
  volume =       "7",
  number =       "4",
  pages =        "10:1--10:??",
  month =        jan,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2996470",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 16 15:48:30 MDT 2017",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Since any organizational environment is typically
                 resource constrained, especially in terms of human
                 capital, organization managers would like to maximize
                 the utilization of available human resources. However,
                 tasks cannot simply be assigned to arbitrary employees
                 since the employee needs to have the necessary
                 capabilities for executing a task. Furthermore,
                 security policies constrain the assignment of tasks to
                 employees, especially given the other tasks assigned to
                 the same employee. Since role-based access control
                 (RBAC) is the most commonly used access control model
                 for commercial information systems, we limit our
                 attention to consider constraints in RBAC. In this
                 article, we define the Employee Assignment Problem
                 (EAP), which aims to identify an employee to role
                 assignment such that it permits the maximal flexibility
                 in assigning tasks to employees while ensuring that the
                 required security constraints are met. We prove that
                 finding an optimal solution is NP-complete and
                 therefore provide a greedy solution. Experimental
                 evaluation of the proposed approach shows that it is
                 both efficient and effective.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "10",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Chen:2017:DLN,
  author =       "Hao Chen and Keli Xiao and Jinwen Sun and Song Wu",
  title =        "A Double-Layer Neural Network Framework for
                 High-Frequency Forecasting",
  journal =      j-TMIS,
  volume =       "7",
  number =       "4",
  pages =        "11:1--11:??",
  month =        jan,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3021380",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 16 15:48:30 MDT 2017",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Nowadays, machine trading contributes significantly to
                 activities in the equity market, and forecasting market
                 movement under high-frequency scenario has become an
                 important topic in finance. A key challenge in
                 high-frequency market forecasting is modeling the
                 dependency structure among stocks and business sectors,
                 with their high dimensionality and the requirement of
                 computational efficiency. As a group of powerful
                 models, neural networks (NNs) have been used to capture
                 the complex structure in many studies. However, most
                 existing applications of NNs only focus on forecasting
                 with daily or monthly data, not with minute-level data
                 that usually contains more noises. In this article, we
                 propose a novel double-layer neural (DNN) network for
                 high-frequency forecasting, with links specially
                 designed to capture dependence structures among stock
                 returns within different business sectors. Various
                 important technical indicators are also included at
                 different layers of the DNN framework. Our model
                 framework allows update over time to achieve the best
                 goodness-of-fit with the most recent data. The model
                 performance is tested based on 100 stocks with the
                 largest capitals from the S8P 500. The results show
                 that the proposed framework outperforms benchmark
                 methods in terms of the prediction accuracy and
                 returns. Our method will help in financial analysis and
                 trading strategy designs.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "11",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Lu:2017:SLE,
  author =       "Yan Lu and Michael Chau and Patrick Y. K. Chau",
  title =        "Are Sponsored Links Effective? {Investigating} the
                 Impact of Trust in Search Engine Advertising",
  journal =      j-TMIS,
  volume =       "7",
  number =       "4",
  pages =        "12:1--12:??",
  month =        jan,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3023365",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 16 15:48:30 MDT 2017",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "As information on the Internet grows exponentially,
                 online users primarily rely on search engines (SEs) to
                 locate e-commerce sites for online shopping. To
                 generate revenue while providing free service to users,
                 SE companies offer sponsored link (SL) placements to
                 e-commerce sites that want to appear in the first SE
                 results page. However, the lack of users' trust in SE
                 advertising indicates that SEs should utilize
                 strategies to project trustworthiness on this
                 mechanism. Despite these insights, the role of users'
                 trust in the operation of SE advertising is still an
                 unexplored territory. To address this issue, a
                 theoretical model was synthesized from the social
                 psychology literature, the marketing literature, and
                 the trust literature to investigate the factors that
                 may pose impacts on the effectiveness of SE advertising
                 by influencing users' perception of both cognitive and
                 emotional trust. A laboratory experiment was conducted.
                 The findings document the importance of incorporating
                 emotional components of trust in the study of online
                 communication by showing that emotional dimension of
                 trust is different from and complementary to cognitive
                 trust in facilitating online communication. The
                 findings also provide valuable implications for
                 practitioners to design and provide more effective SLs
                 that can benefit all parties involved.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "12",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Pika:2017:MRP,
  author =       "Anastasiia Pika and Michael Leyer and Moe T. Wynn and
                 Colin J. Fidge and Arthur H. M. Ter Hofstede and Wil M.
                 P. {Van Der Aalst}",
  title =        "Mining Resource Profiles from Event Logs",
  journal =      j-TMIS,
  volume =       "8",
  number =       "1",
  pages =        "1:1--1:??",
  month =        may,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3041218",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Sep 16 11:43:32 MDT 2017",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "In most business processes, several activities need to
                 be executed by human resources and cannot be fully
                 automated. To evaluate resource performance and
                 identify best practices as well as opportunities for
                 improvement, managers need objective information about
                 resource behaviors. Companies often use information
                 systems to support their processes, and these systems
                 record information about process execution in event
                 logs. We present a framework for analyzing and
                 evaluating resource behavior through mining such event
                 logs. The framework provides (1) a method for
                 extracting descriptive information about resource
                 skills, utilization, preferences, productivity, and
                 collaboration patterns; (2) a method for analyzing
                 relationships between different resource behaviors and
                 outcomes; and (3) a method for evaluating the overall
                 resource productivity, tracking its changes over time,
                 and comparing it to the productivity of other
                 resources. To demonstrate the applicability of our
                 framework, we apply it to analyze employee behavior in
                 an Australian company and evaluate its usefulness by a
                 survey among industry managers.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "1",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Eftekhari:2017:DHI,
  author =       "Saeede Eftekhari and Niam Yaraghi and Ranjit Singh and
                 Ram D. Gopal and R. Ramesh",
  title =        "Do Health Information Exchanges Deter Repetition of
                 Medical Services?",
  journal =      j-TMIS,
  volume =       "8",
  number =       "1",
  pages =        "2:1--2:??",
  month =        may,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3057272",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Sep 16 11:43:32 MDT 2017",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Repetition of medical services by providers is one of
                 the major sources of healthcare costs. The lack of
                 access to previous medical information on a patient at
                 the point of care often leads a physician to perform
                 medical procedures that have already been done.
                 Multiple healthcare initiatives and legislation at both
                 the federal and state levels have mandated Health
                 Information Exchange (HIE) systems to address this
                 problem. This study aims to assess the extent to which
                 HIE could reduce these repetitions, using data from
                 Centers for Medicare 8 Medicaid Services and a regional
                 HIE organization. A 2-Stage Least Square model is
                 developed to predict the impact of HIE on repetitions
                 of two classes of procedures: diagnostic and
                 therapeutic. The first stage is a predictive analytic
                 model that estimates the duration of tenure of each HIE
                 member-practice. Based on these estimates, the second
                 stage predicts the effect of providers' HIE tenure on
                 their repetition of medical services. The model
                 incorporates moderating effects of a federal quality
                 assurance program and the complexity of medical
                 procedures with a set of control variables. Our
                 analyses show that a practice's tenure with HIE
                 significantly lowers the repetition of therapeutic
                 medical procedures, while diagnostic procedures are not
                 impacted. The medical reasons for the effects observed
                 in each class of procedures are discussed. The results
                 will inform healthcare policymakers and provide
                 insights on the business models of HIE platforms.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "2",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Kakar:2017:IRB,
  author =       "Adarsh Kumar Kakar",
  title =        "Investigating the Relationships Between the Use
                 Contexts, User Perceived Values, and Loyalty to a
                 Software Product",
  journal =      j-TMIS,
  volume =       "8",
  number =       "1",
  pages =        "3:1--3:??",
  month =        may,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3057271",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Sep 16 11:43:32 MDT 2017",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "In this study, we propose that software products
                 provide three types of value-utilitarian, hedonic, and
                 social-that impact user loyalty. Although the
                 Technology Acceptance Model (TAM) has focused on the
                 user impacts of utilitarian and hedonic values provided
                 by utilitarian and hedonic software products on system
                 use, the impact of social value provided by the
                 software products in general have been largely ignored.
                 The results of a longitudinal study with actual users
                 of three types of software products show that all three
                 types of software products-utilitarian (Producteev),
                 hedonic (Kerbal), and social (Facebook)-provide
                 significant but varying degrees of all three types of
                 values. Further, the value derived by the users'
                 primary use context moderated the impact of the
                 secondary values provided by the software product to
                 the users on their loyalty for the product.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "3",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Bhattacharjee:2017:IWS,
  author =       "Sudip Bhattacharjee and Varghese Jacob and Zhengrui
                 (Jeffrey) Jiang and Subodha Kumar",
  title =        "Introduction to {WITS 2015} Special Issue in {TMIS}",
  journal =      j-TMIS,
  volume =       "8",
  number =       "2--3",
  pages =        "4:1--4:??",
  month =        aug,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3108899",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Sep 16 11:43:33 MDT 2017",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "4e",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Deng:2017:RAS,
  author =       "Shuyuan Deng and Atish P. Sinha and Huimin Zhao",
  title =        "Resolving Ambiguity in Sentiment Classification: The
                 Role of Dependency Features",
  journal =      j-TMIS,
  volume =       "8",
  number =       "2--3",
  pages =        "4:1--4:??",
  month =        aug,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3046684",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Sep 16 11:43:33 MDT 2017",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Sentiment analysis has become popular in business
                 intelligence and analytics applications due to the
                 great need for learning insights from the vast amounts
                 of user generated content on the Internet. One major
                 challenge of sentiment analysis, like most text
                 classification tasks, is finding structures from
                 unstructured texts. Existing sentiment analysis
                 techniques employ the supervised learning approach and
                 the lexicon scoring approach, both of which largely
                 rely on the representation of a document as a
                 collection of words and phrases. The semantic ambiguity
                 (i.e., polysemy) of single words and the sparsity of
                 phrases negatively affect the robustness of sentiment
                 analysis, especially in the context of short social
                 media texts. In this study, we propose to represent
                 texts using dependency features. We test the
                 effectiveness of dependency features in supervised
                 sentiment classification. We compare our method with
                 the current standard practice using a labeled data set
                 containing 170,874 microblogging messages. The
                 combination of unigram features and dependency features
                 significantly outperformed other popular types of
                 features.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "4",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Al-Ramahi:2017:DDP,
  author =       "Mohammad A. Al-Ramahi and Jun Liu and Omar F.
                 El-Gayar",
  title =        "Discovering Design Principles for Health Behavioral
                 Change Support Systems: a Text Mining Approach",
  journal =      j-TMIS,
  volume =       "8",
  number =       "2--3",
  pages =        "5:1--5:??",
  month =        aug,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3055534",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Sep 16 11:43:33 MDT 2017",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Behavioral Change Support Systems (BCSSs) aim to
                 change users' behavior and lifestyle. These systems
                 have been gaining popularity with the proliferation of
                 wearable devices and recent advances in mobile
                 technologies. In this article, we extend the existing
                 literature by discovering design principles for health
                 BCSSs based on a systematic analysis of users'
                 feedback. Using mobile diabetes applications as an
                 example of Health BCSSs, we use topic modeling to
                 discover design principles from online user reviews. We
                 demonstrate the importance of the design principles
                 through analyzing their existence in users' complaints.
                 Overall, the results highlight the necessity of going
                 beyond the techno-centric approach used in current
                 practice and incorporating the social and
                 organizational features into persuasive systems design,
                 as well as integrating with medical devices and other
                 systems in their usage context.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "5",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Sun:2017:BCP,
  author =       "Can Sun and Yonghua Ji and Bora Kolfal and Ray
                 Patterson",
  title =        "Business-to-Consumer Platform Strategy: How Vendor
                 Certification Changes Platform and Seller Incentives",
  journal =      j-TMIS,
  volume =       "8",
  number =       "2--3",
  pages =        "6:1--6:??",
  month =        aug,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3057273",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Sep 16 11:43:33 MDT 2017",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "We build an economic model to study the problem of
                 offering a new, high-certainty channel on an existing
                 business-to-consumer platform such as Taobao and eBay.
                 On this new channel, the platform owner exerts effort
                 to reduce the uncertainty of service quality. Sellers
                 can either sell through the existing low-certainty
                 channel or go through additional screening to sell on
                 this new channel. We model the problem as a Bertrand
                 competition game where sellers compete on price and
                 exert effort to provide better service to consumers. In
                 this game, we consider a reputation spillover effect
                 that refers to the impact of the high-certainty channel
                 on the perceived service quality in the low-certainty
                 channel. Counter-intuitively, we find that
                 low-certainty channel demand will decrease as the
                 reputation spillover effect increases, in the case of
                 low inter-channel competition. Also, low-certainty
                 channel demand increases as the quality uncertainty
                 increases, in the case of intense inter-channel
                 competition. Furthermore, the platform owner should
                 offer a new high-certainty channel when (i) the
                 perceived quality for this channel is sufficiently
                 high, (ii) sellers in this channel are able to
                 efficiently provide quality service, (iii) consumers in
                 this channel are not so sensitive to the quality
                 uncertainty, or (iv) the reputation spillover effect is
                 high. In the one-channel case, the incentives of the
                 platform owner and sellers are aligned for all model
                 parameters. However, this is not the case for the
                 two-channel solution, and our model reveals where
                 tensions will arise between parties.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "6",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Bauman:2017:USS,
  author =       "Konstantin Bauman and Alexander Tuzhilin and Ryan
                 Zaczynski",
  title =        "Using Social Sensors for Detecting Emergency Events: a
                 Case of Power Outages in the Electrical Utility
                 Industry",
  journal =      j-TMIS,
  volume =       "8",
  number =       "2--3",
  pages =        "7:1--7:??",
  month =        aug,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3052931",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Sep 16 11:43:33 MDT 2017",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "This article presents a novel approach to detecting
                 emergency events, such as power outages, that utilizes
                 social media users as ``social sensors'' for virtual
                 detection of such events. The proposed new method is
                 based on the analysis of the Twitter data that leads to
                 the detection of Twitter discussions about these
                 emergency events. The method described in the article
                 was implemented and deployed by one of the vendors in
                 the context of detecting power outages as a part of
                 their comprehensive social engagement platform. It was
                 also field tested on Twitter users in an industrial
                 setting and performed well during these tests.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "7",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Mannino:2017:DES,
  author =       "Michael Mannino and Joel Fredrickson and Farnoush
                 Banaei-Kashani and Iris Linck and Raghda Alqurashi
                 Raghda",
  title =        "Development and Evaluation of a Similarity Measure for
                 Medical Event Sequences",
  journal =      j-TMIS,
  volume =       "8",
  number =       "2--3",
  pages =        "8:1--8:??",
  month =        aug,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3070684",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Sep 16 11:43:33 MDT 2017",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "We develop a similarity measure for medical event
                 sequences (MESs) and empirically evaluate it using U.S.
                 Medicare claims data. Existing similarity measures do
                 not use unique characteristics of MESs and have never
                 been evaluated on real MESs. Our similarity measure,
                 the Optimal Temporal Common Subsequence for Medical
                 Event Sequences (OTCS-MES), provides a matching
                 component that integrates event prevalence, event
                 duplication, and hierarchical coding, important
                 elements of MESs. The OTCS-MES also uses normalization
                 to mitigate the impact of heavy positive skew of
                 matching events and compact distribution of event
                 prevalence. We empirically evaluate the OTCS-MES
                 measure against two other measures specifically
                 designed for MESs, the original OTCS and Artemis, a
                 measure incorporating event alignment. Our evaluation
                 uses two substantial data sets of Medicare claims data
                 containing inpatient and outpatient sequences with
                 different medical event coding. We find a small overlap
                 in nearest neighbors among the three similarity
                 measures, demonstrating the superior design of the
                 OTCS-MES with its emphasis on unique aspects of MESs.
                 The evaluation also provides evidence about the impact
                 of component weights, neighborhood size, and sequence
                 length.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "8",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Taghavi:2017:RCF,
  author =       "Atefeh Taghavi and Carson Woo",
  title =        "The Role Clarity Framework to Improve Requirements
                 Gathering",
  journal =      j-TMIS,
  volume =       "8",
  number =       "2--3",
  pages =        "9:1--9:??",
  month =        aug,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3083726",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Sep 16 11:43:33 MDT 2017",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Incorrect and incomplete requirements have been
                 reported as two of the top reasons for information
                 systems (IS) project failures. In order to address
                 these concerns, several IS analysis and design studies
                 have focused on understanding the business needs and
                 organizational factors prior to specifying the
                 requirements. In this research, we add to the existing
                 incremental solutions, such as the work system method
                 and goal-oriented requirements engineering, by
                 proposing the Role Clarity Framework drawn from the
                 theories of ``role dynamics'' and ``goal setting and
                 task performance'' in organization studies. The Role
                 Clarity Framework consists of three main concepts
                 related to any organizational role: expectations,
                 activities, and consequences. Based on the interactions
                 among different roles, this framework demonstrates how
                 the business goals and activities of each role, as
                 played out by IS users, are formed and/or changed in
                 the organization. Finally, the Role Clarity Framework
                 helps IS analysts to improve their communication with
                 users and anticipate changes in their requirements,
                 thus improving the gathering of requirements for IS
                 design.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "9",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Mukherjee:2017:ARB,
  author =       "Anik Mukherjee and R. P. Sundarraj and Kaushik Dutta",
  title =        "Apriori Rule-Based In-App Ad Selection Online
                 Algorithm for Improving Supply-Side Platform Revenues",
  journal =      j-TMIS,
  volume =       "8",
  number =       "2--3",
  pages =        "10:1--10:??",
  month =        aug,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3086188",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Sep 16 11:43:33 MDT 2017",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Today, smartphone-based in-app advertisement forms a
                 substantial portion of the online advertising market.
                 In-app publishers go through ad-space aggregators known
                 as Supply-Side Platforms (SSPs), who, in turn, act as
                 intermediaries for ad-agency aggregators known as
                 demand-side platforms. The SSPs face the twin issue of
                 making ad placement decisions within an order of
                 milliseconds, even though their revenue streams can be
                 optimized only by a careful selection of ads that
                 elicit appropriate user responses regarding
                 impressions, clicks, and conversions. This article
                 considers the SSP's perspective and presents an online
                 algorithm that balances these two issues. Our
                 experimental results indicate that the decision-making
                 time generally ranges between 20 ms and 50 ms and
                 accuracy from 1\% to 10\%. Further, we conduct
                 statistical analysis comparing the theoretical
                 complexity of the online algorithm with its empirical
                 performance. Empirically, we observe that the time is
                 directly proportional to the number of incoming ads and
                 the number of online rules.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "10",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Ha:2017:PPE,
  author =       "Tuan Minh Ha and Masaki Samejima and Norihisa Komoda",
  title =        "Power and Performance Estimation for Fine-Grained
                 Server Power Capping via Controlling Heterogeneous
                 Applications",
  journal =      j-TMIS,
  volume =       "8",
  number =       "4",
  pages =        "11:1--11:??",
  month =        sep,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3086449",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Jan 22 17:26:40 MST 2018",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  abstract =     "Power capping is a method to save power consumption of
                 servers by limiting performance of the servers.
                 Although users frequently run applications on different
                 virtual machines (VMs) for keeping their performance
                 and having them isolated from the other applications,
                 power capping may degrade performance of all the
                 applications running on the server. We present
                 fine-grained power capping by limiting performance of
                 each application individually. For keeping performance
                 defined in Quality of Service (QoS) requirements, it is
                 important to estimate applications' performance and
                 power consumption after the fine-grained power capping
                 is applied. We propose the estimation method of
                 physical CPU usage when limiting virtual CPU usage of
                 applications on VMs. On servers where multiple VMs run,
                 VM's usage of physical CPU is interrupted by the other
                 VMs, and a hypervisor uses physical CPU to control VMs.
                 These VMs' and hypervisor's behaviors make it difficult
                 to estimate performance and power consumption by
                 straightforward methods, such as linear regression and
                 polynomial regression. The proposed method uses
                 Piecewise Linear Regression to estimate physical CPU
                 usage by assuming that VM's access to physical CPU is
                 not interrupted by the other VMs. Then we estimate how
                 much physical CPU usage is reduced by the interruption.
                 Because physical CPU usage is not stable soon after
                 limiting CPU usage, the proposed method estimates a
                 convergence value of CPU usage after many interruptions
                 are repeated.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "11",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Basole:2017:UAP,
  author =       "Rahul C. Basole and Timothy Major and Arjun
                 Srinivasan",
  title =        "Understanding Alliance Portfolios Using Visual
                 Analytics",
  journal =      j-TMIS,
  volume =       "8",
  number =       "4",
  pages =        "12:1--12:??",
  month =        sep,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3086308",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Jan 22 17:26:40 MST 2018",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "In an increasingly global and competitive business
                 landscape, firms must collaborate and partner with
                 others to ensure survival, growth, and innovation.
                 Understanding the evolutionary composition of a firm's
                 relationship portfolio and the underlying formation
                 strategy is a difficult task given the
                 multidimensional, temporal, and geospatial nature of
                 the data. In collaboration with senior executives, we
                 iteratively determine core design requirements and then
                 design and implement an interactive visualization
                 system that enables decision makers to gain both
                 systemic (macro) and detailed (micro) insights into a
                 firm's alliance activities and discover patterns of
                 multidimensional relationship formation. Our system
                 provides both sequential and temporal representation
                 modes, a rich set of additive cross-linked filters, the
                 ability to stack multiple alliance portfolios, and a
                 dynamically updated activity state model visualization
                 to inform decision makers of past and likely future
                 relationship moves. We illustrate our tool with
                 examples of alliance activities of firms listed on the
                 S8P 500. A controlled experiment and real-world
                 evaluation with practitioners and researchers reveals
                 significant evidence of the value of our visual
                 analytic tool. Our design study contributes to design
                 science by addressing a known problem (i.e., alliance
                 portfolio analysis) with a novel solution (interactive,
                 pixel-based multivariate visualization) and to the
                 rapidly emerging area of data-driven visual decision
                 support in corporate strategy contexts. We conclude
                 with implications and future research opportunities.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "12",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Cazier:2017:VCT,
  author =       "Joseph Cazier and Benjamin Shao and Robert
                 {St. Louis}",
  title =        "Value Congruence, Trust, and Their Effects on Purchase
                 Intention and Reservation Price",
  journal =      j-TMIS,
  volume =       "8",
  number =       "4",
  pages =        "13:1--13:??",
  month =        sep,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3110939",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Jan 22 17:26:40 MST 2018",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "We study the roles of value congruence and trust in
                 increasing online shoppers' intention to purchase goods
                 and their reservation prices for these goods.
                 Hypotheses are developed and a controlled experiment is
                 conducted to measure subjects' value congruence with
                 and their trust in online sellers with disparate
                 values, along with their purchase intention and
                 willingness to pay price premiums. Using social
                 exchange theory, we find that, for business-to-consumer
                 (B2C) e-commerce, value congruence increases consumer
                 online trust, and both value congruence and online
                 trust have direct effects on purchase intention and
                 reservation prices. In particular, in the positive
                 value congruence vs. value neutral case, trust has a
                 greater effect than value congruence on purchase
                 intention, but value congruence has a greater effect
                 than trust on reservation price. These findings suggest
                 that trust is essential to a consumer's intention to
                 purchase online but value congruence can induce price
                 premiums from potential buyers for online sellers. This
                 implies that trust is essential to B2C e-commerce, but
                 value congruence can be a more effective instrument for
                 online sellers to achieve competitive advantage through
                 value-based differentiation in the virtual
                 marketplace.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "13",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Lukyanenko:2017:ACC,
  author =       "Roman Lukyanenko and Binny M. Samuel",
  title =        "Are All Classes Created Equal? {Increasing} Precision
                 of Conceptual Modeling Grammars",
  journal =      j-TMIS,
  volume =       "8",
  number =       "4",
  pages =        "14:1--14:??",
  month =        sep,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3131780",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Jan 22 17:26:40 MST 2018",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Recent decade has seen a dramatic change in the
                 information systems landscape that alters the ways we
                 design and interact with information technologies,
                 including such developments as the rise of business
                 analytics, user-generated content, and NoSQL databases,
                 to name just a few. These changes challenge conceptual
                 modeling research to offer innovative solutions
                 tailored to these environments. Conceptual models
                 typically represent classes (categories, kinds) of
                 objects rather than concrete specific objects, making
                 the class construct a critical medium for capturing
                 domain semantics. While representation of classes may
                 differ between grammars, a common design assumption is
                 what we term different semantics same syntax (D3S).
                 Under D3S, all classes are depicted using the same
                 syntactic symbols. Following recent findings in
                 psychology, we introduce a novel assumption
                 semantics-contingent syntax (SCS) whereby syntactic
                 representations of classes in conceptual models may
                 differ based on their semantic meaning. We propose a
                 core SCS design principle and five guidelines pertinent
                 for conceptual modeling. We believe SCS carries
                 profound implications for theory and practice of
                 conceptual modeling as it seeks to better support
                 modern information environments.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "14",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Li:2018:SLR,
  author =       "Zhepeng (Lionel) Li and Xiao Fang and Olivia R. Liu
                 Sheng",
  title =        "A Survey of Link Recommendation for Social Networks:
                 Methods, Theoretical Foundations, and Future Research
                 Directions",
  journal =      j-TMIS,
  volume =       "9",
  number =       "1",
  pages =        "1:1--1:??",
  month =        feb,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3131782",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Mar 12 16:04:48 MDT 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Link recommendation has attracted significant
                 attention from both industry practitioners and academic
                 researchers. In industry, link recommendation has
                 become a standard and most important feature in online
                 social networks, prominent examples of which include
                 ``People You May Know'' on LinkedIn and ``You May
                 Know'' on Google+. In academia, link recommendation has
                 been and remains a highly active research area. This
                 article surveys state-of-the-art link recommendation
                 methods, which can be broadly categorized into
                 learning-based methods and proximity-based methods. We
                 further identify social and economic theories, such as
                 social interaction theory, that underlie these methods
                 and explain from a theoretical perspective why a link
                 recommendation method works. Finally, we propose to
                 extend link recommendation research in several
                 directions that include utility-based link
                 recommendation, diversity of link recommendation, link
                 recommendation from incomplete data, and experimental
                 study of link recommendation.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "1",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Xiao:2018:PSD,
  author =       "Keli Xiao and Qi Liu and Chuanren Liu and Hui Xiong",
  title =        "Price Shock Detection With an Influence-Based Model of
                 Social Attention",
  journal =      j-TMIS,
  volume =       "9",
  number =       "1",
  pages =        "2:1--2:??",
  month =        feb,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3131781",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Mar 12 16:04:48 MDT 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "There has been increasing interest in exploring the
                 impact of human behavior on financial market dynamics.
                 One of the important related questions is whether
                 attention from society can lead to significant stock
                 price movements or even abnormal returns. To answer the
                 question, we develop a new measurement of social
                 attention, named periodic cumulative degree of social
                 attention, by simultaneously considering the individual
                 influence and the information propagation in social
                 networks. Based on the vast social network data, we
                 evaluate the new attention measurement by testing its
                 significance in explaining future abnormal returns. In
                 addition, we test the forecasting ability of social
                 attention for stock price shocks, defined by the
                 cumulative abnormal returns. Our results provide
                 significant evidence to support the intercorrelated
                 relationship between the social attention and future
                 abnormal returns. The outperformance of the new
                 approach in predicting price shocks is also confirmed
                 by comparison with several benchmark methods.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "2",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Tuarob:2018:DDB,
  author =       "Suppawong Tuarob and Ray Strong and Anca Chandra and
                 Conrad S. Tucker",
  title =        "Discovering Discontinuity in Big Financial Transaction
                 Data",
  journal =      j-TMIS,
  volume =       "9",
  number =       "1",
  pages =        "3:1--3:??",
  month =        feb,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3159445",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Mar 12 16:04:48 MDT 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Business transactions are typically recorded in the
                 company ledger. The primary purpose of such financial
                 information is to accompany a monthly or quarterly
                 report for executives to make sound business decisions
                 and strategies for the next business period. These
                 business strategies often result in transitions that
                 cause underlying infrastructures and components to
                 change, including alteration in the nomenclature system
                 of the business components. As a result, a transaction
                 stream of an affected component would be replaced by
                 another stream with a different component name,
                 resulting in discontinuity of a financial stream of the
                 same component. Recently, advancement in large-scale
                 data mining technologies has enabled a set of critical
                 applications to utilize knowledge extracted from a vast
                 amount of existing data that would otherwise have been
                 unused or underutilized. In financial and services
                 computing domains, recent studies have illustrated that
                 historical financial data could be used to predict
                 future revenues and profits, optimizing costs, among
                 other potential applications. These prediction models
                 rely on long-term availability of the historical data
                 that traces back for multiple years. However, the
                 discontinuity of the financial transaction stream
                 associated with a business component has limited the
                 learning capability of the prediction models. In this
                 article, we propose a set of machine learning-based
                 algorithms to automatically discover component name
                 replacements, using information available in general
                 ledger databases. The algorithms are designed to be
                 scalable for handling massive data points, especially
                 in large companies. Furthermore, the proposed
                 algorithms are generalizable to other domains whose
                 data is time series and shares the same nature as the
                 financial data available in business ledgers. A case
                 study of real-world IBM service delivery retrieved from
                 four different geographical regions is used to validate
                 the efficacy of the proposed methodology.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "3",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Mendling:2018:BBP,
  author =       "Jan Mendling and Ingo Weber and Wil {Van Der Aalst}
                 and Jan {Vom Brocke and} Cristina Cabanillas and
                 Florian Daniel and S{\o}ren Debois and Claudio {Di
                 Ciccio} and Marlon Dumas and Schahram Dustdar and
                 Avigdor Gal and Luciano Garc{\'\i}a-Ba{\~n}uelos and
                 Guido Governatori and Richard Hull and Marcello {La
                 Rosa} and Henrik Leopold and Frank Leymann and Jan
                 Recker and Manfred Reichert and Hajo A. Reijers and
                 Stefanie Rinderle-Ma and Andreas Solti and Michael
                 Rosemann and Stefan Schulte and Munindar P. Singh and
                 Tijs Slaats and Mark Staples and Barbara Weber and
                 Matthias Weidlich and Mathias Weske and Xiwei Xu and
                 Liming Zhu",
  title =        "Blockchains for Business Process Management ---
                 Challenges and Opportunities",
  journal =      j-TMIS,
  volume =       "9",
  number =       "1",
  pages =        "4:1--4:??",
  month =        feb,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3183367",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Mar 12 16:04:48 MDT 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Blockchain technology offers a sizable promise to
                 rethink the way interorganizational business processes
                 are managed because of its potential to realize
                 execution without a central party serving as a single
                 point of trust (and failure). To stimulate research on
                 this promise and the limits thereof, in this article,
                 we outline the challenges and opportunities of
                 blockchain for business process management (BPM). We
                 first reflect how blockchains could be used in the
                 context of the established BPM lifecycle and second how
                 they might become relevant beyond. We conclude our
                 discourse with a summary of seven research directions
                 for investigating the application of blockchain
                 technology in the context of BPM.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "4",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Zimbra:2018:SAT,
  author =       "David Zimbra and Ahmed Abbasi and Daniel Zeng and
                 Hsinchun Chen",
  title =        "The State-of-the-Art in {Twitter} Sentiment Analysis:
                 a Review and Benchmark Evaluation",
  journal =      j-TMIS,
  volume =       "9",
  number =       "2",
  pages =        "5:1--5:??",
  month =        sep,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3185045",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Mar 12 16:04:48 MDT 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Twitter has emerged as a major social media platform
                 and generated great interest from sentiment analysis
                 researchers. Despite this attention, state-of-the-art
                 Twitter sentiment analysis approaches perform
                 relatively poorly with reported classification
                 accuracies often below 70\%, adversely impacting
                 applications of the derived sentiment information. In
                 this research, we investigate the unique challenges
                 presented by Twitter sentiment analysis and review the
                 literature to determine how the devised approaches have
                 addressed these challenges. To assess the
                 state-of-the-art in Twitter sentiment analysis, we
                 conduct a benchmark evaluation of 28 top academic and
                 commercial systems in tweet sentiment classification
                 across five distinctive data sets. We perform an error
                 analysis to uncover the causes of commonly occurring
                 classification errors. To further the evaluation, we
                 apply select systems in an event detection case study.
                 Finally, we summarize the key trends and takeaways from
                 the review and benchmark evaluation and provide
                 suggestions to guide the design of the next generation
                 of approaches.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "5",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Basole:2018:EDE,
  author =       "Rahul C. Basole and Arjun Srinivasan and Hyunwoo Park
                 and Shiv Patel",
  title =        "{\tt ecoxight}: Discovery, Exploration, and Analysis
                 of Business Ecosystems Using Interactive
                 Visualization",
  journal =      j-TMIS,
  volume =       "9",
  number =       "2",
  pages =        "6:1--6:??",
  month =        sep,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3185047",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Mar 12 16:04:48 MDT 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "The term ecosystem is used pervasively in industry,
                 government, and academia to describe the complex,
                 dynamic, hyperconnected nature of many social,
                 economic, and technical systems that exist today.
                 Ecosystems are characterized by a large, dynamic, and
                 heterogeneous set of geospatially distributed entities
                 that are interconnected through various types of
                 relationships. This study describes the design and
                 development of ecoxight, a Web-based visualization
                 platform that provides multiple coordinated views of
                 multipartite, multiattribute, dynamic, and geospatial
                 ecosystem data with novel and rich interaction
                 capabilities to augment decision makers ecosystem
                 intelligence. The design of ecoxight was informed by an
                 extensive multiphase field study of executives. The
                 ecoxight platform not only provides capabilities to
                 interactively explore and make sense of ecosystems but
                 also provides rich visual construction capabilities to
                 help decision makers align their mental model. We
                 demonstrate the usability, utility, and value of our
                 system using multiple evaluation studies with
                 practitioners using socially curated data on the
                 emerging application programming interface ecosystem.
                 We report on our findings and conclude with research
                 implications. Collectively, our study contributes to
                 design science research at the intersection of
                 information systems and strategy and the rapidly
                 emerging field of visual enterprise analytics.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "6",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Fan:2018:IES,
  author =       "Xiangyu Fan and Xi Niu",
  title =        "Implementing and Evaluating Serendipity in Delivering
                 Personalized Health Information",
  journal =      j-TMIS,
  volume =       "9",
  number =       "2",
  pages =        "7:1--7:??",
  month =        sep,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3205849",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Mar 12 16:04:48 MDT 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Serendipity has been recognized to have the potential
                 of enhancing unexpected information discovery. This
                 study shows that decomposing the concept of serendipity
                 into unexpectedness and interest is a useful way for
                 implementing this concept. Experts' domain knowledge
                 helps in providing serendipitous recommendation, which
                 can be further improved by adaptively incorporating
                 users' real-time feedback. This research also conducts
                 an empirical user-study to analyze the influence of
                 serendipity in a health news delivery context. A
                 personalized filtering system named MedSDFilter was
                 developed, on top of which serendipitous recommendation
                 was implemented using three approaches: random,
                 static-knowledge-based, and adaptive-knowledge-based
                 models. The three different models were compared. The
                 results indicate that the adaptive-knowledge-based
                 method has the highest ability in helping people
                 discover unexpected and interesting contents. The
                 insights of the research will make researchers and
                 practitioners rethink the way in which search engines
                 and recommender systems operate to address the
                 challenges of discovering unexpected and interesting
                 information. The outcome will have implications for
                 empowering ordinary people with more chances of bumping
                 into beneficial information.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "7",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Purao:2018:MLC,
  author =       "Sandeep Purao and Narasimha Bolloju and Chuan-Hoo
                 Tan",
  title =        "A Modeling Language for Conceptual Design of Systems
                 Integration Solutions",
  journal =      j-TMIS,
  volume =       "9",
  number =       "2",
  pages =        "8:1--8:??",
  month =        sep,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3185046",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Mar 12 16:04:48 MDT 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Systems integration-connecting software systems for
                 cross-functional work-is a significant concern in many
                 large organizations, which continue to maintain
                 hundreds, if not thousands, of independently evolving
                 software systems. Current approaches in this space
                 remain ad hoc, and closely tied to technology
                 platforms. Following a design science approach, and via
                 multiple design-evaluate cycles, we develop Systems
                 Integration Requirements Engineering Modeling Language
                 (SIRE-ML) to address this problem. SIRE-ML builds on
                 the foundation of coordination theory, and incorporates
                 important semantic information about the systems
                 integration domain. The article develops constructs in
                 SIRE-ML, and a merge algorithm that allows both
                 functional managers and integration professionals to
                 contribute to building a systems integration solution.
                 Integration models built with SIRE-ML provide benefits
                 such as ensuring coverage and minimizing ambiguity, and
                 can be used to drive implementation with different
                 platforms such as middleware, services, and distributed
                 objects. We evaluate SIRE-ML for ontological
                 expressiveness and report findings about applicability
                 check with an expert panel. The article discusses
                 implications for future research such as tool building
                 and empirical evaluation, as well as implications for
                 practice.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "8",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{De-Arteaga:2018:MLD,
  author =       "Maria De-Arteaga and William Herlands and Daniel B.
                 Neill and Artur Dubrawski",
  title =        "Machine Learning for the Developing World",
  journal =      j-TMIS,
  volume =       "9",
  number =       "2",
  pages =        "9:1--9:??",
  month =        sep,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3210548",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Mar 12 16:04:48 MDT 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  abstract =     "Researchers from across the social and computer
                 sciences are increasingly using machine learning to
                 study and address global development challenges. This
                 article examines the burgeoning field of machine
                 learning for the developing world (ML4D). First, we
                 present a review of prominent literature. Next, we
                 suggest best practices drawn from the literature for
                 ensuring that ML4D projects are relevant to the
                 advancement of development objectives. Finally, we
                 discuss how developing world challenges can motivate
                 the design of novel machine learning methodologies.
                 This article provides insights into systematic
                 differences between ML4D and more traditional machine
                 learning applications. It also discusses how technical
                 complications of ML4D can be treated as novel research
                 questions, how ML4D can motivate new research
                 directions, and where machine learning can be most
                 useful.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "9",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Ketter:2018:ISS,
  author =       "Wolfgang Ketter and John Collins and Maytal
                 Saar-Tsechansky and Ori Marom",
  title =        "Information Systems for a Smart Electricity Grid:
                 Emerging Challenges and Opportunities",
  journal =      j-TMIS,
  volume =       "9",
  number =       "3",
  pages =        "10:1--10:??",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3230712",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Mar 12 16:04:49 MDT 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3230712",
  abstract =     "The drive for sustainability as evidenced by the Paris
                 Accords is forcing a radical re-examination of the way
                 electricity is produced, managed, and consumed.
                 Research on sustainable smart electricity markets is
                 facilitating the emergence of sustainable energy
                 systems and a revolution in the efficiency and
                 reliability of electricity consumption, production, and
                 distribution. Traditional electricity grids and markets
                 are being disrupted by a range of forces, including the
                 rise of weather-dependent and distributed renewable
                 sources, growing consumer involvement in managing their
                 power consumption and production, and the
                 electrification of transport. These changes will likely
                 bring about complex and dynamic smart electricity
                 markets that rely on analysis of information to inform
                 stakeholders, and on effective integration of
                 stakeholders' actions. We outline a research agenda on
                 how advances in information-intensive processes are
                 fundamental for facilitating these transformations,
                 describe the roles that such processes will play, and
                 discuss Information Systems research challenges
                 necessary to achieve these goals. These challenges span
                 public policy, privacy, and security; market
                 mechanisms; and data-driven decision support. The
                 diverse challenges we outline also underscore that the
                 diverse IS research perspective is instrumental for
                 addressing the complexity and interdisciplinary nature
                 of this research.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "10",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Russo:2018:MMI,
  author =       "Daniel Russo and Paolo Ciancarini and Tommaso
                 Falasconi and Massimo Tomasi",
  title =        "A Meta-Model for Information Systems Quality: a Mixed
                 Study of the Financial Sector",
  journal =      j-TMIS,
  volume =       "9",
  number =       "3",
  pages =        "11:1--11:??",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3230713",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Mar 12 16:04:49 MDT 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3230713",
  abstract =     "Information Systems Quality (ISQ) is a critical source
                 of competitive advantages for organizations. In a
                 scenario of increasing competition on digital services,
                 ISQ is a competitive differentiation asset. In this
                 regard, managing, maintaining, and evolving IT
                 infrastructures have become a primary concern of
                 organizations. Thus, a technical perspective on ISQ
                 provides useful guidance to meet current challenges.
                 The financial sector is paradigmatic, since it is a
                 traditional business, with highly complex
                 business-critical legacy systems, facing a tremendous
                 change due to market and regulation drivers. We carried
                 out a Mixed-Methods study, performing a Delphi-like
                 study on the financial sector. We developed a specific
                 research framework to pursue this vertical study. Data
                 were collected in four phases starting with a
                 high-level randomly stratified panel of 13 senior
                 managers and then a target panel of 124 carefully
                 selected and well-informed domain experts. We have
                 identified and dealt with several quality factors; they
                 were discussed in a comprehensive model inspired by the
                 ISO 25010, 42010, and 12207 standards, corresponding to
                 software quality, software architecture, and software
                 process, respectively. Our results suggest that the
                 relationship among quality, architecture, and process
                 is a valuable technical perspective to explain the
                 quality of an information system. Thus, we introduce
                 and illustrate a novel meta-model, named SQuAP
                 (Software Quality, Architecture, Process), which is
                 intended to give a comprehensive picture of ISQ by
                 abstracting and connecting detailed individual ISO
                 models.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "11",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Zhu:2018:PJF,
  author =       "Chen Zhu and Hengshu Zhu and Hui Xiong and Chao Ma and
                 Fang Xie and Pengliang Ding and Pan Li",
  title =        "Person-Job Fit: Adapting the Right Talent for the
                 Right Job with Joint Representation Learning",
  journal =      j-TMIS,
  volume =       "9",
  number =       "3",
  pages =        "12:1--12:??",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3234465",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Mar 12 16:04:49 MDT 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3234465",
  abstract =     "Person-Job Fit is the process of matching the right
                 talent for the right job by identifying talent
                 competencies that are required for the job. While many
                 qualitative efforts have been made in related fields,
                 it still lacks quantitative ways of measuring talent
                 competencies as well as the job's talent requirements.
                 To this end, in this article, we propose a novel
                 end-to-end data-driven model based on a Convolutional
                 Neural Network (CNN), namely, the Person-Job Fit Neural
                 Network (PJFNN), for matching a talent qualification to
                 the requirements of a job. To be specific, PJFNN is a
                 bipartite neural network that can effectively learn the
                 joint representation of Person-Job fitness from
                 historical job applications. In particular, due to the
                 design of a hierarchical representation structure,
                 PJFNN can not only estimate whether a candidate fits a
                 job but also identify which specific requirement items
                 in the job posting are satisfied by the candidate by
                 measuring the distances between corresponding latent
                 representations. Finally, the extensive experiments on
                 a large-scale real-world dataset clearly validate the
                 performance of PJFNN in terms of Person-Job Fit
                 prediction. Also, we provide effective data
                 visualization to show some job and talent benchmark
                 insights obtained by PJFNN.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "12",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Delano:2018:SDT,
  author =       "John D. Delano and Hemant K. Jain and Atish P. Sinha",
  title =        "System Design through the Exploration of Contemporary
                 {Web} Services",
  journal =      j-TMIS,
  volume =       "9",
  number =       "3",
  pages =        "13:1--13:??",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3273932",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Mar 12 16:04:49 MDT 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3273932",
  abstract =     "In this article, we develop a Contemporary Web Service
                 (CWS) repository of system designs, which are encoded
                 as metadata of contemporary web services. We examine if
                 this CWS repository serves as an effective design tool
                 for initial CWS design and as an effective support tool
                 for business users and analysts working together on
                 system design. The CWS repository reduces the cognitive
                 load of both the analyst and the business user as they
                 jointly explore the CWS repository of system designs.
                 It supports an evolutionary approach to system design
                 through rapid selection of appropriate CWS metadata. To
                 accomplish that, we introduce several new design
                 characteristics for the CWS repository. The evaluation
                 results demonstrate that the CWS repository is an
                 effective tool for supporting designers during initial
                 service design, as well as for supporting business
                 users and analysts during system design.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "13",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Lo:2019:PWT,
  author =       "Kar Kei Lo and Michael Chau",
  title =        "A Penny Is Worth a Thousand? {Investigating} the
                 Relationship Between Social Media and Penny Stocks",
  journal =      j-TMIS,
  volume =       "9",
  number =       "4",
  pages =        "14:1--14:??",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3309704",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Mar 12 16:04:49 MDT 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3309704",
  abstract =     "Increasingly more investors are seeking information
                 from social media to help make investment decisions.
                 Considering that information on penny stocks is often
                 less reported in traditional media, investors may rely
                 more on social media to obtain such information for
                 investment advice. Although previous research has shown
                 that stock opinions in traditional media is a possible
                 predictor of stock returns, no previous research has
                 considered the effect of the stock opinions in social
                 media on these stocks in terms of future stock
                 performance and the moderation effect of penny stocks.
                 In this research, we studied the relationship between
                 social media and the financial performance of penny
                 stocks. We used the net proportion of positive words in
                 stock articles in social media to help predict the
                 future stock performance for penny stocks. The
                 moderation effect of penny stocks on the net fraction
                 of positive words was found to be significant in short
                 terms, revealing a stronger relationship between social
                 media and stock performance at lower price and market
                 capitalization (MC) levels. Based on the findings, we
                 proposed simple strategies utilizing social media and
                 our measure. The results of our applications will be of
                 interest to individual and institutional investors,
                 shareholders, and regulators.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "14",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Kratzwald:2019:PQA,
  author =       "Bernhard Kratzwald and Stefan Feuerriegel",
  title =        "Putting Question-Answering Systems into Practice:
                 Transfer Learning for Efficient Domain Customization",
  journal =      j-TMIS,
  volume =       "9",
  number =       "4",
  pages =        "15:1--15:??",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3309706",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Mar 12 16:04:49 MDT 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3309706",
  abstract =     "Traditional information retrieval (such as that
                 offered by web search engines) impedes users with
                 information overload from extensive result pages and
                 the need to manually locate the desired information
                 therein. Conversely, question-answering systems change
                 how humans interact with information systems: users can
                 now ask specific questions and obtain a tailored
                 answer-both conveniently in natural language. Despite
                 obvious benefits, their use is often limited to an
                 academic context, largely because of expensive domain
                 customizations, which means that the performance in
                 domain-specific applications often fails to meet
                 expectations. This article proposes cost-efficient
                 remedies: (i) we leverage metadata through a filtering
                 mechanism, which increases the precision of document
                 retrieval, and (ii) we develop a novel
                 fuse-and-oversample approach for transfer learning to
                 improve the performance of answer extraction. Here,
                 knowledge is inductively transferred from related, yet
                 different, tasks to the domain-specific application,
                 while accounting for potential differences in the
                 sample sizes across both tasks. The resulting
                 performance is demonstrated with actual use cases from
                 a finance company and the film industry, where fewer
                 than 400 question-answer pairs had to be annotated to
                 yield significant performance gains. As a direct
                 implication to management, this presents a promising
                 path to better leveraging of knowledge stored in
                 information systems.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "15",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Yu:2019:EAC,
  author =       "Shuo Yu and Hongyi Zhu and Shan Jiang and Yong Zhang
                 and Chunxiao Xing and Hsinchun Chen",
  title =        "Emoticon Analysis for {Chinese} Social Media and
                 E-commerce: The {AZEmo} System",
  journal =      j-TMIS,
  volume =       "9",
  number =       "4",
  pages =        "16:1--16:??",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3309707",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Mar 12 16:04:49 MDT 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3309707",
  abstract =     "This article presents a novel system, AZEmo, which
                 extracts and classifies emoticons from the ever-growing
                 critical Chinese social media and E-commerce. An
                 emoticon is a meta-communicative pictorial
                 representation of facial expressions, which helps to
                 describe the sender's emotional state. To complement
                 non-verbal communication, emoticons are frequently used
                 in social media websites. However, limited research has
                 been done to effectively analyze the affects of
                 emoticons in a Chinese context. In this study, we
                 developed an emoticon analysis system to extract
                 emoticons from Chinese text and classify them into one
                 of seven affect categories. The system is based on a
                 kinesics model that divides emoticons into semantic
                 areas (eyes, mouths, etc.), with improvements for
                 adaptation in the Chinese context. Machine-learning
                 methods were developed based on feature vector
                 extraction of emoticons. Empirical tests were conducted
                 to evaluate the effectiveness of the proposed system in
                 extracting and classifying emoticons, based on corpora
                 from a video sharing website and an E-commerce website.
                 Results showed the effectiveness of the system in
                 detecting and extracting emoticons from text and in
                 interpreting the affects conveyed by emoticons.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "16",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Hartono:2019:WVD,
  author =       "Edward Hartono and Clyde W. Holsapple",
  title =        "{Website} Visual Design Qualities: a Threefold
                 Framework",
  journal =      j-TMIS,
  volume =       "10",
  number =       "1",
  pages =        "1:1--1:??",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3309708",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Nov 29 07:31:35 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3309708",
  abstract =     "The present study aims to contribute to the
                 information systems (IS) literature by developing a new
                 theoretical perspective that integrates three
                 dimensions of artifact visual design quality-namely
                 aesthetic, functional, and symbolic dimensions-in the
                 investigation of website visual design qualities that
                 influence visitors' attitudes and behaviors. Results
                 suggest that website aesthetic, functional, and
                 symbolic qualities positively influence intention to
                 use the website and positive word of mouth and that
                 website aesthetic quality positively influences website
                 functional and symbolic qualities. Results also
                 demonstrate that functional and symbolic qualities
                 mediate the relationships between aesthetic quality and
                 intention to use and positive word of mouth.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "1",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Xiong:2019:FES,
  author =       "Hu Xiong and Yi Wang and Wenchao Li and Chien-Ming
                 Chen",
  title =        "Flexible, Efficient, and Secure Access Delegation in
                 Cloud Computing",
  journal =      j-TMIS,
  volume =       "10",
  number =       "1",
  pages =        "2:1--2:??",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3318212",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Nov 29 07:31:35 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3318212",
  abstract =     "The convenience of the cloud-assisted Internet of
                 Things has led to the need for improved protections for
                 the large volumes of data collected from devices around
                 the world and stored on cloud-based servers. Proxy
                 re-encryption (PRE) has been presented as a suitable
                 mechanism for secure transmission and sharing of files
                 within the cloud. However, existing PRE schemes do not
                 support unidirectional data transformation,
                 fine-grained controls, multiple hops, and
                 identity-based encryption simultaneously. To solve
                 these problems, we propose a unidirectional multi-hop
                 identity based-conditional PRE scheme that meets all of
                 the above requirements. Our proposal has the additional
                 benefits of a constant ciphertext size,
                 non-interactivity, and collusion resistance. We also
                 prove that our scheme is secure against adaptive
                 identity chosen-ciphertext attacks in the standard
                 model.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "2",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Mohammadi:2019:SAB,
  author =       "Majid Mohammadi and Wout Hofman and Yao-Hua Tan",
  title =        "Simulated Annealing-based Ontology Matching",
  journal =      j-TMIS,
  volume =       "10",
  number =       "1",
  pages =        "3:1--3:??",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3314948",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Nov 29 07:31:35 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3314948",
  abstract =     "Ontology alignment is a fundamental task to reconcile
                 the heterogeneity among various information systems
                 using distinct information sources. The evolutionary
                 algorithms (EAs) have been already considered as the
                 primary strategy to develop an ontology alignment
                 system. However, such systems have two significant
                 drawbacks: they either need a ground truth that is
                 often unavailable, or they utilize the population-based
                 EAs in a way that they require massive computation and
                 memory. This article presents a new ontology alignment
                 system, called SANOM, which uses the well-known
                 simulated annealing as the principal technique to find
                 the mappings between two given ontologies while no
                 ground truth is available. In contrast to
                 population-based EAs, the simulated annealing need not
                 generate populations, which makes it significantly
                 swift and memory-efficient for the ontology alignment
                 problem. This article models the ontology alignment
                 problem as optimizing the fitness of a state whose
                 optimum is obtained by using the simulated annealing. A
                 complex fitness function is developed that takes
                 advantage of various similarity metrics including
                 string, linguistic, and structural similarities. A
                 randomized warm initialization is specially tailored
                 for the simulated annealing to expedite its
                 convergence. The experiments illustrate that SANOM is
                 competitive with the state-of-the-art and is
                 significantly superior to other EA-based systems.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "3",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Emami:2019:GBA,
  author =       "Hojjat Emami",
  title =        "A Graph-based Approach to Person Name Disambiguation
                 in {Web}",
  journal =      j-TMIS,
  volume =       "10",
  number =       "2",
  pages =        "4:1--4:??",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3314949",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Nov 29 07:32:09 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3314949",
  abstract =     "This article presents a name disambiguation approach
                 to resolve ambiguities between person names and group
                 web pages according to the individuals they refer to.
                 The proposed approach exploits two important sources of
                 entity-centric semantic information extracted from web
                 pages, including personal attributes and social
                 relationships. It takes as input the web pages that are
                 results for a person name search. The web pages are
                 analyzed to extract personal attributes and social
                 relationships. The personal attributes and social
                 relationships are mapped into an undirected weighted
                 graph, called attribute-relationship graph. A
                 graph-based clustering algorithm is proposed to group
                 the nodes representing the web pages, each of which
                 refers to a person entity. The outcome is a set of
                 clusters such that the web pages within each cluster
                 refer to the same person. We show the effectiveness of
                 our approach by evaluating it on large-scale datasets
                 WePS-1, WePS-2, and WePS-3. Experimental results are
                 encouraging and show that the proposed method clearly
                 outperforms several baseline methods and also its
                 counterparts.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "4",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Jiang:2019:MAI,
  author =       "Jian-Min Jiang and Zhong Hong and Yangyang Chen",
  title =        "Modeling and Analyzing Incremental Natures of
                 Developing Software",
  journal =      j-TMIS,
  volume =       "10",
  number =       "2",
  pages =        "5:1--5:??",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3333535",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Nov 29 07:32:09 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3333535",
  abstract =     "The basic premise of iterative and evolutionary
                 project management is that a project is divided into
                 early, frequent, and short duration delivery steps.
                 Each step attempts to deliver some real value to
                 stakeholders. The increment size and iteration length
                 usually depend on profitability, finance, deadline, and
                 so on, rather than the functionality of a developing
                 system. It is difficult to guarantee the correctness in
                 every iteration step. In this article, we propose a
                 method of ensuring the correctness of iterative design
                 in terms of deadlock-freedom of the behavior of
                 software. The method first obtains the correct
                 (deadlock-free) atomic subsystems of a system using a
                 decomposition approach. In the iterative development
                 process, the method then requires that one atomic
                 subsystem or the composition of multiple atomic
                 subsystems should be regarded as one increment. Every
                 increment is naturally correct and can be completely
                 independently developed, independently deployed, and
                 independently maintained. The currently released system
                 in each iteration step is naturally guaranteed to be
                 correct. It is not necessary for developers to consider
                 the composition of the increment and the previously
                 released system may cause flaws and errors. We also
                 discuss the approach for ensuring correctness when
                 design modifications are made in an iteration step.
                 Finally, we explore the automatic decomposition of a
                 system into multiple atomic subsystems and present the
                 corresponding algorithm. A case demonstrates these
                 results.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "5",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Jain:2019:ISS,
  author =       "Hemant Jain and T. S. Raghu and Victoria Yoon and Wei
                 Thoo Yue",
  title =        "Introduction to Special Section Based on Papers
                 Presented at the {Workshop on Information Technology
                 and Systems, 2017}",
  journal =      j-TMIS,
  volume =       "10",
  number =       "2",
  pages =        "6:1--6:??",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3342557",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Nov 29 07:32:09 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3342557",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "6e",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Sutterer:2019:TBP,
  author =       "Paul Sutterer and Stefan Waldherr and Martin Bichler",
  title =        "Are Truthful Bidders Paying too Much? {Efficiency} and
                 Revenue in Display Ad Auctions",
  journal =      j-TMIS,
  volume =       "10",
  number =       "2",
  pages =        "6:1--6:??",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3325523",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Nov 29 07:32:09 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3325523",
  abstract =     "Display ad auctions have become the predominant means
                 to allocate user impressions on a website to
                 advertisers. These auctions are conducted in
                 milliseconds online, whenever a user visits a website.
                 The impressions are typically priced via a simple
                 second-price rule. For single-item auctions, this
                 Vickrey payment rule is known to be
                 incentive-compatible. However, it is unclear whether
                 bidders should still bid truthful in an online auction
                 where impressions (or items) arrive dynamically over
                 time and their valuations are not separable, as is the
                 case with campaign targets or budgets. The allocation
                 process might not maximize welfare and the payments can
                 differ substantially from those paid in an offline
                 auction with a Vickrey-Clarke-Groves (VCG) payment rule
                 or also competitive equilibrium prices. We study the
                 properties of the offline problem and model it as a
                 mathematical program. In numerical experiments, we find
                 that the welfare achieved in the online auction process
                 with truthful bidders is high compared to the
                 theoretical worst-case efficiency, but that the bidders
                 pay significantly more on average compared to what they
                 would need to pay in a corresponding offline auction in
                 thin markets with up to four bidders. However,
                 incentives for bid shading in these second-price
                 auctions decrease quickly with additional competition
                 and bidders risk losing.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "6",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Han:2019:CTR,
  author =       "Xu Han and Niam Yaraghi and Ram Gopal",
  title =        "Catching Them Red-Handed: Optimizing the Nursing
                 Homes' Rating System",
  journal =      j-TMIS,
  volume =       "10",
  number =       "2",
  pages =        "7:1--7:??",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3325522",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Nov 29 07:32:09 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3325522",
  abstract =     "The Centers for Medicare 8 Medicaid Services (CMS)
                 launched its nursing home rating system in 2008, which
                 has been widely used among patients, doctors, and
                 insurance companies since then. The system rates
                 nursing homes based on a combination of CMS's
                 inspection results and nursing homes' self-reported
                 measures. Prior research has shown that the rating
                 system is subject to inflation in the self-reporting
                 procedure, leading to biased overall ratings. Given the
                 limited resources CMS has, it is important to optimize
                 the inspection process and develop an effective audit
                 process to detect and deter inflation. We first examine
                 if the domain that CMS currently inspects is the best
                 choice in terms of minimizing the population of nursing
                 homes that can inflate and minimizing the difficulty of
                 detecting such inflators. To do this, we formulate the
                 problem mathematically and test the model by using
                 publicly available CMS data on nursing home ratings. We
                 show that CMS's current choice of inspection domain is
                 not optimal if it intends to minimize the number of
                 nursing homes that can inflate their reports, and CMS
                 will be better off if it inspects the staffing domain
                 instead. We also show that CMS's current choice of
                 inspection domain is only optimal had there been an
                 audit system in place to complement it. We then design
                 an audit system for CMS which will be coupled with its
                 current inspection strategy to either minimize the
                 initial budget required to conduct the audits or to
                 maximize the efficiency of the audit process. To design
                 the audit system, we consider nursing homes' reactions
                 to different audit policies, and conduct a detailed
                 simulation study on the optimal audit parameter
                 settings. Our result suggests that CMS should use a
                 moderate audit policy in order to carefully balance the
                 tradeoff between audit net budget and audit
                 efficiency.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "7",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Kartal:2019:DPV,
  author =       "Hasan B. Kartal and Xiaoping Liu and Xiao-Bai Li",
  title =        "Differential Privacy for the Vast Majority",
  journal =      j-TMIS,
  volume =       "10",
  number =       "2",
  pages =        "8:1--8:??",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3329717",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Nov 29 07:32:09 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3329717",
  abstract =     "Differential privacy has become one of the widely used
                 mechanisms for protecting sensitive information in
                 databases and information systems. Although
                 differential privacy provides a clear measure of
                 privacy guarantee, it implicitly assumes that each
                 individual corresponds to a single record in the result
                 of a database query. This assumption may not hold in
                 many database query applications. When an individual
                 has multiple records, strict implementation of
                 differential privacy may cause significant information
                 loss. In this study, we extend the differential privacy
                 principle to situations where multiple records in a
                 database are associated with the same individual. We
                 propose a new privacy principle that integrates
                 differential privacy with the Pareto principle in
                 analyzing privacy risk and data utility. When applied
                 to the situations with multiple records per person, the
                 proposed approach can significantly reduce the
                 information loss in the released query results with a
                 relatively small relaxation in the differential privacy
                 guarantee. The effectiveness of the proposed approach
                 is evaluated using three real-world databases.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "8",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Pal:2019:REC,
  author =       "Ranjan Pal and Leana Golubchik and Konstantions
                 Psounis and Tathagata Bandyopadhyay",
  title =        "On Robust Estimates of Correlated Risk in
                 Cyber-Insured {IT} Firms: a First Look at Optimal
                 {AI}-Based Estimates under ``Small'' Data",
  journal =      j-TMIS,
  volume =       "10",
  number =       "3",
  pages =        "9:1--9:??",
  month =        nov,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3351158",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Nov 29 07:28:37 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3351158",
  abstract =     "In this article, we comment on the drawbacks of the
                 existing AI-based Bayesian network (BN)
                 cyber-vulnerability analysis (C-VA) model proposed in
                 Mukhopadhyay et al. (2013) to assess cyber-risk in IT
                 firms, where this quantity is usually a joint
                 distribution of multiple risk (random) variables (e.g.,
                 quality of antivirus, frequency of monitoring, etc.)
                 coming from heterogeneous distribution families. As a
                 major modeling drawback, Mukhopadhyay et al. (2013)
                 assume that any pair of random variables in the BN are
                 linearly correlated with each other. This simplistic
                 assumption might not always hold true for general IT
                 organizational environments. Thus, the use of the C-VA
                 model in general will result in loose estimates of
                 correlated IT risk and will subsequently affect
                 cyber-insurance companies in framing profitable
                 coverage policies for IT organizations. To this end, we
                 propose methods to (1) find a closed-form expression
                 for the maximal correlation arising between pairs of
                 discrete random variables, whose value finds importance
                 in getting robust estimates of copula-induced
                 computations of organizational cyber-risk, and (2)
                 arrive at a computationally effective mechanism to
                 compute nonlinear correlations among pairs of discrete
                 random variables in the correlation matrix of the CBBN
                 model (Mukhopadhyay et al. 2013). We also prove that an
                 empirical computation of MC using our method converges
                 rapidly, that is, exponentially fast, to the true
                 correlation value in the number of samples. Our
                 proposed method contributes to a tighter estimate of IT
                 cyber-risk under environments of low-risk data
                 availability and will enable insurers to better assess
                 organizational risks and subsequently underwrite
                 profitable cyber-insurance policies.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "9",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Zo:2019:SOA,
  author =       "Hangjung Zo and Derek L. Nazareth and Hemant K. Jain",
  title =        "Service-oriented Application Composition with
                 Evolutionary Heuristics and Multiple Criteria",
  journal =      j-TMIS,
  volume =       "10",
  number =       "3",
  pages =        "10:1--10:??",
  month =        nov,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3354288",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Nov 29 07:28:37 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3354288",
  abstract =     "The need to create and deploy business application
                 systems rapidly has sparked interest in using web
                 services to compose them. When creating
                 mission-critical business applications through web
                 service compositions, in addition to ensuring that
                 functional requirements are met, designers need to
                 consider the end-to-end reliability, security,
                 performance, and overall cost of the application. As
                 the number of available coarse-grain business services
                 grows, the problem of selecting appropriate services
                 quickly becomes combinatorially explosive for
                 realistic-sized business applications. This article
                 develops a business-process-driven approach for
                 composing service-oriented applications. We use a
                 combination of weights to explore the entire QoS
                 criteria landscape through the use of a multi-criteria
                 genetic algorithm (GA) to identify a Pareto-optimal
                 multidimensional frontier that permits managers to
                 trade off conflicting objectives when selecting a set
                 of services. We illustrate the effectiveness of the
                 approach by applying it to a real-world drop-ship
                 business application and compare its performance to
                 another GA-based approach for service composition.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "10",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Lai:2019:TVK,
  author =       "Jianwei Lai and Dongsong Zhang and Sen Wang and Isil
                 Doga Yakut Kilic and Lina Zhou",
  title =        "{ThumbStroke}: a Virtual Keyboard in Support of
                 Sight-Free and One-Handed Text Entry on Touchscreen
                 Mobile Devices",
  journal =      j-TMIS,
  volume =       "10",
  number =       "3",
  pages =        "11:1--11:??",
  month =        nov,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3343858",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Nov 29 07:28:37 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3343858",
  abstract =     "The QWERTY keyboard on mobile devices usually requires
                 users' full visual attention and both hands, which is
                 not always possible. We propose a thumb-stroke-based
                 keyboard, ThumbStroke, to support both sight-free and
                 one-handed text entry. Text entry via ThumbStroke
                 completely relies on the directions of thumb strokes at
                 any place on the screen of a mobile device. It does not
                 require physical press on any specific keys, thus
                 eliminating the need for visual attention and reducing
                 errors due to tiny key size, fat thumbs, limited thumb
                 reachability, and visual occlusion. We empirically
                 evaluated ThumbStroke through a 20-session longitudinal
                 controlled lab experiment. ThumbStroke shows advantages
                 in typing accuracy and user perceptions in comparison
                 to the Escape and QWERTY keyboards and results in
                 faster typing speed than QWERTY in sight-free and
                 one-handed text entry. This study provides novel
                 research contributions to mobile HCI, advancing the
                 design of soft keyboards for one-handed interaction
                 with mobile devices and mobile accessibility.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "11",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Kang:2019:HAO,
  author =       "Yin Kang and Lina Zhou",
  title =        "Helpfulness Assessment of Online Reviews: The Role of
                 Semantic Hierarchy of Product Features",
  journal =      j-TMIS,
  volume =       "10",
  number =       "3",
  pages =        "12:1--12:??",
  month =        nov,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3365538",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Nov 29 07:28:37 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3365538",
  abstract =     "Effective use of online consumer reviews is hampered
                 by uncertainty about their helpfulness. Despite a
                 growing body of knowledge on indicators of review
                 helpfulness, previous studies have overlooked rich
                 semantic information embedded in review content.
                 Following design science principles, this study
                 introduces a semantic hierarchy of product features by
                 probing the review text. Using the hierarchical
                 framework as a guide, we develop a research model of
                 review helpfulness assessment. In the model, we propose
                 and conceptualize three new factors-breadth, depth, and
                 redundancy, by building on and/or extending product
                 uncertainty, information quality, signaling, and
                 encoding variability theories. The model-testing
                 results lend strong support to the proposed effects of
                 those factors on review helpfulness. They also reveal
                 interesting differences in the effects of redundancy
                 and readability between different types of products.
                 This study embodies knowledge moments of multiple
                 genres of inquiry in design science research, which
                 have multifold research and practical implications.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "12",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Park:2019:ECR,
  author =       "Jiyong Park and Daegon Cho and Jae Kyu Lee and
                 Byungtae Lee",
  title =        "The Economics of Cybercrime: The Role of Broadband and
                 Socioeconomic Status",
  journal =      j-TMIS,
  volume =       "10",
  number =       "4",
  pages =        "13:1--13:??",
  month =        dec,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3351159",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Dec 20 07:16:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3351159",
  abstract =     "Under what conditions is the Internet more likely to
                 be used maliciously for criminal activity? This study
                 examines the conditions under which the Internet is
                 associated with cybercriminal offenses. Using
                 comprehensive state-level data in the United States
                 during 2004--2010, our findings show that there is no
                 clear empirical evidence that the Internet penetration
                 rate is related to the number of Internet crime
                 perpetrators; however, cybercriminal activities are
                 contingent upon socioeconomic factors and connection
                 speed. Specifically, a higher income, more education, a
                 lower poverty rate, and a higher inequality are likely
                 to make the Internet penetration be more positively
                 related with cybercrime perpetrators, which are indeed
                 different from the conditions of terrestrial crime in
                 the real world. In addition, as opposed to narrowband,
                 the broadband connections are significantly and
                 positively associated with the number of Internet crime
                 perpetrators, and it amplifies the aforementioned
                 moderating effects of socioeconomic status on Internet
                 crime offenses. Taken together, cybercrime requires
                 more than just a skilled perpetrator, and it requires
                 an infrastructure to facilitate profiteering from the
                 act.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "13",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Chung:2019:IMD,
  author =       "Wingyan Chung and Bingbing Rao and Liqiang Wang",
  title =        "Interaction Models for Detecting Nodal Activities in
                 Temporal Social Media Networks",
  journal =      j-TMIS,
  volume =       "10",
  number =       "4",
  pages =        "14:1--14:??",
  month =        dec,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3365537",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Dec 20 07:16:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3365537",
  abstract =     "Detecting nodal activities in dynamic social networks
                 has strategic importance in many applications, such as
                 online marketing campaigns and homeland security
                 surveillance. How peer-to-peer exchanges in social
                 media can facilitate nodal activity detection is not
                 well explored. Existing models assume network nodes to
                 be static in time and do not adequately consider
                 features from social theories. This research developed
                 and validated two theory-based models, Random
                 Interaction Model (RIM) and Preferential Interaction
                 Model (PIM), to characterize temporal nodal activities
                 in social media networks of human agents. The models
                 capture the network characteristics of randomness and
                 preferential interaction due to community size, human
                 bias, declining connection cost, and rising
                 reachability. The models were compared against three
                 benchmark models (abbreviated as EAM, TAM, and DBMM)
                 using a social media community consisting of 790,462
                 users who posted over 3,286,473 tweets and formed more
                 than 3,055,797 links during 2013-2015. The experimental
                 results show that both RIM and PIM outperformed EAM and
                 TAM significantly in accuracy across different dates
                 and time windows. Both PIM and RIM scored significantly
                 smaller errors than DBMM did. Structural properties of
                 social networks were found to provide a simple and yet
                 accurate approach to predicting model performances.
                 These results indicate the models' strong capability of
                 accounting for user interactions in real-world social
                 media networks and temporal activity detection. The
                 research should provide new approaches for temporal
                 network activity detection, develop relevant new
                 measures, and report new findings from large social
                 media datasets.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "14",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Chen:2019:ESC,
  author =       "Jiawei Chen and Hongyan Liu and Yinghui (Catherine)
                 Yang and Jun He",
  title =        "Effective Selection of a Compact and High-Quality
                 Review Set with Information Preservation",
  journal =      j-TMIS,
  volume =       "10",
  number =       "4",
  pages =        "15:1--15:??",
  month =        dec,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3369395",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Dec 20 07:16:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3369395",
  abstract =     "Consumers increasingly make informed buying decisions
                 based on reading online reviews for products and
                 services. Due to the large volume of available online
                 reviews, consumers hardly have the time and patience to
                 read them all. This article aims to select a compact
                 set of high-quality reviews that can cover a specific
                 set of product features and related consumer
                 sentiments. Selecting such a subset of reviews can
                 significantly save the time spent on reading reviews
                 while preserving the information needed. A unique
                 review selection problem is defined and modeled as a
                 bi-objective combinatorial optimization problem, which
                 is then transformed into a minimum-cost set cover
                 problem that is NP-complete. Several approximation
                 algorithms are then designed, which can sustain
                 performance guarantees in polynomial time. Our
                 effective selection algorithms can also be upgraded to
                 handle dynamic situations. Comprehensive experiments
                 conducted on twelve real datasets demonstrate that the
                 proposed algorithms significantly outperform benchmark
                 methods by generating a more compact review set with
                 much lower computational cost. The number of reviews
                 selected is much smaller compared to the quantity of
                 all available reviews, and the selection efficiency is
                 deeply increased by accelerating strategies, making it
                 very practical to adopt the methods in real-world
                 online applications.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "15",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Jannach:2019:MBV,
  author =       "Dietmar Jannach and Michael Jugovac",
  title =        "Measuring the Business Value of Recommender Systems",
  journal =      j-TMIS,
  volume =       "10",
  number =       "4",
  pages =        "16:1--16:??",
  month =        dec,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3370082",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Dec 20 07:16:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3370082",
  abstract =     "Recommender Systems are nowadays successfully used by
                 all major web sites-from e-commerce to social media-to
                 filter content and make suggestions in a personalized
                 way. Academic research largely focuses on the value of
                 recommenders for consumers, e.g., in terms of reduced
                 information overload. To what extent and in which ways
                 recommender systems create business value is, however,
                 much less clear, and the literature on the topic is
                 scattered. In this research commentary, we review
                 existing publications on field tests of recommender
                 systems and report which business-related performance
                 measures were used in such real-world deployments. We
                 summarize common challenges of measuring the business
                 value in practice and critically discuss the value of
                 algorithmic improvements and offline experiments as
                 commonly done in academic environments. Overall, our
                 review indicates that various open questions remain
                 both regarding the realistic quantification of the
                 business effects of recommenders and the performance
                 assessment of recommendation algorithms in academia.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "16",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}

@Article{Li:2020:IIE,
  author =       "Hongfei Li and Ramesh Shankar and Jan Stallaert",
  title =        "Invested or Indebted: Ex-ante and Ex-post Reciprocity
                 in Online Knowledge Sharing Communities",
  journal =      j-TMIS,
  volume =       "11",
  number =       "1",
  pages =        "1:1--1:26",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3371388",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Apr 21 08:19:23 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/abs/10.1145/3371388",
  abstract =     "Online communities that curate knowledge critically
                 depend on high-quality contributions from anonymous
                 expert users. Understanding users' motivation to
                 contribute knowledge helps practitioners design such
                 websites for optimal user contribution and user
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "1",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Rezvani:2020:RRS,
  author =       "Mohsen Rezvani and Mojtaba Rezvani",
  title =        "A Randomized Reputation System in the Presence of
                 Unfair Ratings",
  journal =      j-TMIS,
  volume =       "11",
  number =       "1",
  pages =        "2:1--2:16",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3384472",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Apr 21 08:19:23 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/abs/10.1145/3384472",
  abstract =     "With the increasing popularity of online shopping
                 markets, a significant number of consumers rely on
                 these venues to meet their demands while choosing
                 different products based on the ratings provided by
                 others. Simultaneously, consumers feel confident
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "2",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Ni:2020:MLD,
  author =       "Li Ni and Wenjian Luo and Nannan Lu and Wenjie Zhu",
  title =        "Mining the Local Dependency Itemset in a Products
                 Network",
  journal =      j-TMIS,
  volume =       "11",
  number =       "1",
  pages =        "3:1--3:31",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3384473",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Apr 21 08:19:23 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/abs/10.1145/3384473",
  abstract =     "Many studies have been conducted on market basket
                 analysis such as association rules and dependent
                 patterns. These studies mainly focus on mining all
                 significant patterns or patterns directly associated
                 with a given item in a dataset. The problem that
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "3",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Pierazzi:2020:DDC,
  author =       "Fabio Pierazzi and Ghita Mezzour and Qian Han and
                 Michele Colajanni and V. S. Subrahmanian",
  title =        "A Data-driven Characterization of Modern {Android}
                 Spyware",
  journal =      j-TMIS,
  volume =       "11",
  number =       "1",
  pages =        "4:1--4:38",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3382158",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Apr 21 08:19:23 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/abs/10.1145/3382158",
  abstract =     "According to Nokia's 2017 Threat Intelligence Report,
                 68.5\% of malware targets the Android platform; Windows
                 is second with 28\%, followed by iOS and other
                 platforms with 3.5\%. The Android spyware family UAPUSH
                 was responsible for the most infections, \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "4",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Pal:2020:WCB,
  author =       "Ranjan Pal and Konstantinos Psounis and Jon Crowcroft
                 and Frank Kelly and Pan Hui and Sasu Tarkoma and
                 Abhishek Kumar and John Kelly and Aritra Chatterjee and
                 Leana Golubchik and Nishanth Sastry and Bodhibrata
                 Nag",
  title =        "When Are Cyber Blackouts in Modern Service Networks
                 Likely?: a Network Oblivious Theory on Cyber
                 (Re)Insurance Feasibility",
  journal =      j-TMIS,
  volume =       "11",
  number =       "2",
  pages =        "5:1--5:38",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3386159",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Jul 10 09:12:15 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/abs/10.1145/3386159",
  abstract =     "Service liability interconnections among globally
                 networked IT- and IoT-driven service organizations
                 create potential channels for cascading service
                 disruptions worth billions of dollars, due to modern
                 cyber-crimes such as DDoS, APT, and ransomware
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "5",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Ermakova:2020:SPR,
  author =       "Tatiana Ermakova and Benjamin Fabian and Marta
                 Kornacka and Scott Thiebes and Ali Sunyaev",
  title =        "Security and Privacy Requirements for Cloud Computing
                 in Healthcare: Elicitation and Prioritization from a
                 Patient Perspective",
  journal =      j-TMIS,
  volume =       "11",
  number =       "2",
  pages =        "6:1--6:29",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3386160",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Jul 10 09:12:15 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/abs/10.1145/3386160",
  abstract =     "Cloud computing promises essential improvements in
                 healthcare delivery performance. However, its wide
                 adoption in healthcare is yet to be seen, one main
                 reason being patients' concerns for security and
                 privacy of their sensitive medical records. These
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "6",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Lu:2020:AAW,
  author =       "Haibing Lu and Xi Chen and Junmin Shi and Jaideep
                 Vaidya and Vijayalakshmi Atluri and Yuan Hong and Wei
                 Huang",
  title =        "Algorithms and Applications to Weighted Rank-one
                 Binary Matrix Factorization",
  journal =      j-TMIS,
  volume =       "11",
  number =       "2",
  pages =        "7:1--7:33",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3386599",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Jul 10 09:12:15 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/abs/10.1145/3386599",
  abstract =     "Many applications use data that are better represented
                 in the binary matrix form, such as click-stream data,
                 market basket data, document-term data, user-permission
                 data in access control, and others. Matrix
                 factorization methods have been widely used \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "7",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Unger:2020:CAR,
  author =       "Moshe Unger and Alexander Tuzhilin and Amit Livne",
  title =        "Context-Aware Recommendations Based on Deep Learning
                 Frameworks",
  journal =      j-TMIS,
  volume =       "11",
  number =       "2",
  pages =        "8:1--8:15",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3386243",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Jul 10 09:12:15 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/abs/10.1145/3386243",
  abstract =     "In this article, we suggest a novel deep learning
                 recommendation framework that incorporates contextual
                 information into neural collaborative filtering
                 recommendation approaches. Since context is often
                 represented by dynamic and high-dimensional feature
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "8",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Dutta:2020:IWS,
  author =       "Kaushik Dutta and Xiao Fang and Zhengrui (Jeffrey)
                 Jiang",
  title =        "Introduction to {WITS 2018} Special Issue in {TMIS}",
  journal =      j-TMIS,
  volume =       "11",
  number =       "3",
  pages =        "9:1--9:2",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3404392",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Aug 19 07:07:56 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3404392",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "9",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Gopal:2020:RIU,
  author =       "Ram D. Gopal and Hooman Hidaji and Sule Nur Kutlu and
                 Raymond A. Patterson and Erik Rolland and Dmitry
                 Zhdanov",
  title =        "Real or Not?: Identifying Untrustworthy News Websites
                 Using Third-party Partnerships",
  journal =      j-TMIS,
  volume =       "11",
  number =       "3",
  pages =        "10:1--10:20",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3382188",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Aug 19 07:07:56 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3382188",
  abstract =     "Untrustworthy content such as fake news and clickbait
                 have become a pervasive problem on the Internet,
                 causing significant socio-political problems around the
                 world. Identifying untrustworthy content is a crucial
                 step in countering them. The current \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "10",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Tan:2020:CPC,
  author =       "Liling Tan and Maggie Yundi Li and Stanley Kok",
  title =        "E-Commerce Product Categorization via Machine
                 Translation",
  journal =      j-TMIS,
  volume =       "11",
  number =       "3",
  pages =        "11:1--11:14",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3382189",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Aug 19 07:07:56 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3382189",
  abstract =     "E-commerce platforms categorize their products into a
                 multi-level taxonomy tree with thousands of leaf
                 categories. Conventional methods for product
                 categorization are typically based on machine learning
                 classification algorithms. These algorithms take
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "11",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Wang:2020:PUP,
  author =       "Xiangyu Wang and Kang Zhao and Xun Zhou and Nick
                 Street",
  title =        "Predicting User Posting Activities in Online Health
                 Communities with Deep Learning",
  journal =      j-TMIS,
  volume =       "11",
  number =       "3",
  pages =        "12:1--12:15",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3383780",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Aug 19 07:07:56 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3383780",
  abstract =     "Online health communities (OHCs) represent a great
                 source of social support for patients and their
                 caregivers. Better predictions of user activities in
                 OHCs can help improve user engagement and retention,
                 which are important to manage and sustain a \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "12",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Tao:2020:WSW,
  author =       "Jie Tao and Lina Zhou",
  title =        "A Weakly Supervised {WordNet-Guided} Deep Learning
                 Approach to Extracting Aspect Terms from Online
                 Reviews",
  journal =      j-TMIS,
  volume =       "11",
  number =       "3",
  pages =        "13:1--13:22",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3399630",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Aug 19 07:07:56 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3399630",
  abstract =     "The unstructured nature of online reviews makes it
                 inefficient and inconvenient for prospective consumers
                 to research and use in support of purchase decision
                 making. The aspects of products provide a fine-grained
                 meaningful perspective for understanding \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "13",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Gan:2020:UDM,
  author =       "Wensheng Gan and Jerry Chun-Wei Lin and Han-Chieh Chao
                 and Philippe Fournier-Viger and Xuan Wang and Philip S.
                 Yu",
  title =        "Utility-Driven Mining of Trend Information for
                 Intelligent System",
  journal =      j-TMIS,
  volume =       "11",
  number =       "3",
  pages =        "14:1--14:28",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3391251",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Aug 19 07:07:56 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3391251",
  abstract =     "Useful knowledge, embedded in a database, is likely to
                 change over time. Identifying the recent changes in
                 temporal data can provide valuable up-to-date
                 information to decision makers. Nevertheless,
                 techniques for mining high-utility patterns (HUPs)
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "14",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Sreenu:2020:CPP,
  author =       "Nenavath Sreenu",
  title =        "Cashless Payment Policy and Its Effects on Economic
                 Growth of {India}: an Exploratory Study",
  journal =      j-TMIS,
  volume =       "11",
  number =       "3",
  pages =        "15:1--15:10",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3391402",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Aug 19 07:07:56 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3391402",
  abstract =     "The present world has moved from cash transactions to
                 cashless transactions. This article examines the impact
                 of implementation of a cashless payment policy on
                 economic development and gradual transition to a
                 cashless economy in India. For this study, \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "15",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Belhadi:2020:TOD,
  author =       "Asma Belhadi and Youcef Djenouri and Jerry Chun-Wei
                 Lin and Alberto Cano",
  title =        "Trajectory Outlier Detection: Algorithms, Taxonomies,
                 Evaluation, and Open Challenges",
  journal =      j-TMIS,
  volume =       "11",
  number =       "3",
  pages =        "16:1--16:29",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3399631",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Aug 19 07:07:56 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3399631",
  abstract =     "Detecting abnormal trajectories is an important task
                 in research and industrial applications, which has
                 attracted considerable attention in recent decades.
                 This work studies the existing trajectory outlier
                 detection algorithms in different industrial \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "16",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Samtani:2020:TAI,
  author =       "Sagar Samtani and Murat Kantarcioglu and Hsinchun
                 Chen",
  title =        "Trailblazing the Artificial Intelligence for
                 Cybersecurity Discipline: a Multi-Disciplinary Research
                 Roadmap",
  journal =      j-TMIS,
  volume =       "11",
  number =       "4",
  pages =        "17:1--17:19",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3430360",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Mar 20 18:13:57 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3430360",
  abstract =     "Cybersecurity has rapidly emerged as a grand societal
                 challenge of the 21st century. Innovative solutions to
                 proactively tackle emerging cybersecurity challenges
                 are essential to ensuring a safe and secure society.
                 Artificial Intelligence (AI) has \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "17",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Mudgerikar:2020:EBI,
  author =       "Anand Mudgerikar and Puneet Sharma and Elisa Bertino",
  title =        "Edge-Based Intrusion Detection for {IoT} devices",
  journal =      j-TMIS,
  volume =       "11",
  number =       "4",
  pages =        "18:1--18:21",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3382159",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Mar 20 18:13:57 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3382159",
  abstract =     "As the Internet of Things (IoT) is estimated to grow
                 to 25 billion by 2021, there is a need for an effective
                 and efficient Intrusion Detection System (IDS) for IoT
                 devices. Traditional network-based IDSs are unable to
                 efficiently detect IoT malware and \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "18",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Husak:2020:PCS,
  author =       "Martin Hus{\'a}k and Tom{\'a}s Bajtos and Jaroslav
                 Kaspar and Elias Bou-Harb and Pavel Celeda",
  title =        "Predictive Cyber Situational Awareness and
                 Personalized Blacklisting: a Sequential Rule Mining
                 Approach",
  journal =      j-TMIS,
  volume =       "11",
  number =       "4",
  pages =        "19:1--19:16",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3386250",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Mar 20 18:13:57 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3386250",
  abstract =     "Cybersecurity adopts data mining for its ability to
                 extract concealed and indistinct patterns in the data,
                 such as for the needs of alert correlation. Inferring
                 common attack patterns and rules from the alerts helps
                 in understanding the threat landscape \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "19",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Alagheband:2020:TBG,
  author =       "Mahdi R. Alagheband and Atefeh Mashatan and Morteza
                 Zihayat",
  title =        "Time-based Gap Analysis of Cybersecurity Trends in
                 Academic and Digital Media",
  journal =      j-TMIS,
  volume =       "11",
  number =       "4",
  pages =        "20:1--20:20",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3389684",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Mar 20 18:13:57 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3389684",
  abstract =     "This study analyzes cybersecurity trends and proposes
                 a conceptual framework to identify cybersecurity topics
                 of social interest and emerging topics that need to be
                 addressed by researchers in the field. The insights
                 drawn from this framework allow for \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "20",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Mangino:2020:ISI,
  author =       "Antonio Mangino and Morteza Safaei Pour and Elias
                 Bou-Harb",
  title =        "{Internet}-scale Insecurity of Consumer {Internet of
                 Things}: an Empirical Measurements Perspective",
  journal =      j-TMIS,
  volume =       "11",
  number =       "4",
  pages =        "21:1--21:24",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3394504",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Mar 20 18:13:57 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3394504",
  abstract =     "The number of Internet-of-Things (IoT) devices
                 actively communicating across the Internet is
                 continually increasing, as these devices are deployed
                 across a variety of sectors, constantly transferring
                 private data across the Internet. Due to the \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "21",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Sweet:2020:VVC,
  author =       "Christopher Sweet and Stephen Moskal and Shanchieh Jay
                 Yang",
  title =        "On the Variety and Veracity of Cyber Intrusion Alerts
                 Synthesized by Generative Adversarial Networks",
  journal =      j-TMIS,
  volume =       "11",
  number =       "4",
  pages =        "22:1--22:21",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3394503",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Mar 20 18:13:57 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3394503",
  abstract =     "Many cyber attack actions can be observed, but the
                 observables often exhibit intricate feature
                 dependencies, non-homogeneity, and potentially rare yet
                 critical samples. This work tests the ability to learn,
                 model, and synthesize cyber intrusion alerts \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "22",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Mehrotra:2020:PPD,
  author =       "Sharad Mehrotra and Shantanu Sharma and Jeffrey D.
                 Ullman and Dhrubajyoti Ghosh and Peeyush Gupta and
                 Anurag Mishra",
  title =        "{PANDA}: Partitioned Data Security on Outsourced
                 Sensitive and Non-sensitive Data",
  journal =      j-TMIS,
  volume =       "11",
  number =       "4",
  pages =        "23:1--23:41",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3397521",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Mar 20 18:13:57 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3397521",
  abstract =     "Despite extensive research on cryptography, secure and
                 efficient query processing over outsourced data remains
                 an open challenge. This article continues along with
                 the emerging trend in secure data processing that
                 recognizes that the entire dataset may \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "23",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Shao:2020:EEA,
  author =       "Sicong Shao and Cihan Tunc and Amany Al-Shawi and
                 Salim Hariri",
  title =        "An Ensemble of Ensembles Approach to Author
                 Attribution for {Internet} Relay Chat Forensics",
  journal =      j-TMIS,
  volume =       "11",
  number =       "4",
  pages =        "24:1--24:25",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3409455",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Mar 20 18:13:57 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3409455",
  abstract =     "With the advances in Internet technologies and
                 services, social media has been gained extreme
                 popularity, especially because these technologies
                 provide potential anonymity, which in turn harbors
                 hacker discussion forums, underground markets, dark
                 web, \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "24",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Kesan:2020:ACI,
  author =       "Jay P. Kesan and Linfeng Zhang",
  title =        "Analysis of Cyber Incident Categories Based on
                 Losses",
  journal =      j-TMIS,
  volume =       "11",
  number =       "4",
  pages =        "25:1--25:28",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3418288",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Mar 20 18:13:57 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3418288",
  abstract =     "The fact that ``cyber risk'' is indeed a collective
                 term for various distinct risks creates great
                 difficulty in communications. For example,
                 policyholders of ``cyber insurance'' contracts often
                 have a limited or inaccurate understanding about the
                 coverage \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "25",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Sainani:2020:IRS,
  author =       "Henanksha Sainani and Josephine M. Namayanja and
                 Guneeti Sharma and Vasundhara Misal and Vandana P.
                 Janeja",
  title =        "{IP} Reputation Scoring with Geo-Contextual Feature
                 Augmentation",
  journal =      j-TMIS,
  volume =       "11",
  number =       "4",
  pages =        "26:1--26:29",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3419373",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Mar 20 18:13:57 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3419373",
  abstract =     "The focus of this article is to present an effective
                 anomaly detection model for an encrypted network
                 session by developing a novel IP reputation scoring
                 model that labels the incoming session IP address based
                 on the most similar IP addresses in terms \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "26",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Samtani:2021:MDP,
  author =       "Sagar Samtani and Murat Kantarcioglu and Hsinchun
                 Chen",
  title =        "A Multi-Disciplinary Perspective for Conducting
                 Artificial Intelligence-enabled Privacy Analytics:
                 Connecting Data, Algorithms, and Systems",
  journal =      j-TMIS,
  volume =       "12",
  number =       "1",
  pages =        "1:1--1:18",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3447507",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Mar 20 18:13:58 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3447507",
  abstract =     "Events such as Facebook-Cambridge Analytica scandal
                 and data aggregation efforts by technology providers
                 have illustrated how fragile modern society is to
                 privacy violations. Internationally recognized entities
                 such as the National Science Foundation \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "1",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Zaeem:2021:EGP,
  author =       "Razieh Nokhbeh Zaeem and K. Suzanne Barber",
  title =        "The Effect of the {GDPR} on Privacy Policies: Recent
                 Progress and Future Promise",
  journal =      j-TMIS,
  volume =       "12",
  number =       "1",
  pages =        "2:1--2:20",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3389685",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Mar 20 18:13:58 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3389685",
  abstract =     "The General Data Protection Regulation (GDPR) is
                 considered by some to be the most important change in
                 data privacy regulation in 20 years. Effective May
                 2018, the European Union GDPR privacy law applies to
                 any organization that collects and processes \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "2",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Sudhakar:2021:DLM,
  author =       "Tanuja Sudhakar and Marina Gavrilova",
  title =        "Deep Learning for Multi-instance Biometric Privacy",
  journal =      j-TMIS,
  volume =       "12",
  number =       "1",
  pages =        "3:1--3:23",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3389683",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Mar 20 18:13:58 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3389683",
  abstract =     "The fundamental goal of a revocable biometric system
                 is to defend a user's biometrics from being
                 compromised. This research explores the application of
                 deep learning or Convolutional Neural Networks to
                 multi-instance biometrics. Modality features are
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "3",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Kul:2021:ACI,
  author =       "G{\"o}khan Kul and Shambhu Upadhyaya and Andrew
                 Hughes",
  title =        "An Analysis of Complexity of Insider Attacks to
                 Databases",
  journal =      j-TMIS,
  volume =       "12",
  number =       "1",
  pages =        "4:1--4:18",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3391231",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Mar 20 18:13:58 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3391231",
  abstract =     "Insider attacks are one of the most dangerous threats
                 to an organization. Unfortunately, they are very
                 difficult to foresee, detect, and defend against due to
                 the trust and responsibilities placed on the employees.
                 In this article, we first define the \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "4",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Ranathunga:2021:MRM,
  author =       "Dinesha Ranathunga and Matthew Roughan and Hung
                 Nguyen",
  title =        "Mathematical Reconciliation of Medical Privacy
                 Policies",
  journal =      j-TMIS,
  volume =       "12",
  number =       "1",
  pages =        "5:1--5:18",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3397520",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Mar 20 18:13:58 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3397520",
  abstract =     "Healthcare data are arguably the most private of
                 personal data. This very private information in the
                 wrong hands can lead to identity theft, prescription
                 fraud, insurance fraud, and an array of other crimes.
                 Electronic-health systems such as My Health Record in
                 Australia holds great promise in sharing medical data
                 and improving healthcare quality. But, a key privacy
                 issue in these systems is the misuse of healthcare data
                 by authorities. The recent General Data Protection
                 Regulation (GDPR) introduced in the EU aims to reduce
                 personal-data misuse. But, there are no tools currently
                 available to accurately reconcile a domestic E-health
                 policy against the GDPR to identify discrepancies.
                 Reconciling privacy policies is also non-trivial,
                 because policies are often written in free text, making
                 them subject to human interpretation.\par

                 In this article, we propose a tool that allows the
                 description of E-health privacy policies, represents
                 them using formal constructs making the policies
                 precise and explicit. Using this formal framework, our
                 tool can automatically reconcile a domestic E-health
                 policy against the GDPR to identify violations and
                 omissions. We use our prototype to illustrate several
                 critical flaws in Australia's My Health Record policy,
                 including a non-compliance with GDPR that allows
                 healthcare providers to access medical records by
                 default.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "5",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Roy:2021:OER,
  author =       "Arindam Roy and Shamik Sural and Arun Kumar Majumdar
                 and Jaideep Vaidya and Vijayalakshmi Atluri",
  title =        "Optimal Employee Recruitment in Organizations under
                 Attribute-Based Access Control",
  journal =      j-TMIS,
  volume =       "12",
  number =       "1",
  pages =        "6:1--6:24",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3403950",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Mar 20 18:13:58 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3403950",
  abstract =     "For any successful business endeavor, recruitment of a
                 required number of appropriately qualified employees in
                 proper positions is a key requirement. For effective
                 utilization of human resources, reorganization of such
                 workforce assignment is also a \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "6",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Akanfe:2021:DIF,
  author =       "Oluwafemi Akanfe and Rohit Valecha and H. Raghav Rao",
  title =        "Design of an Inclusive Financial Privacy Index
                 {(INF-PIE)}: a Financial Privacy and Digital Financial
                 Inclusion Perspective",
  journal =      j-TMIS,
  volume =       "12",
  number =       "1",
  pages =        "7:1--7:21",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3403949",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Mar 20 18:13:58 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3403949",
  abstract =     "Financial privacy is an important part of an
                 individual's privacy, but efforts to enhance financial
                 privacy have often not been given enough prominence by
                 some countries when advancing financial inclusion. This
                 impedes under-served communities from \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "7",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Alkhodair:2021:DHE,
  author =       "Sarah A. Alkhodair and Benjamin C. M. Fung and Steven
                 H. H. Ding and William K. Cheung and Shih-Chia Huang",
  title =        "Detecting High-Engaging Breaking News Rumors in Social
                 Media",
  journal =      j-TMIS,
  volume =       "12",
  number =       "1",
  pages =        "8:1--8:16",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3416703",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Mar 20 18:13:58 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3416703",
  abstract =     "Users from all over the world increasingly adopt
                 social media for newsgathering, especially during
                 breaking news. Breaking news is an unexpected event
                 that is currently developing. Early stages of breaking
                 news are usually associated with lots of \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "8",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Benedetto:2021:EIC,
  author =       "Francesco Benedetto and Loretta Mastroeni and
                 Pierluigi Vellucci",
  title =        "Extraction of Information Content Exchange in
                 Financial Markets by an Entropy Analysis",
  journal =      j-TMIS,
  volume =       "12",
  number =       "1",
  pages =        "9:1--9:16",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3419372",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Mar 20 18:13:58 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3419372",
  abstract =     "Recently, there has been an explosive interest in the
                 literature about modeling and forecasting volatility in
                 financial markets. Many researches have focused on
                 energy markets and oil volatility index (OVX). In this
                 article, we aim first at showing if \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "9",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Ng:2021:LSM,
  author =       "Ka Chung Ng and Mike K. P. So and Kar Yan Tam",
  title =        "A Latent Space Modeling Approach to Interfirm
                 Relationship Analysis",
  journal =      j-TMIS,
  volume =       "12",
  number =       "2",
  pages =        "10:1--10:44",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3424240",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sun Jun 27 07:39:07 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3424240",
  abstract =     "Interfirm relationships are crucial to our
                 understanding of firms' collective and interactive
                 behavior. Many information systems-related phenomena,
                 including the diffusion of innovations, standard
                 alliances, technology collaboration, and outsourcing,
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "10",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Onumo:2021:AME,
  author =       "Aristotle Onumo and Irfan Ullah-Awan and Andrea
                 Cullen",
  title =        "Assessing the Moderating Effect of Security
                 Technologies on Employees Compliance with Cybersecurity
                 Control Procedures",
  journal =      j-TMIS,
  volume =       "12",
  number =       "2",
  pages =        "11:1--11:29",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3424282",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sun Jun 27 07:39:07 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3424282",
  abstract =     "The increase in cybersecurity threats and the
                 challenges for organisations to protect their
                 information technology assets has made adherence to
                 organisational security control processes and
                 procedures a critical issue that needs to be adequately
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "11",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Belhadi:2021:MLI,
  author =       "Asma Belhadi and Youcef Djenouri and Djamel Djenouri
                 and Tomasz Michalak and Jerry Chun-Wei Lin",
  title =        "Machine Learning for Identifying Group Trajectory
                 Outliers",
  journal =      j-TMIS,
  volume =       "12",
  number =       "2",
  pages =        "12:1--12:25",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3430195",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sun Jun 27 07:39:07 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3430195",
  abstract =     "Prior works on the trajectory outlier detection
                 problem solely consider individual outliers. However,
                 in real-world scenarios, trajectory outliers can often
                 appear in groups, e.g., a group of bikes that deviates
                 to the usual trajectory due to the \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "12",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Abdibayev:2021:UWE,
  author =       "Almas Abdibayev and Dongkai Chen and Haipeng Chen and
                 Deepti Poluru and V. S. Subrahmanian",
  title =        "Using Word Embeddings to Deter Intellectual Property
                 Theft through Automated Generation of Fake Documents",
  journal =      j-TMIS,
  volume =       "12",
  number =       "2",
  pages =        "13:1--13:22",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3418289",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sun Jun 27 07:39:07 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3418289",
  abstract =     "Theft of intellectual property is a growing
                 problem-one that is exacerbated by the fact that a
                 successful compromise of an enterprise might only
                 become known months after the hack. A recent solution
                 called FORGE addresses this problem by automatically
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "13",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Xue:2021:OOA,
  author =       "Xingsi Xue and Xiaojing Wu and Junfeng Chen",
  title =        "Optimizing Ontology Alignment Through an Interactive
                 Compact Genetic Algorithm",
  journal =      j-TMIS,
  volume =       "12",
  number =       "2",
  pages =        "14:1--14:17",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3439772",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sun Jun 27 07:39:07 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3439772",
  abstract =     "Ontology provides a shared vocabulary of a domain by
                 formally representing the meaning of its concepts, the
                 properties they possess, and the relations among them,
                 which is the state-of-the-art knowledge modeling
                 technique. However, the ontologies in the \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "14",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Djenouri:2021:EDS,
  author =       "Youcef Djenouri and Jerry Chun-Wei Lin and Kjetil
                 N{\o}rv{\aa}g and Heri Ramampiaro and Philip S. Yu",
  title =        "Exploring Decomposition for Solving Pattern Mining
                 Problems",
  journal =      j-TMIS,
  volume =       "12",
  number =       "2",
  pages =        "15:1--15:36",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3439771",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sun Jun 27 07:39:07 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3439771",
  abstract =     "This article introduces a highly efficient pattern
                 mining technique called Clustering-based Pattern Mining
                 (CBPM). This technique discovers relevant patterns by
                 studying the correlation between transactions in the
                 transaction database based on \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "15",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Teng:2021:ENF,
  author =       "Mingfei Teng and Hengshu Zhu and Chuanren Liu and Hui
                 Xiong",
  title =        "Exploiting Network Fusion for Organizational Turnover
                 Prediction",
  journal =      j-TMIS,
  volume =       "12",
  number =       "2",
  pages =        "16:1--16:18",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3439770",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sun Jun 27 07:39:07 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3439770",
  abstract =     "As an emerging measure of proactive talent management,
                 talent turnover prediction is critically important for
                 companies to attract, engage, and retain talents in
                 order to prevent the loss of intellectual capital.
                 While tremendous efforts have been made \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "16",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Pal:2021:WCC,
  author =       "Ranjan Pal and Ziyuan Huang and Sergey Lototsky and
                 Xinlong Yin and Mingyan Liu and Jon Crowcroft and
                 Nishanth Sastry and Swades De and Bodhibrata Nag",
  title =        "Will Catastrophic Cyber-Risk Aggregation Thrive in the
                 {IoT} Age? {A} Cautionary Economics Tale for
                 (Re-)Insurers and Likes",
  journal =      j-TMIS,
  volume =       "12",
  number =       "2",
  pages =        "17:1--17:36",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3446635",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sun Jun 27 07:39:07 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3446635",
  abstract =     "Service liability interconnections among networked IT
                 and IoT-driven service organizations create potential
                 channels for cascading service disruptions due to
                 modern cybercrimes such as DDoS, APT, and ransomware
                 attacks. These attacks are known to \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "17",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Nakashima:2021:AFS,
  author =       "Makiya Nakashima and Alex Sim and Youngsoo Kim and
                 Jonghyun Kim and Jinoh Kim",
  title =        "Automated Feature Selection for Anomaly Detection in
                 Network Traffic Data",
  journal =      j-TMIS,
  volume =       "12",
  number =       "3",
  pages =        "18:1--18:28",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3446636",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Jul 22 08:13:40 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3446636",
  abstract =     "Variable selection (also known as feature selection )
                 is essential to optimize the learning complexity by
                 prioritizing features, particularly for a massive,
                 high-dimensional dataset like network traffic data. In
                 reality, however, it is not an easy task to \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "18",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Qiu:2021:MDP,
  author =       "Lin Qiu and Sruthi Gorantla and Vaibhav Rajan and
                 Bernard C. Y. Tan",
  title =        "Multi-disease Predictive Analytics: a Clinical
                 Knowledge-aware Approach",
  journal =      j-TMIS,
  volume =       "12",
  number =       "3",
  pages =        "19:1--19:34",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3447942",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Jul 22 08:13:40 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3447942",
  abstract =     "Multi-Disease Predictive Analytics (MDPA) models
                 simultaneously predict the risks of multiple diseases
                 in patients and are valuable in early diagnoses.
                 Patients tend to have multiple diseases simultaneously
                 or develop multiple complications over time, and
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "19",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Leng:2021:LIC,
  author =       "Yan Leng and Jinhua Zhao and Haris Koutsopoulos",
  title =        "Leveraging Individual and Collective Regularity to
                 Profile and Segment User Locations from Mobile Phone
                 Data",
  journal =      j-TMIS,
  volume =       "12",
  number =       "3",
  pages =        "20:1--20:22",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3449042",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Jul 22 08:13:40 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3449042",
  abstract =     "The dynamic monitoring of home and workplace
                 distribution is a fundamental building block for
                 improving location-based service systems in
                 fast-developing cities worldwide. Inferring these
                 places is challenging; existing approaches rely on
                 labor-intensive \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "20",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Wang:2021:GCN,
  author =       "Xi Wang and Yibo Chai and Hui Li and Wenbin Wang and
                 Weishan Sun",
  title =        "Graph Convolutional Network-based Model for
                 Incident-related Congestion Prediction: a Case Study of
                 {Shanghai} Expressways",
  journal =      j-TMIS,
  volume =       "12",
  number =       "3",
  pages =        "21:1--21:22",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3451356",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Jul 22 08:13:40 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3451356",
  abstract =     "Traffic congestion has become a significant obstacle
                 to the development of mega cities in China. Although
                 local governments have used many resources in
                 constructing road infrastructure, it is still
                 insufficient for the increasing traffic demands. As a
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "21",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Huang:2021:EEM,
  author =       "Peng Huang and Henry C. Lucas",
  title =        "Early Exploration of {MOOCs} in the {U.S}. Higher
                 Education: an Absorptive Capacity Perspective",
  journal =      j-TMIS,
  volume =       "12",
  number =       "3",
  pages =        "22:1--22:28",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3456295",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Jul 22 08:13:40 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3456295",
  abstract =     "Advanced information technologies have enabled Massive
                 Open Online Courses (MOOCs), which have the potential
                 to transform higher education around the world. Why are
                 some institutions eager to embrace this
                 technology-enabled model of teaching, while others
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "22",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Parameshwarappa:2021:ADA,
  author =       "Pooja Parameshwarappa and Zhiyuan Chen and G{\"u}nes
                 Koru",
  title =        "Anonymization of Daily Activity Data by Using
                 $l$-diversity Privacy Model",
  journal =      j-TMIS,
  volume =       "12",
  number =       "3",
  pages =        "23:1--23:21",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3456876",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Jul 22 08:13:40 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3456876",
  abstract =     "In the age of IoT, collection of activity data has
                 become ubiquitous. Publishing activity data can be
                 quite useful for various purposes such as estimating
                 the level of assistance required by older adults and
                 facilitating early diagnosis and treatment of
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "23",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Xie:2021:WLP,
  author =       "Jiaheng Xie and Bin Zhang and Susan Brown and Daniel
                 Zeng",
  title =        "Write Like a Pro or an Amateur? {Effect} of Medical
                 Language Formality",
  journal =      j-TMIS,
  volume =       "12",
  number =       "3",
  pages =        "24:1--24:25",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3458752",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Jul 22 08:13:40 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3458752",
  abstract =     "Past years have seen rising engagement among
                 caregivers in online health communities. Although
                 studies indicate that this caregiver-generated online
                 health information benefits patients, how such
                 information can be perceived easily and correctly
                 remains \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "24",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Edla:2021:EDL,
  author =       "Damodar Reddy Edla and Shubham Dodia and Annushree
                 Bablani and Venkatanareshbabu Kuppili",
  title =        "An Efficient Deep Learning Paradigm for Deceit
                 Identification Test on {EEG} Signals",
  journal =      j-TMIS,
  volume =       "12",
  number =       "3",
  pages =        "25:1--25:20",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3458791",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Jul 22 08:13:40 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3458791",
  abstract =     "Brain-Computer Interface is the collaboration of the
                 human brain and a device that controls the actions of a
                 human using brain signals. Applications of
                 brain-computer interface vary from the field of
                 entertainment to medical. In this article, a novel
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "25",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Wang:2021:ABB,
  author =       "Qin Wang and Shiping Chen and Yang Xiang",
  title =        "Anonymous Blockchain-based System for Consortium",
  journal =      j-TMIS,
  volume =       "12",
  number =       "3",
  pages =        "26:1--26:25",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3459087",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Jul 22 08:13:40 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3459087",
  abstract =     "Blockchain records transactions with various
                 protection techniques against tampering. To meet the
                 requirements on cooperation and anonymity of companies
                 and organizations, researchers have developed a few
                 solutions. Ring signature-based schemes allow multiple
                 participants cooperatively to manage while preserving
                 their individuals' privacy. However, the solutions
                 cannot work properly due to the increased computing
                 complexity along with the expanded group size. In this
                 article, we propose a Multi-center Anonymous
                 Blockchain-based (MAB) system, with joint management
                 for the consortium and privacy protection for the
                 participants. To achieve that, we formalize the syntax
                 used by the MAB system and present a general
                 construction based on a modular design. By applying
                 cryptographic primitives to each module, we instantiate
                 our scheme with anonymity and decentralization.
                 Furthermore, we carry out a comprehensive formal
                 analysis of our exemplified scheme. A proof of concept
                 simulation is provided to show the feasibility. The
                 results demonstrate security and efficiency from both
                 theoretical perspectives and practical perspectives.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "26",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Zhao:2021:ISS,
  author =       "Kang Zhao and Qingpeng Zhang and Sean H. Y. Yuan and
                 Kelvin Kam-Fai Tsoi",
  title =        "Introduction to the Special Section on Using {AI} and
                 Data Science to Handle Pandemics and Related
                 Disruptions",
  journal =      j-TMIS,
  volume =       "12",
  number =       "4",
  pages =        "27:1--27:2",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3486969",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Oct 27 15:36:00 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3486969",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "27",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Avetisian:2021:CSR,
  author =       "Manvel Avetisian and Ilya Burenko and Konstantin
                 Egorov and Vladimir Kokh and Aleksandr Nesterov and
                 Aleksandr Nikolaev and Alexander Ponomarchuk and Elena
                 Sokolova and Alex Tuzhilin and Dmitry Umerenkov",
  title =        "{CoRSAI}: a System for Robust Interpretation of {CT}
                 Scans of {COVID-19} Patients Using Deep Learning",
  journal =      j-TMIS,
  volume =       "12",
  number =       "4",
  pages =        "28:1--28:16",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3467471",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Oct 27 15:36:00 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3467471",
  abstract =     "Analysis of chest CT scans can be used in detecting
                 parts of lungs that are affected by infectious diseases
                 such as COVID-19. Determining the volume of lungs
                 affected by lesions is essential for formulating
                 treatment recommendations and prioritizing \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "28",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Zokaeinikoo:2021:AIA,
  author =       "Maryam Zokaeinikoo and Pooyan Kazemian and Prasenjit
                 Mitra and Soundar Kumara",
  title =        "{AIDCOV}: an Interpretable Artificial Intelligence
                 Model for Detection of {COVID-19} from Chest
                 Radiography Images",
  journal =      j-TMIS,
  volume =       "12",
  number =       "4",
  pages =        "29:1--29:20",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3466690",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Oct 27 15:36:00 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3466690",
  abstract =     "As the Coronavirus Disease 2019 (COVID-19) pandemic
                 continues to grow globally, testing to detect COVID-19
                 and isolating individuals who test positive remains the
                 primary strategy for preventing community spread of the
                 disease. Therefore, automatic and \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "29",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Liang:2021:USM,
  author =       "Guanqing Liang and Jingxin Zhao and Helena Yan Ping
                 Lau and Cane Wing-Ki Leung",
  title =        "Using Social Media to Analyze Public Concerns and
                 Policy Responses to {COVID-19} in {Hong Kong}",
  journal =      j-TMIS,
  volume =       "12",
  number =       "4",
  pages =        "30:1--30:20",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3460124",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Oct 27 15:36:00 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3460124",
  abstract =     "The outbreak of COVID-19 has caused huge economic and
                 societal disruptions. To fight against the coronavirus,
                 it is critical for policymakers to take swift and
                 effective actions. In this article, we take Hong Kong
                 as a case study, aiming to leverage \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "30",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Biester:2021:UIC,
  author =       "Laura Biester and Katie Matton and Janarthanan
                 Rajendran and Emily Mower Provost and Rada Mihalcea",
  title =        "Understanding the Impact of {COVID-19} on Online
                 Mental Health Forums",
  journal =      j-TMIS,
  volume =       "12",
  number =       "4",
  pages =        "31:1--31:28",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3458770",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Oct 27 15:36:00 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3458770",
  abstract =     "Like many of the disasters that have preceded it, the
                 COVID-19 pandemic is likely to have a profound impact
                 on people's mental health. Understanding its impact can
                 inform strategies for mitigating negative consequences.
                 This work seeks to better \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "31",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Gu:2021:SFR,
  author =       "Kang Gu and Soroush Vosoughi and Temiloluwa Prioleau",
  title =        "{SymptomID}: a Framework for Rapid Symptom
                 Identification in Pandemics Using News Reports",
  journal =      j-TMIS,
  volume =       "12",
  number =       "4",
  pages =        "32:1--32:17",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3462441",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Oct 27 15:36:00 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3462441",
  abstract =     "The ability to quickly learn fundamentals about a new
                 infectious disease, such as how it is transmitted, the
                 incubation period, and related symptoms, is crucial in
                 any novel pandemic. For instance, rapid identification
                 of symptoms can enable interventions \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "32",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Zhu:2021:HRS,
  author =       "Shixiang Zhu and Alexander Bukharin and Liyan Xie and
                 Mauricio Santillana and Shihao Yang and Yao Xie",
  title =        "High-Resolution Spatio-Temporal Model for County-Level
                 {COVID-19} Activity in the {U.S}.",
  journal =      j-TMIS,
  volume =       "12",
  number =       "4",
  pages =        "33:1--33:20",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3468876",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Oct 27 15:36:00 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3468876",
  abstract =     "We present an interpretable high-resolution
                 spatio-temporal model to estimate COVID-19 deaths
                 together with confirmed cases 1 week ahead of the
                 current time, at the county level and weekly
                 aggregated, in the United States. A notable feature of
                 our spatio-. \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "33",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Li:2021:CSS,
  author =       "Junye Li and Aryan Sharma and Deepak Mishra and
                 Gustavo Batista and Aruna Seneviratne",
  title =        "{COVID}-Safe Spatial Occupancy Monitoring Using
                 {OFDM}-Based Features and Passive {WiFi} Samples",
  journal =      j-TMIS,
  volume =       "12",
  number =       "4",
  pages =        "34:1--34:24",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3472668",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Oct 27 15:36:00 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3472668",
  abstract =     "During the COVID-19 pandemic, authorities have been
                 asking for social distancing to prevent transmission of
                 the virus. However, enforcing such distancing has been
                 challenging in tight spaces such as elevators and
                 unmonitored commercial settings such as \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "34",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Kharkwal:2021:UOD,
  author =       "Himanshu Kharkwal and Dakota Olson and Jiali Huang and
                 Abhiraj Mohan and Ankur Mani and Jaideep Srivastava",
  title =        "University Operations During a Pandemic: a Flexible
                 Decision Analysis Toolkit",
  journal =      j-TMIS,
  volume =       "12",
  number =       "4",
  pages =        "35:1--35:24",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3460125",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Oct 27 15:36:00 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3460125",
  abstract =     "Modeling infection spread during pandemics is not new,
                 with models using past data to tune simulation
                 parameters for predictions. These help in understanding
                 of the healthcare burden posed by a pandemic and
                 responding accordingly. However, the problem of
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "35",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Ouyang:2021:DRS,
  author =       "Chun Ouyang and Michael Adams and Arthur H. M. Ter
                 Hofstede and Yang Yu",
  title =        "Design and Realisation of Scalable Business Process
                 Management Systems for Deployment in the Cloud",
  journal =      j-TMIS,
  volume =       "12",
  number =       "4",
  pages =        "36:1--36:26",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3460123",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Oct 27 15:36:00 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3460123",
  abstract =     "Business Process Management Systems (BPMSs) provide
                 automated support for the execution of business
                 processes in modern organisations. With the emergence
                 of cloud computing, BPMS deployment considerations are
                 shifting from traditional on-premise models to
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "36",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Chakraborty:2021:MLA,
  author =       "Saurav Chakraborty and Agnieszka Onuchowska and Sagar
                 Samtani and Wolfgang Jank and Brandon Wolfram",
  title =        "Machine Learning for Automated Industrial {IoT} Attack
                 Detection: an Efficiency-Complexity Trade-off",
  journal =      j-TMIS,
  volume =       "12",
  number =       "4",
  pages =        "37:1--37:28",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3460822",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Oct 27 15:36:00 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3460822",
  abstract =     "Critical city infrastructures that depend on smart
                 Industrial Internet of Things (IoT) devices have been
                 increasingly becoming a target of cyberterrorist or
                 hacker attacks. Although this has led to multiple
                 studies in the recent past, there exists a \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "37",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Cwei:2022:ISI,
  author =       "Lin Jerry Cwei and Nachiketa Sahoo and Gautam
                 Srivastava and Weiping Ding",
  title =        "Introduction to the Special Issue on Pattern-Driven
                 Mining, Analytics, and Prediction for Decision Making,
                 {Part 1}",
  journal =      j-TMIS,
  volume =       "13",
  number =       "1",
  pages =        "1:1--1:3",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3486960",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Jan 7 07:41:54 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3486960",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "1",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Wang:2022:DDS,
  author =       "Shui-Hua Wang and Xin Zhang and Yu-Dong Zhang",
  title =        "{DSSAE}: Deep Stacked Sparse Autoencoder Analytical
                 Model for {COVID-19} Diagnosis by Fractional {Fourier}
                 Entropy",
  journal =      j-TMIS,
  volume =       "13",
  number =       "1",
  pages =        "2:1--2:20",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3451357",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Jan 7 07:41:54 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3451357",
  abstract =     "(Aim) COVID-19 has caused more than 2.28 million
                 deaths till 4/Feb/2021 while it is still spreading
                 across the world. This study proposed a novel
                 artificial intelligence model to diagnose COVID-19
                 based on chest CT images. (Methods) First, the two-.
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "2",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Chen:2022:TDT,
  author =       "Fan Chen and Jiaoxiong Xia and Honghao Gao and Huahu
                 Xu and Wei Wei",
  title =        "{TRG-DAtt}: The Target Relational Graph and Double
                 Attention Network Based Sentiment Analysis and
                 Prediction for Supporting Decision Making",
  journal =      j-TMIS,
  volume =       "13",
  number =       "1",
  pages =        "3:1--3:25",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3462442",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Jan 7 07:41:54 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3462442",
  abstract =     "The management of public opinion and the use of big
                 data monitoring to accurately judge and verify all
                 kinds of information are valuable aspects in the
                 enterprise management decision-making process. The
                 sentiment analysis of reviews is a key decision-.
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "3",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Nawaz:2022:MHU,
  author =       "M. Saqib Nawaz and Philippe Fournier-Viger and Unil
                 Yun and Youxi Wu and Wei Song",
  title =        "Mining High Utility Itemsets with {Hill} Climbing and
                 Simulated Annealing",
  journal =      j-TMIS,
  volume =       "13",
  number =       "1",
  pages =        "4:1--4:22",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3462636",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Jan 7 07:41:54 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3462636",
  abstract =     "High utility itemset mining (HUIM) is the task of
                 finding all items set, purchased together, that
                 generate a high profit in a transaction database. In
                 the past, several algorithms have been developed to
                 mine high utility itemsets (HUIs). However, most of
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "4",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Niu:2022:CMT,
  author =       "Shuteng Niu and Yushan Jiang and Bowen Chen and Jian
                 Wang and Yongxin Liu and Houbing Song",
  title =        "Cross-Modality Transfer Learning for Image-Text
                 Information Management",
  journal =      j-TMIS,
  volume =       "13",
  number =       "1",
  pages =        "5:1--5:14",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3464324",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Jan 7 07:41:54 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3464324",
  abstract =     "In the past decades, information from all kinds of
                 data has been on a rapid increase. With
                 state-of-the-art performance, machine learning
                 algorithms have been beneficial for information
                 management. However, insufficient supervised training
                 data is still \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "5",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Chen:2022:ABV,
  author =       "Mu-Yen Chen and Min-Hsuan Fan and Li-Xiang Huang",
  title =        "{AI}-Based Vehicular Network toward {6G} and {IoT}:
                 Deep Learning Approaches",
  journal =      j-TMIS,
  volume =       "13",
  number =       "1",
  pages =        "6:1--6:12",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3466691",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Jan 7 07:41:54 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3466691",
  abstract =     "In recent years, vehicular networks have become
                 increasingly large, heterogeneous, and dynamic, making
                 it difficult to meet strict requirements of ultralow
                 latency, high reliability, high security, and massive
                 connections for next generation (6G) \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "6",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Lv:2022:NML,
  author =       "Zhihan Lv and Ranran Lou and Hailin Feng and Dongliang
                 Chen and Haibin Lv",
  title =        "Novel Machine Learning for Big Data Analytics in
                 Intelligent Support Information Management Systems",
  journal =      j-TMIS,
  volume =       "13",
  number =       "1",
  pages =        "7:1--7:21",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3469890",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Jan 7 07:41:54 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3469890",
  abstract =     "Two-dimensional$^1$ arrays of bi-component structures
                 made of cobalt and permalloy elliptical dots with
                 thickness of 25 nm, length 1 mm and width of 225 nm,
                 have been prepared by a self-aligned shadow deposition
                 technique. Brillouin light scattering has been
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "7",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Kumar:2022:DBP,
  author =       "Ankit Kumar and Abhishek Kumar and Ali Kashif Bashir
                 and Mamoon Rashid and V. D. Ambeth Kumar and Rupak
                 Kharel",
  title =        "Distance Based Pattern Driven Mining for Outlier
                 Detection in High Dimensional Big Dataset",
  journal =      j-TMIS,
  volume =       "13",
  number =       "1",
  pages =        "8:1--8:17",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3469891",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Jan 7 07:41:54 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3469891",
  abstract =     "Detection of outliers or anomalies is one of the vital
                 issues in pattern-driven data mining. Outlier detection
                 detects the inconsistent behavior of individual
                 objects. It is an important sector in the data mining
                 field with several different applications \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "8",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Chowdhury:2022:NAM,
  author =       "Mohammad Ehsan Shahmi Chowdhury and Chowdhury Farhan
                 Ahmed and Carson K. Leung",
  title =        "A New Approach for Mining Correlated Frequent
                 Subgraphs",
  journal =      j-TMIS,
  volume =       "13",
  number =       "1",
  pages =        "9:1--9:28",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3473042",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Jan 7 07:41:54 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3473042",
  abstract =     "Nowadays graphical datasets are having a vast amount
                 of applications. As a result, graph mining-mining graph
                 datasets to extract frequent subgraphs-has proven to be
                 crucial in numerous aspects. It is important to perform
                 correlation analysis among the \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "9",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Wen:2022:KFA,
  author =       "Bo Wen and Paul Jen-Hwa Hu and Mohammadreza Ebrahimi
                 and Hsinchun Chen",
  title =        "Key Factors Affecting User Adoption of Open-Access
                 Data Repositories in Intelligence and Security
                 Informatics: an Affordance Perspective",
  journal =      j-TMIS,
  volume =       "13",
  number =       "1",
  pages =        "10:1--10:24",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3460823",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Jan 7 07:41:54 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3460823",
  abstract =     "Rich, diverse cybersecurity data are critical for
                 efforts by the intelligence and security informatics
                 (ISI) community. Although open-access data repositories
                 (OADRs) provide tremendous benefits for ISI researchers
                 and practitioners, determinants of their \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "10",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Elkoumy:2022:PCP,
  author =       "Gamal Elkoumy and Stephan A. Fahrenkrog-Petersen and
                 Mohammadreza Fani Sani and Agnes Koschmider and Felix
                 Mannhardt and Saskia Nu{\~n}ez Von Voigt and Majid
                 Rafiei and Leopold {Von Waldthausen}",
  title =        "Privacy and Confidentiality in Process Mining: Threats
                 and Research Challenges",
  journal =      j-TMIS,
  volume =       "13",
  number =       "1",
  pages =        "11:1--11:17",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3468877",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Jan 7 07:41:54 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3468877",
  abstract =     "Privacy and confidentiality are very important
                 prerequisites for applying process mining to comply
                 with regulations and keep company secrets. This article
                 provides a foundation for future research on
                 privacy-preserving and confidential process mining
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "11",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Sun:2022:DAM,
  author =       "Bo Sun and Takeshi Takahashi and Tao Ban and Daisuke
                 Inoue",
  title =        "Detecting {Android} Malware and Classifying Its
                 Families in Large-scale Datasets",
  journal =      j-TMIS,
  volume =       "13",
  number =       "2",
  pages =        "12:1--12:21",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3464323",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Mar 25 07:15:03 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3464323",
  abstract =     "To relieve the burden of security analysts, Android
                 malware detection and its family classification need to
                 be automated. There are many previous works focusing on
                 using machine (or deep) learning technology to tackle
                 these two important issues, but as \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "12",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Marshall:2022:MLS,
  author =       "Byron Marshall and Michael Curry and Robert E.
                 Crossler and John Correia",
  title =        "Machine Learning and Survey-based Predictors of
                 {InfoSec} Non-Compliance",
  journal =      j-TMIS,
  volume =       "13",
  number =       "2",
  pages =        "13:1--13:20",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3466689",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Mar 25 07:15:03 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3466689",
  abstract =     "Survey items developed in behavioral Information
                 Security (InfoSec) research should be practically
                 useful in identifying individuals who are likely to
                 create risk by failing to comply with InfoSec guidance.
                 The literature shows that attitudes, beliefs,
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "13",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Xie:2022:RPP,
  author =       "Jiaheng Xie and Bin Zhang and Jian Ma and Daniel Zeng
                 and Jenny Lo-Ciganic",
  title =        "Readmission Prediction for Patients with Heterogeneous
                 Medical History: a Trajectory-Based Deep Learning
                 Approach",
  journal =      j-TMIS,
  volume =       "13",
  number =       "2",
  pages =        "14:1--14:27",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3468780",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Mar 25 07:15:03 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3468780",
  abstract =     "Hospital readmission refers to the situation where a
                 patient is re-hospitalized with the same primary
                 diagnosis within a specific time interval after
                 discharge. Hospital readmission causes \$26 billion
                 preventable expenses to the U.S. health systems
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "14",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{He:2022:MAC,
  author =       "Luo He and Hongyan Liu and Yinghui Yang and Bei Wang",
  title =        "A Multi-attention Collaborative Deep Learning Approach
                 for Blood Pressure Prediction",
  journal =      j-TMIS,
  volume =       "13",
  number =       "2",
  pages =        "15:1--15:20",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3471571",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Mar 25 07:15:03 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3471571",
  abstract =     "We develop a deep learning model based on Long
                 Short-term Memory (LSTM) to predict blood pressure
                 based on a unique data set collected from physical
                 examination centers capturing comprehensive multi-year
                 physical examination and lab results. In the Multi-.
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "15",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Tang:2022:QLW,
  author =       "Yan Tang and Weilong Cui and Jianwen Su",
  title =        "A Query Language for Workflow Logs",
  journal =      j-TMIS,
  volume =       "13",
  number =       "2",
  pages =        "16:1--16:28",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3482968",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Mar 25 07:15:03 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3482968",
  abstract =     "A business process (workflow) is an assembly of tasks
                 to accomplish a business goal. Real-world workflow
                 models often demanded to change due to new laws and
                 policies, changes in the environment, and so on. To
                 understand the inner workings of a business \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "16",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Huang:2022:IMA,
  author =       "Shi Ming Huang and David C. Yen and Ting Jyun Yan and
                 Yi Ting Yang",
  title =        "An Intelligent Mechanism to Automatically Discover
                 Emerging Technology Trends: Exploring Regulatory
                 Technology",
  journal =      j-TMIS,
  volume =       "13",
  number =       "2",
  pages =        "17:1--17:29",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3485187",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Mar 25 07:15:03 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3485187",
  abstract =     "Technology trend analysis uses data relevant to
                 historical performance and extrapolates it to estimate
                 and assess the future potential of technology. Such
                 analysis is used to analyze emerging technologies or
                 predict the growing markets that influence the
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "17",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Miksa:2022:ARD,
  author =       "Tomasz Miksa and Simon Oblasser and Andreas Rauber",
  title =        "Automating Research Data Management Using
                 Machine-Actionable Data Management Plans",
  journal =      j-TMIS,
  volume =       "13",
  number =       "2",
  pages =        "18:1--18:22",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3490396",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Mar 25 07:15:03 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3490396",
  abstract =     "Many research funders mandate researchers to create
                 and maintain data management plans (DMPs) for research
                 projects that describe how research data is managed to
                 ensure its reusability. A DMP, being a static textual
                 document, is difficult to act upon and \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "18",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Li:2022:IBS,
  author =       "Guangrui (Kayla) Li and Mike K. P. So and Kar Yan
                 Tam",
  title =        "Identifying the Big Shots --- a Quantile-Matching Way
                 in the Big Data Context",
  journal =      j-TMIS,
  volume =       "13",
  number =       "2",
  pages =        "19:1--19:30",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3490395",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Mar 25 07:15:03 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3490395",
  abstract =     "The prevalence of big data has raised significant
                 epistemological concerns in information systems
                 research. This study addresses two of them-the deflated
                 p -value problem and the role of explanation and
                 prediction. To address the deflated p -value problem,
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "19",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Wu:2022:EST,
  author =       "Xindong Wu and Xingquan Zhu and Minghui Wu",
  title =        "The Evolution of Search: Three Computing Paradigms",
  journal =      j-TMIS,
  volume =       "13",
  number =       "2",
  pages =        "20:1--20:20",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3495214",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Mar 25 07:15:03 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3495214",
  abstract =     "Search is probably the most common activity that
                 humans conduct all the time. A search target can be a
                 concrete item (with a yes or no answer and location
                 information), an abstract concept (such as the most
                 important information on the Web about Xindong
                 \ldots{}).",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "20",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Zhang:2022:CDW,
  author =       "Ning Zhang and Mohammadreza Ebrahimi and Weifeng Li
                 and Hsinchun Chen",
  title =        "Counteracting Dark {Web} Text-Based {CAPTCHA} with
                 Generative Adversarial Learning for Proactive Cyber
                 Threat Intelligence",
  journal =      j-TMIS,
  volume =       "13",
  number =       "2",
  pages =        "21:1--21:21",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3505226",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Mar 25 07:15:03 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3505226",
  abstract =     "Automated monitoring of dark web (DW) platforms on a
                 large scale is the first step toward developing
                 proactive Cyber Threat Intelligence (CTI). While there
                 are efficient methods for collecting data from the
                 surface web, large-scale dark web data \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "21",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Werder:2022:EDP,
  author =       "Karl Werder and Balasubramaniam Ramesh and Rongen
                 (Sophia) Zhang",
  title =        "Establishing Data Provenance for Responsible
                 Artificial Intelligence Systems",
  journal =      j-TMIS,
  volume =       "13",
  number =       "2",
  pages =        "22:1--22:23",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3503488",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Fri Mar 25 07:15:03 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3503488",
  abstract =     "Data provenance, a record that describes the origins
                 and processing of data, offers new promises in the
                 increasingly important role of artificial intelligence
                 (AI)-based systems in guiding human decision making. To
                 avoid disastrous outcomes that can \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "22",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Lin:2022:ISI,
  author =       "Jerry Chun-Wei Lin and Nachiketa Sahoo and Gautam
                 Srivastava and Weiping Ding",
  title =        "Introduction to the Special Issue on Pattern-Driven
                 Mining, Analytics, and Prediction for Decision Making,
                 {Part II}",
  journal =      j-TMIS,
  volume =       "13",
  number =       "3",
  pages =        "23:1--23:3",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3512468",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Jun 2 07:44:18 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3512468",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "23",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Ebrahimi:2022:QCS,
  author =       "Maryam Ebrahimi and Mohammad Hesam Tadayon and
                 Mohammad Sayad Haghighi and Alireza Jolfaei",
  title =        "A Quantitative Comparative Study of Data-oriented
                 Trust Management Schemes in {Internet of Things}",
  journal =      j-TMIS,
  volume =       "13",
  number =       "3",
  pages =        "24:1--24:30",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3476248",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Jun 2 07:44:18 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3476248",
  abstract =     "In the Internet of Things (IoT) paradigm, all entities
                 in the IoT network, whether home users or industrial
                 things, receive data from other things to make
                 decisions. However, in the decentralized,
                 heterogeneous, and rapidly changing IoT network with
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "24",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Wu:2022:OMS,
  author =       "Youxi Wu and Xiaohui Wang and Yan Li and Lei Guo and
                 Zhao Li and Ji Zhang and Xindong Wu",
  title =        "{OWSP-Miner}: Self-adaptive One-off Weak-gap Strong
                 Pattern Mining",
  journal =      j-TMIS,
  volume =       "13",
  number =       "3",
  pages =        "25:1--25:23",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3476247",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Jun 2 07:44:18 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3476247",
  abstract =     "Gap constraint sequential pattern mining (SPM), as a
                 kind of repetitive SPM, can avoid mining too many
                 useless patterns. However, this method is difficult for
                 users to set a suitable gap without prior knowledge and
                 each character is considered to have the \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "25",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Gao:2022:FEH,
  author =       "Yuan Gao and Laurence T. Yang and Yaliang Zhao and
                 Jing Yang",
  title =        "Feature Extraction of High-dimensional Data Based on
                 {J-HOSVD} for Cyber-Physical-Social Systems",
  journal =      j-TMIS,
  volume =       "13",
  number =       "3",
  pages =        "26:1--26:21",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3483448",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Jun 2 07:44:18 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3483448",
  abstract =     "With the further integration of Cyber-Physical-Social
                 systems (CPSSs), there is explosive growth of the data
                 in CPSSs. How to discover effective information or
                 knowledge from CPSSs big data and provide support for
                 subsequent learning tasks has become a \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "26",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Hsieh:2022:DFR,
  author =       "Hsun-Ping Hsieh and Fandel Lin and Nai-Yu Chen and
                 Tzu-Hsin Yang",
  title =        "A Decision Framework to Recommend Cruising Locations
                 for Taxi Drivers under the Constraint of Booking
                 Information",
  journal =      j-TMIS,
  volume =       "13",
  number =       "3",
  pages =        "27:1--27:30",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3490687",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Jun 2 07:44:18 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3490687",
  abstract =     "As the demand for taxi reservation services has
                 increased, increasing the income of taxi drivers with
                 advanced services has attracted attention. In this
                 article, we propose a path decision framework that
                 considers real-time spatial-temporal predictions
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "27",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Pika:2022:CBP,
  author =       "Anastasiia Pika and Chun Ouyang and Arthur H. M. ter
                 Hofstede",
  title =        "Configurable Batch-Processing Discovery from Event
                 Logs",
  journal =      j-TMIS,
  volume =       "13",
  number =       "3",
  pages =        "28:1--28:25",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3490394",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Jun 2 07:44:18 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3490394",
  abstract =     "Batch processing is used in many production and
                 service processes and can help achieve efficiencies of
                 scale; however, it can also increase inventories and
                 introduce process delays. Before organizations can
                 develop good understanding about the effects of
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "28",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Rashid:2022:ADC,
  author =       "A. N. M. Bazlur Rashid and Mohiuddin Ahmed and Leslie
                 F. Sikos and Paul Haskell-Dowland",
  title =        "Anomaly Detection in Cybersecurity Datasets via
                 Cooperative Co-evolution-based Feature Selection",
  journal =      j-TMIS,
  volume =       "13",
  number =       "3",
  pages =        "29:1--29:39",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3495165",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Jun 2 07:44:18 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3495165",
  abstract =     "Anomaly detection from Big Cybersecurity Datasets is
                 very important; however, this is a very challenging and
                 computationally expensive task. Feature selection (FS)
                 is an approach to remove irrelevant and redundant
                 features and select a subset of features, \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "29",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Liu:2022:EFP,
  author =       "Xin Liu and Liang Zheng and Weishan Zhang and Jiehan
                 Zhou and Shuai Cao and Shaowen Yu",
  title =        "An Evolutive Frequent Pattern Tree-based Incremental
                 Knowledge Discovery Algorithm",
  journal =      j-TMIS,
  volume =       "13",
  number =       "3",
  pages =        "30:1--30:20",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3495213",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Jun 2 07:44:18 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3495213",
  abstract =     "To understand current situation in specific scenarios,
                 valuable knowledge should be mined from both historical
                 data and emerging new data. However, most existing
                 algorithms take the historical data and the emerging
                 data as a whole and periodically repeat \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "30",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Corradini:2022:ETA,
  author =       "Flavio Corradini and Alessandro Marcelletti and Andrea
                 Morichetta and Andrea Polini and Barbara Re and
                 Francesco Tiezzi",
  title =        "Engineering Trustable and Auditable Choreography-based
                 Systems Using Blockchain",
  journal =      j-TMIS,
  volume =       "13",
  number =       "3",
  pages =        "31:1--31:53",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3505225",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Jun 2 07:44:18 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3505225",
  abstract =     "A key challenge in engineering distributed systems
                 consists in the integration into their development of a
                 decentralised infrastructure allowing the system
                 participants to trust each other. In this article, we
                 face such a challenge by proposing a model-. \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "31",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Yeo:2022:HCD,
  author =       "M. Lisa Yeo and Erik Rolland and Jacquelyn Rees Ulmer
                 and Raymond A. Patterson",
  title =        "How Customer Demand Reactions Impact Technology
                 Innovation and Security",
  journal =      j-TMIS,
  volume =       "13",
  number =       "3",
  pages =        "32:1--32:17",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3505227",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Jun 2 07:44:18 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3505227",
  abstract =     "Innovation is a very important concern for both
                 managers and governmental policy makers. There is an
                 important interplay between security and technology
                 innovation that is largely unrecognized in the
                 literature. This research considers the case where
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "32",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Ma:2022:SME,
  author =       "Wanlun Ma and Xiangyu Hu and Chao Chen and Sheng Wen
                 and Kkwang Raymond Choo and Yang Xiang",
  title =        "Social Media Event Prediction using {DNN} with
                 Feedback Mechanism",
  journal =      j-TMIS,
  volume =       "13",
  number =       "3",
  pages =        "33:1--33:24",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3522759",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Jun 2 07:44:18 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3522759",
  abstract =     "Online social networks (OSNs) are a rich source of
                 information, and the data (including user-generated
                 content) can be mined to facilitate real-world event
                 prediction. However, the dynamic nature of OSNs and the
                 fast-pace nature of social events or hot \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "33",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Adomavicius:2022:IBE,
  author =       "Gediminas Adomavicius and Mochen Yang",
  title =        "Integrating Behavioral, Economic, and Technical
                 Insights to Understand and Address Algorithmic Bias: a
                 Human-Centric Perspective",
  journal =      j-TMIS,
  volume =       "13",
  number =       "3",
  pages =        "34:1--34:27",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3519420",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Jun 2 07:44:18 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3519420",
  abstract =     "Many important decisions are increasingly being made
                 with the help of information systems that use
                 artificial intelligence and machine learning models.
                 These computational models are designed to discover
                 useful patterns from large amounts of data, which
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "34",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Chen:2022:ISI,
  author =       "Mu-Yen Chen and Bhavani Thuraisingham and Erol
                 Egrioglu and Jose {De Jesus Rubio}",
  title =        "Introduction to the Special Issue on Smart Systems for
                 {Industry 4.0} and {IoT}",
  journal =      j-TMIS,
  volume =       "13",
  number =       "4",
  pages =        "35:1--35:??",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3583985",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:44 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3583985",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "35",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Romero:2022:IDP,
  author =       "Esteban Elias Romero and Carlos David Camacho and
                 Carlos Enrique Montenegro and {\'O}scar Esneider Acosta
                 and Rub{\'e}n Gonz{\'a}lez Crespo and Elvis Eduardo
                 Gaona and Marcelo Herrera Mart{\'\i}nez",
  title =        "Integration of {DevOps} Practices on a Noise Monitor
                 System with {CircleCI} and {Terraform}",
  journal =      j-TMIS,
  volume =       "13",
  number =       "4",
  pages =        "36:1--36:??",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3505228",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:44 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3505228",
  abstract =     "Lowering pollution levels is one of the main
                 principles of Sustainable Development goals dictated by
                 the United Nations. Consequently, developments on noise
                 monitoring contribute in great manner to this purpose,
                 since they give the opportunity to \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "36",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Ren:2022:AMD,
  author =       "Bin Ren and Yuquiang Chen and Fujie Wang",
  title =        "Application Massive Data Processing Platform for Smart
                 Manufacturing Based on Optimization of Data Storage",
  journal =      j-TMIS,
  volume =       "13",
  number =       "4",
  pages =        "37:1--37:??",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3508395",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:44 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3508395",
  abstract =     "The aim of smart manufacturing is to reduce manpower
                 requirements of the production line by applying
                 technology of huge amounts of data to the manufacturing
                 industry. Smart manufacturing is also called Industry
                 4.0, and the platform for processing huge \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "37",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Liu:2022:PDX,
  author =       "Genggeng Liu and Yuhan Zhu and Saijuan Xu and Hao Tang
                 and Yeh-Cheng Chen",
  title =        "Performance-Driven {X}-Architecture Routing Algorithm
                 for Artificial Intelligence Chip Design in Smart
                 Manufacturing",
  journal =      j-TMIS,
  volume =       "13",
  number =       "4",
  pages =        "38:1--38:??",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3519422",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:44 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3519422",
  abstract =     "The new 7-nm Artificial Intelligence (AI) chip is an
                 important milestone recently announced by the IBM
                 research team, with a very important optimization goal
                 of performance. This chip technology can be extended to
                 various business scenarios in the \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "38",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Lv:2022:CIS,
  author =       "Zhihan Lv and Dongliang Chen and Hailin Feng and Amit
                 Kumar Singh and Wei Wei and Haibin Lv",
  title =        "Computational Intelligence in Security of Digital
                 Twins Big Graphic Data in Cyber-physical Systems of
                 Smart Cities",
  journal =      j-TMIS,
  volume =       "13",
  number =       "4",
  pages =        "39:1--39:??",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3522760",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:44 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3522760",
  abstract =     "This investigation focuses on the application of
                 computational intelligence to the security of Digital
                 Twins (DTs) graphic data of the Cyber-physical System
                 (CPS). The intricate and diverse physical space of CPS
                 in the smart city is mapped in virtual \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "39",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Chen:2022:CIM,
  author =       "Rongli Chen and Xiaozhong Chen and Lei Wang and
                 Jianxin Li",
  title =        "The Core Industry Manufacturing Process of Electronics
                 Assembly Based on Smart Manufacturing",
  journal =      j-TMIS,
  volume =       "13",
  number =       "4",
  pages =        "40:1--40:??",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3529098",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:44 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3529098",
  abstract =     "This research takes a case study approach to show the
                 development of a diverse adoption and product strategy
                 distinct from the core manufacturing industry process.
                 It explains the development status in all aspects of
                 smart manufacturing, via the example \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "40",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Liu:2022:TSC,
  author =       "Genggeng Liu and Ruping Zhou and Saijuan Xu and Yuhan
                 Zhu and Wenzhong Guo and Yeh-Cheng Chen and Guolong
                 Chen",
  title =        "Two-Stage Competitive Particle Swarm Optimization
                 Based Timing-Driven {X}-Routing for {IC} Design Under
                 Smart Manufacturing",
  journal =      j-TMIS,
  volume =       "13",
  number =       "4",
  pages =        "41:1--41:??",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3531328",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:44 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3531328",
  abstract =     "As timing delay becomes a critical issue in chip
                 performance, there is a burning desire for IC design
                 under smart manufacturing to optimize the delay. As the
                 best connection model for multi-terminal nets, the
                 wirelength and the maximum source-to-sink \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "41",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Du:2022:SWI,
  author =       "Xin Du and Songtao Tang and Zhihui Lu and Keke Gai and
                 Jie Wu and Patrick C. K. Hung",
  title =        "Scientific Workflows in {IoT} Environments: a Data
                 Placement Strategy Based on Heterogeneous Edge-Cloud
                 Computing",
  journal =      j-TMIS,
  volume =       "13",
  number =       "4",
  pages =        "42:1--42:??",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3531327",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:44 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3531327",
  abstract =     "In Industry 4.0 and Internet of Things (IoT)
                 environments, the heterogeneous edge-cloud computing
                 paradigm can provide a more proper solution to deploy
                 scientific workflows compared to cloud computing or
                 other traditional distributed computing. Owing to
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "42",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Lin:2022:SSJ,
  author =       "Qi Lin and Wensheng Gan and Yongdong Wu and Jiahui
                 Chen and Chien-Ming Chen",
  title =        "Smart System: Joint Utility and Frequency for Pattern
                 Classification",
  journal =      j-TMIS,
  volume =       "13",
  number =       "4",
  pages =        "43:1--43:??",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3531480",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:44 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3531480",
  abstract =     "Nowadays, the environments of smart systems for
                 Industry 4.0 and Internet of Things are experiencing
                 fast industrial upgrading. Big data technologies such
                 as design making, event detection, and classification
                 are developed to help manufacturing \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "43",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Parameswarath:2022:UEP,
  author =       "Rohini Poolat Parameswarath and Prosanta Gope and
                 Biplab Sikdar",
  title =        "User-empowered Privacy-preserving Authentication
                 Protocol for Electric Vehicle Charging Based on
                 Decentralized Identity and Verifiable Credential",
  journal =      j-TMIS,
  volume =       "13",
  number =       "4",
  pages =        "44:1--44:??",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3532869",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:44 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3532869",
  abstract =     "The use of Electric Vehicles (EVs) has been gaining
                 traction in recent years due to various reasons. While
                 charging their EVs, users expose their identity and
                 personal details, and an adversary being able to
                 identify and track where users charge their EVs
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "44",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Nong:2022:ARC,
  author =       "Mengxin Nong and Lingfeng Huang and Mingtao Liu",
  title =        "Allocation of Resources for Cloud Survivability in
                 Smart Manufacturing",
  journal =      j-TMIS,
  volume =       "13",
  number =       "4",
  pages =        "45:1--45:??",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3533701",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:44 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3533701",
  abstract =     "With the development of virtualization technology,
                 cloud computing has emerged as a powerful and flexible
                 platform for various services such as online trading.
                 However, there are concerns about the survivability of
                 cloud services in smart manufacturing. \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "45",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Ahmed:2022:HEA,
  author =       "Usman Ahmed and Jerry Chun-Wei Lin and Gautam
                 Srivastava",
  title =        "Heterogeneous Energy-aware Load Balancing for
                 {Industry 4.0} and {IoT} Environments",
  journal =      j-TMIS,
  volume =       "13",
  number =       "4",
  pages =        "46:1--46:??",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3543859",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:44 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3543859",
  abstract =     "With the improvement of global infrastructure,
                 Cyber-Physical Systems (CPS) have become an important
                 component of Industry 4.0. Both the application as well
                 as the machine work together to improve the task of
                 interdependencies. Machine learning methods in
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "46",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Chen:2022:RUB,
  author =       "Yu-Chia Chen and Sin-Ye Jhong and Chih-Hsien Hsia",
  title =        "Roadside Unit-based Unknown Object Detection in
                 Adverse Weather Conditions for Smart {Internet of
                 Vehicles}",
  journal =      j-TMIS,
  volume =       "13",
  number =       "4",
  pages =        "47:1--47:??",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3554923",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:44 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3554923",
  abstract =     "For Internet of Vehicles applications, reliable
                 autonomous driving systems usually perform the majority
                 of their computations on the cloud due to the limited
                 computing power of edge devices. The communication
                 delay between cloud platforms and edge devices,.
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "47",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Janiesch:2023:AUP,
  author =       "Christian Janiesch and Marcus Fischer and Florian
                 Imgrund and Adrian Hofmann and Axel Winkelmann",
  title =        "An Architecture Using Payment Channel Networks for
                 Blockchain-based {Wi-Fi} Sharing",
  journal =      j-TMIS,
  volume =       "14",
  number =       "1",
  pages =        "1:1--1:??",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3529097",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:45 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3529097",
  abstract =     "Enabling Internet access while taking load of mobile
                 networks, the concept of Wi-Fi sharing holds much
                 potential. While trust-based concepts require a trusted
                 intermediary and cannot prevent malicious behavior, for
                 example, conducted through fake profiles,. \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "1",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Morid:2023:TSP,
  author =       "Mohammad Amin Morid and Olivia R. Liu Sheng and Joseph
                 Dunbar",
  title =        "Time Series Prediction Using Deep Learning Methods in
                 Healthcare",
  journal =      j-TMIS,
  volume =       "14",
  number =       "1",
  pages =        "2:1--2:??",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3531326",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:45 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3531326",
  abstract =     "Traditional machine learning methods face unique
                 challenges when applied to healthcare predictive
                 analytics. The high-dimensional nature of healthcare
                 data necessitates labor-intensive and time-consuming
                 processes when selecting an appropriate set of
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "2",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Zhai:2023:RNB,
  author =       "Shuang (Sophie) Zhai and Zhu (Drew) Zhang",
  title =        "Read the News, Not the Books: Forecasting Firms'
                 Long-term Financial Performance via Deep Text Mining",
  journal =      j-TMIS,
  volume =       "14",
  number =       "1",
  pages =        "3:1--3:??",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3533018",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:45 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3533018",
  abstract =     "In this paper, we show textual data from firm-related
                 events in news articles can effectively predict various
                 firm financial ratios, with or without historical
                 financial ratios. We exploit state-of-the-art neural
                 architectures, including pseudo-event \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "3",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Ameri:2023:DNI,
  author =       "Kimia Ameri and Michael Hempel and Hamid Sharif and
                 Juan Lopez and Kalyan Perumalla",
  title =        "Design of a Novel Information System for
                 Semi-automated Management of Cybersecurity in
                 Industrial Control Systems",
  journal =      j-TMIS,
  volume =       "14",
  number =       "1",
  pages =        "4:1--4:??",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3546580",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:45 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3546580",
  abstract =     "There is an urgent need in many critical
                 infrastructure sectors, including the energy sector,
                 for attaining detailed insights into cybersecurity
                 features and compliance with cybersecurity requirements
                 related to their Operational Technology (OT) \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "4",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Joshi:2023:LNL,
  author =       "Amogh Manoj Joshi and Deepak Ranjan Nayak and
                 Dibyasundar Das and Yudong Zhang",
  title =        "{LiMS-Net}: a Lightweight Multi-Scale {CNN} for
                 {COVID-19} Detection from Chest {CT} Scans",
  journal =      j-TMIS,
  volume =       "14",
  number =       "1",
  pages =        "5:1--5:??",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3551647",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:45 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3551647",
  abstract =     "Recent years have witnessed a rise in employing deep
                 learning methods, especially convolutional neural
                 networks (CNNs) for detection of COVID-19 cases using
                 chest CT scans. Most of the state-of-the-art models
                 demand a huge amount of parameters which often
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "5",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Kucklick:2023:TAI,
  author =       "Jan-Peter Kucklick and Oliver M{\"u}ller",
  title =        "Tackling the Accuracy-Interpretability Trade-off:
                 Interpretable Deep Learning Models for Satellite
                 Image-based Real Estate Appraisal",
  journal =      j-TMIS,
  volume =       "14",
  number =       "1",
  pages =        "6:1--6:??",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3567430",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:45 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3567430",
  abstract =     "Deep learning models fuel many modern decision support
                 systems, because they typically provide high predictive
                 performance. Among other domains, deep learning is used
                 in real-estate appraisal, where it allows extending the
                 analysis from hard facts only \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "6",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Akello:2023:BUC,
  author =       "Patricia Akello and Naga Vemprala and Nicole Lang
                 Beebe and Kim-Kwang Raymond Choo",
  title =        "Blockchain Use Case in Ballistics and Crime Gun
                 Tracing and Intelligence: Toward Overcoming Gun
                 Violence",
  journal =      j-TMIS,
  volume =       "14",
  number =       "1",
  pages =        "7:1--7:??",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3571290",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:45 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3571290",
  abstract =     "In the United States and around the world, gun
                 violence has become a long-standing public safety
                 concern and a security threat, due to violent
                 gun-related crimes, injuries, and fatalities. Although
                 legislators and lawmakers have attempted to mitigate
                 its \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "7",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Chen:2023:ODD,
  author =       "Xue Chen and Cheng Wang and Qing Yang and Teng Hu and
                 Changjun Jiang",
  title =        "The Opportunity in Difficulty: a Dynamic Privacy
                 Budget Allocation Mechanism for Privacy-Preserving
                 Multi-dimensional Data Collection",
  journal =      j-TMIS,
  volume =       "14",
  number =       "1",
  pages =        "8:1--8:??",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3569944",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:45 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3569944",
  abstract =     "Data collection under local differential privacy (LDP)
                 has been gradually on the stage. Compared with the
                 implementation of LDP on the single attribute data
                 collection, that on multi-dimensional data faces great
                 challenges as follows: (1) Communication \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "8",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Hu:2023:RAH,
  author =       "Yixiang Hu and Xiaoheng Deng and Congxu Zhu and
                 Xuechen Chen and Laixin Chi",
  title =        "Resource Allocation for Heterogeneous Computing Tasks
                 in Wirelessly Powered {MEC}-enabled {IIOT} Systems",
  journal =      j-TMIS,
  volume =       "14",
  number =       "1",
  pages =        "9:1--9:??",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3571291",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:45 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3571291",
  abstract =     "Integrating wireless power transfer with mobile edge
                 computing (MEC) has become a powerful solution for
                 increasingly complicated and dynamic industrial
                 Internet of Things (IIOT) systems. However, the
                 traditional approaches overlooked the heterogeneity of
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "9",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Hevner:2023:RCD,
  author =       "Alan Hevner and Veda Storey",
  title =        "Research Challenges for the Design of Human-Artificial
                 Intelligence Systems ({HAIS})",
  journal =      j-TMIS,
  volume =       "14",
  number =       "1",
  pages =        "10:1--10:??",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3549547",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:45 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3549547",
  abstract =     "Artificial intelligence (AI) capabilities are
                 increasingly common components of all socio-technical
                 information systems that integrate human and machine
                 actions. The impacts of AI components on the design and
                 use of application systems are evolving \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "10",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Dumas:2023:AAB,
  author =       "Marlon Dumas and Fabiana Fournier and Lior Limonad and
                 Andrea Marrella and Marco Montali and Jana-Rebecca
                 Rehse and Rafael Accorsi and Diego Calvanese and
                 Giuseppe {De Giacomo} and Dirk Fahland and Avigdor Gal
                 and Marcello {La Rosa} and Hagen V{\"o}lzer and Ingo
                 Weber",
  title =        "{AI}-augmented Business Process Management Systems: a
                 Research Manifesto",
  journal =      j-TMIS,
  volume =       "14",
  number =       "1",
  pages =        "11:1--11:??",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3576047",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Thu Mar 9 08:04:45 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3576047",
  abstract =     "AI-augmented Business Process Management Systems
                 (ABPMSs) are an emerging class of process-aware
                 information systems, empowered by trustworthy AI
                 technology. An ABPMS enhances the execution of business
                 processes with the aim of making these processes more
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "11",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Leroy:2023:ISI,
  author =       "Gondy Leroy and Bengisu Tulu and Xiao Liu",
  title =        "Introduction to the Special Issue on Design and Data
                 Science Research in Healthcare",
  journal =      j-TMIS,
  volume =       "14",
  number =       "2",
  pages =        "12:1--12:??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3579646",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 27 07:09:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3579646",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "12",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Baucum:2023:OSU,
  author =       "Matt Baucum and Anahita Khojandi and Carole Myers and
                 Larry Kessler",
  title =        "Optimizing Substance Use Treatment Selection Using
                 Reinforcement Learning",
  journal =      j-TMIS,
  volume =       "14",
  number =       "2",
  pages =        "13:1--13:??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3563778",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 27 07:09:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3563778",
  abstract =     "Substance use disorder (SUD) exacts a substantial
                 economic and social cost in the United States, and it
                 is crucial for SUD treatment providers to match
                 patients with feasible, effective, and affordable
                 treatment plans. The availability of large SUD
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "13",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Bartenschlager:2023:CML,
  author =       "Christina C. Bartenschlager and Stefanie S. Ebel and
                 Sebastian Kling and Janne Vehreschild and Lutz T. Zabel
                 and Christoph D. Spinner and Andreas Schuler and Axel
                 R. Heller and Stefan Borgmann and Reinhard Hoffmann and
                 Siegbert Rieg and Helmut Messmann and Martin Hower and
                 Jens O. Brunner and Frank Hanses and Christoph
                 R{\"o}mmele",
  title =        "{COVIDAL}: a Machine Learning Classifier for Digital
                 {COVID-19} Diagnosis in {German} Hospitals",
  journal =      j-TMIS,
  volume =       "14",
  number =       "2",
  pages =        "14:1--14:??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3567431",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 27 07:09:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3567431",
  abstract =     "For the fight against the COVID-19 pandemic, it is
                 particularly important to map the course of infection,
                 in terms of patients who have currently tested
                 SARS-CoV-2 positive, as accurately as possible. In
                 hospitals, this is even more important because
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "14",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{vanderLinden:2023:MVD,
  author =       "Sanne van der Linden and Rita Sevastjanova and Mathias
                 Funk and Mennatallah El-Assady",
  title =        "{MediCoSpace}: Visual Decision-Support for
                 Doctor-Patient Consultations using Medical Concept
                 Spaces from {EHRs}",
  journal =      j-TMIS,
  volume =       "14",
  number =       "2",
  pages =        "15:1--15:??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3564275",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 27 07:09:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3564275",
  abstract =     "Healthcare systems are under pressure from an aging
                 population, rising costs, and increasingly complex
                 conditions and treatments. Although data are determined
                 to play a bigger role in how doctors diagnose and
                 prescribe treatments, they struggle due to a \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "15",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Fechner:2023:NIS,
  author =       "Pascal Fechner and Fabian K{\"o}nig and Wolfgang
                 Kratsch and Jannik Lockl and Maximilian R{\"o}glinger",
  title =        "Near-Infrared Spectroscopy for Bladder Monitoring: a
                 Machine Learning Approach",
  journal =      j-TMIS,
  volume =       "14",
  number =       "2",
  pages =        "16:1--16:??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3563779",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 27 07:09:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3563779",
  abstract =     "Patients living with neurogenic bladder dysfunction
                 can lose the sensation of their bladder filling. To
                 avoid over-distension of the urinary bladder and
                 prevent long-term damage to the urinary tract, the gold
                 standard treatment is clean intermittent \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "16",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Srinivasan:2023:EDM,
  author =       "Karthik Srinivasan and Jinhang Jiang",
  title =        "Examining Disease Multimorbidity in {U.S.} Hospital
                 Visits Before and During {COVID-19} Pandemic: a Graph
                 Analytics Approach",
  journal =      j-TMIS,
  volume =       "14",
  number =       "2",
  pages =        "17:1--17:??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3564274",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 27 07:09:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3564274",
  abstract =     "Enduring effects of the COVID-19 pandemic on
                 healthcare systems can be preempted by identifying
                 patterns in diseases recorded in hospital visits over
                 time. Disease multimorbidity or simultaneous occurrence
                 of multiple diseases is a growing global public
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "17",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Srinivasan:2023:HLS,
  author =       "Karthik Srinivasan and Faiz Currim and Sudha Ram",
  title =        "A Human-in-the-Loop Segmented Mixed-Effects Modeling
                 Method for Analyzing Wearables Data",
  journal =      j-TMIS,
  volume =       "14",
  number =       "2",
  pages =        "18:1--18:??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3564276",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 27 07:09:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3564276",
  abstract =     "Wearables are an important source of big data, as they
                 provide real-time high-resolution data logs of health
                 indicators of individuals. Higher-order associations
                 between pairs of variables is common in wearables data.
                 Representing higher-order association \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "18",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Chai:2023:MLC,
  author =       "Yidong Chai and Hongyan Liu and Jie Xu and Sagar
                 Samtani and Yuanchun Jiang and Haoxin Liu",
  title =        "A Multi-Label Classification with an Adversarial-Based
                 Denoising Autoencoder for Medical Image Annotation",
  journal =      j-TMIS,
  volume =       "14",
  number =       "2",
  pages =        "19:1--19:??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3561653",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 27 07:09:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3561653",
  abstract =     "Medical image annotation aims to automatically
                 describe the content of medical images. It helps
                 doctors to understand the content of medical images and
                 make better informed decisions like diagnoses. Existing
                 methods mainly follow the approach for natural
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "19",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Unger:2023:DNA,
  author =       "Moshe Unger and Pan Li and Sahana (Shahana) Sen and
                 Alexander Tuzhilin",
  title =        "Don't Need All Eggs in One Basket: Reconstructing
                 Composite Embeddings of Customers from
                 Individual-Domain Embeddings",
  journal =      j-TMIS,
  volume =       "14",
  number =       "2",
  pages =        "20:1--20:??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3578710",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 27 07:09:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3578710",
  abstract =     "Although building a 360-degree comprehensive view of a
                 customer has been a long-standing goal in marketing,
                 this challenge has not been successfully addressed in
                 many marketing applications because fractured customer
                 data stored across different ``silos'' \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "20",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Mishra:2023:EED,
  author =       "Rahul Mishra and Dharavath Ramesh and Salil S. Kanhere
                 and Damodar Reddy Edla",
  title =        "Enabling Efficient Deduplication and Secure
                 Decentralized Public Auditing for Cloud Storage: a
                 Redactable Blockchain Approach",
  journal =      j-TMIS,
  volume =       "14",
  number =       "3",
  pages =        "21:1--21:??",
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3578555",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Aug 30 12:00:07 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3578555",
  abstract =     "Public auditing and data deduplication are integral
                 considerations in providing efficient and secure cloud
                 storage services. Nevertheless, the traditional data
                 deduplication models \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "21",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Rubin:2023:UTA,
  author =       "Eran Rubin and Izak Benbasat",
  title =        "Using {Toulmin}'s Argumentation Model to Enhance Trust
                 in Analytics-Based Advice Giving Systems",
  journal =      j-TMIS,
  volume =       "14",
  number =       "3",
  pages =        "22:1--22:??",
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3580479",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Aug 30 12:00:07 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3580479",
  abstract =     "Ecommerce websites increasingly provide predictive
                 analytics-based advice (PAA), such as advice about
                 future potential price reductions. Establishing
                 consumer-trust in these \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "22",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Du:2023:IMK,
  author =       "Kelvin Du and Frank Xing and Erik Cambria",
  title =        "Incorporating Multiple Knowledge Sources for Targeted
                 Aspect-based Financial Sentiment Analysis",
  journal =      j-TMIS,
  volume =       "14",
  number =       "3",
  pages =        "23:1--23:??",
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3580480",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Aug 30 12:00:07 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3580480",
  abstract =     "Combining symbolic and subsymbolic methods has become
                 a promising strategy as research tasks in AI grow
                 increasingly complicated and require higher levels of
                 understanding. \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "23",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Chua:2023:SFD,
  author =       "Cecil Eng Huang Chua and Fred Niederman",
  title =        "Situational Factor Determinants of the Allocation of
                 Decision Rights to Edge Computers",
  journal =      j-TMIS,
  volume =       "14",
  number =       "3",
  pages =        "24:1--24:??",
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3582081",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Aug 30 12:00:07 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3582081",
  abstract =     "Internet of Things (IoT) designers frequently must
                 determine whether action-oriented decisions should be
                 made by edge computers or whether they should be made
                 only by \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "24",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Siering:2023:PPP,
  author =       "Michael Siering",
  title =        "Peer-to-Peer {(P2P)} Lending Risk Management:
                 Assessing Credit Risk on Social Lending Platforms Using
                 Textual Factors",
  journal =      j-TMIS,
  volume =       "14",
  number =       "3",
  pages =        "25:1--25:??",
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3589003",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Aug 30 12:00:07 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3589003",
  abstract =     "Peer-to-peer (P2P) lending platforms offer Internet
                 users the possibility to borrow money from peers
                 without the intervention of traditional financial
                 institutions. Due to \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "25",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Shen:2023:ECA,
  author =       "Dazhong Shen and Hengshu Zhu and Keli Xiao and Xi
                 Zhang and Hui Xiong",
  title =        "Exploiting Connections among Personality, Job
                 Position, and Work Behavior: Evidence from Joint
                 {Bayesian} Learning",
  journal =      j-TMIS,
  volume =       "14",
  number =       "3",
  pages =        "26:1--26:??",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3607875",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Sep 19 06:58:51 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3607875",
  abstract =     "Personality has been considered as a driving factor
                 for work engagement, which significantly affects
                 people's role performance at work. Although existing
                 research has \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "26",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Ang:2023:PER,
  author =       "Gary Ang and Zhiling Guo and Ee-Peng Lim",
  title =        "On Predicting {ESG} Ratings Using Dynamic Company
                 Networks",
  journal =      j-TMIS,
  volume =       "14",
  number =       "3",
  pages =        "27:1--27:??",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3607874",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Tue Sep 19 06:58:51 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3607874",
  abstract =     "Environmental, social and governance (ESG)
                 considerations play an increasingly important role due
                 to the growing focus on sustainability globally.
                 Entities, such as banks and \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "27",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Li:2023:ISI,
  author =       "Xin Li and Juhee Kwon and Balaji Padmanabhan and
                 Pengzhu Zhang",
  title =        "Introduction to the Special Issue on {IT}-enabled
                 Business Management and Decision Making in the (Post)
                 {Covid-19} Era",
  journal =      j-TMIS,
  volume =       "14",
  number =       "4",
  pages =        "28:1--28:??",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3627995",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Dec 13 11:34:23 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3627995",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "28",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Guo:2023:SDH,
  author =       "Tianjian Guo and Indranil Bardhan and Anjum Khurshid",
  title =        "Social Determinants of Health and {ER} Utilization:
                 Role of Information Integration during {COVID-19}",
  journal =      j-TMIS,
  volume =       "14",
  number =       "4",
  pages =        "29:1--29:??",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3583077",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Dec 13 11:34:23 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3583077",
  abstract =     "Emergency room (ER) admissions are the front door for
                 the utilization of a community's health resources and
                 serve as a valuable proxy for a community health
                 system's capacity. \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "29",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Killoran:2023:IIC,
  author =       "Jayson Andrew Killoran and Tracy A. Jenkin and Jasmin
                 Manseau",
  title =        "{ICT} Interactions and {COVID-19} --- a Theorization
                 Across Two Pandemic Waves",
  journal =      j-TMIS,
  volume =       "14",
  number =       "4",
  pages =        "30:1--30:??",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3597938",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Dec 13 11:34:23 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3597938",
  abstract =     "The COVID-19 pandemic instigated the rapid shift to
                 remote work and virtual interactions, constituting a
                 new normal of professional interaction over information
                 and \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "30",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Pilato:2023:MSS,
  author =       "Giovanni Pilato and Fabio Persia and Mouzhi Ge and
                 Theodoros Chondrogiannis and Daniela D'Auria",
  title =        "A Modular Social Sensing System for Personalized
                 Orienteering in the {COVID-19} Era",
  journal =      j-TMIS,
  volume =       "14",
  number =       "4",
  pages =        "31:1--31:??",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3615359",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Dec 13 11:34:23 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3615359",
  abstract =     "Orienteering or itinerary planning algorithms in
                 tourism are used to optimize travel routes by
                 considering user preference and other constraints, such
                 as time budget or \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "31",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Zeng:2023:DAO,
  author =       "Xiao Zeng and David Ji and Dimple R. Thadani and
                 Boying Li and Xiaodie Pu and Zhao Cai and Patrick Y. K.
                 Chau",
  title =        "Disentangling Affordances of Online Collaboration
                 Tools for Mutual Aid in Emergencies: Insights from the
                 {COVID-19} Lockdown",
  journal =      j-TMIS,
  volume =       "14",
  number =       "4",
  pages =        "32:1--32:??",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3593056",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Dec 13 11:34:23 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3593056",
  abstract =     "With the uncertain trajectory of COVID-19 conditions
                 worldwide, there lies the potential for emergencies to
                 arise, abruptly yielding mass social and economic
                 disruption. Gaining \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "32",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Lo:2024:NMG,
  author =       "Pei-Chi Lo and Ee-Peng Lim",
  title =        "Non-monotonic Generation of Knowledge Paths for
                 Context Understanding",
  journal =      j-TMIS,
  volume =       "15",
  number =       "1",
  pages =        "1:1--1:??",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3627994",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 25 11:34:33 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3627994",
  abstract =     "Knowledge graphs can be used to enhance text search
                 and access by augmenting textual content with relevant
                 background knowledge. While many large knowledge graphs
                 are available, \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "1",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Aouachria:2024:PMM,
  author =       "Moufida Aouachria and Abderrahmane Leshob and
                 Abdessamed R{\'e}da Ghomari and Mustapha Aouache",
  title =        "A Process Mining Method for Inter-organizational
                 Business Process Integration",
  journal =      j-TMIS,
  volume =       "15",
  number =       "1",
  pages =        "2:1--2:??",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3638062",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 25 11:34:33 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3638062",
  abstract =     "Business process integration (BPI) allows
                 organizations to connect and automate their business
                 processes in order to deliver the right economic
                 resources at the right time, \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "2",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Pytel:2024:DDT,
  author =       "Norman Pytel and Christian Ziegler and Axel
                 Winkelmann",
  title =        "From Dissonance to Dialogue: a Token-Based Approach to
                 Bridge the Gap Between Manufacturers and Customers",
  journal =      j-TMIS,
  volume =       "15",
  number =       "1",
  pages =        "3:1--3:??",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3639058",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 25 11:34:33 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3639058",
  abstract =     "This article presents a novel token-based recall
                 communication system, which integrates Enterprise
                 Resource Planning (ERP) systems and blockchain
                 technology to enhance \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "3",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Storey:2024:DSI,
  author =       "Veda C. Storey and Richard Baskerville",
  title =        "Design with {Simon}'s Inner and Outer Environments:
                 Theoretical Foundations for Design Science Research
                 Methods for Digital Science",
  journal =      j-TMIS,
  volume =       "15",
  number =       "1",
  pages =        "4:1--4:??",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3640819",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 25 11:34:33 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3640819",
  abstract =     "Design science research has traditionally been applied
                 to complex real-world problems to produce an artifact
                 to address such problems. Although design science
                 research \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "4",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Fernandez:2024:ABM,
  author =       "Joaquin Delgado Fernandez and Tom Barbereau and
                 Orestis Papageorgiou",
  title =        "Agent-Based Model of Initial Token Allocations:
                 Simulating Distributions post Fair Launch",
  journal =      j-TMIS,
  volume =       "15",
  number =       "1",
  pages =        "5:1--5:??",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3649318",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 25 11:34:33 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3649318",
  abstract =     "With advancements in distributed ledger technologies
                 and smart contracts, tokenized voting rights gained
                 prominence within decentralized finance (DeFi). Voting
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "5",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Quattrocchi:2024:DPS,
  author =       "Giovanni Quattrocchi and Willem-Jan van den Heuvel and
                 Damian Andrew Tamburri",
  title =        "The Data Product-service Composition Frontier: a
                 Hybrid Learning Approach",
  journal =      j-TMIS,
  volume =       "15",
  number =       "1",
  pages =        "6:1--6:??",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3649319",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Mon Mar 25 11:34:33 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3649319",
  abstract =     "The service dominant logic is a base concept behind
                 modern economies and software products, with service
                 composition being a well-known practice for companies
                 to gain a \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "6",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Denisenko:2024:PIM,
  author =       "Natalia Denisenko and Youzhi Zhang and Chiara Pulice
                 and Shohini Bhattasali and Sushil Jajodia and Philip
                 Resnik and V. S. Subrahmanian",
  title =        "A Psycholinguistics-inspired Method to Counter {IP}
                 Theft Using Fake Documents",
  journal =      j-TMIS,
  volume =       "15",
  number =       "2",
  pages =        "7:1--7:??",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3651313",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Jun 26 11:03:57 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3651313",
  abstract =     "Intellectual property (IP) theft is a growing problem.
                 We build on prior work to deter IP theft by generating
                 n fake versions of a technical document so a thief has
                 to expend time",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "7",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Li:2024:EFF,
  author =       "Pei-Xuan Li and Yu-En Chang and Ming-Chun Wei and
                 Hsun-Ping Hsieh",
  title =        "Estimating Future Financial Development of Urban Areas
                 for Deploying Bank Branches: a Local-Regional
                 Interpretable Model",
  journal =      j-TMIS,
  volume =       "15",
  number =       "2",
  pages =        "8:1--8:??",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3656479",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Jun 26 11:03:57 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3656479",
  abstract =     "Financial forecasting is an important task for urban
                 development. In this article, we propose a novel deep
                 learning framework to predict the future financial
                 potential of urban \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "8",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Wu:2024:COO,
  author =       "Youxi Wu and Zhen Wang and Yan Li and Yingchun Guo and
                 He Jiang and Xingquan Zhu and Xindong Wu",
  title =        "Co-occurrence Order-preserving Pattern Mining with
                 Keypoint Alignment for Time Series",
  journal =      j-TMIS,
  volume =       "15",
  number =       "2",
  pages =        "9:1--9:??",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3658450",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Jun 26 11:03:57 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3658450",
  abstract =     "Recently, order-preserving pattern (OPP) mining has
                 been proposed to discover some patterns, which can be
                 seen as trend changes in time series. Although existing
                 OPP mining \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "9",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Sheng:2024:MMT,
  author =       "Jessica Qiuhua Sheng and Da Xu and Paul Jen-Hwa Hu and
                 Liang Li and Ting-Shuo Huang",
  title =        "Mining Multimorbidity Trajectories and Co-Medication
                 Effects from Patient Data to Predict Post-Hip Fracture
                 Outcomes",
  journal =      j-TMIS,
  volume =       "15",
  number =       "2",
  pages =        "10:1--10:??",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3665250",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Wed Jun 26 11:03:57 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3665250",
  abstract =     "Hip fractures have profound impacts on patients'
                 conditions and quality of life, even when they receive
                 therapeutic treatments. Many patients face the risk of
                 poor prognosis, physical \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "10",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Chen:2024:EHU,
  author =       "Yijun Chen and Reuben Kirkham",
  title =        "Exploring How {UK} Public Authorities Use Redaction to
                 Protect Personal Information",
  journal =      j-TMIS,
  volume =       "15",
  number =       "3",
  pages =        "11:1--11:??",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3651989",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Sep 21 06:01:20 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3651989",
  abstract =     "Document redaction has become increasingly important
                 for individuals and organizations. This article
                 investigates public-sector information redaction
                 practices in order to \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "11",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Suttaket:2024:IPM,
  author =       "Thiti Suttaket and Stanley Kok",
  title =        "Interpretable Predictive Models for Healthcare via
                 Rational Multi-Layer Perceptrons",
  journal =      j-TMIS,
  volume =       "15",
  number =       "3",
  pages =        "12:1--12:??",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3671150",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Sep 21 06:01:20 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3671150",
  abstract =     "The healthcare sector has recently experienced an
                 unprecedented surge in digital data accumulation,
                 especially in the form of electronic health records
                 (EHRs). These records \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "12",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Degha:2024:ICI,
  author =       "Houssem Eddine Degha and Fatima Zohra Laallam",
  title =        "{ICA-CRMAS}: Intelligent Context-Awareness Approach
                 for Citation Recommendation based on Multi-Agent
                 System",
  journal =      j-TMIS,
  volume =       "15",
  number =       "3",
  pages =        "13:1--13:??",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3680287",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Sep 21 06:01:20 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3680287",
  abstract =     "Navigating the ever-expanding sea of scientific
                 literature presents a daunting challenge for
                 researchers seeking relevant and up-to-date
                 information. Traditional citation \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "13",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

@Article{Zhang:2024:MIF,
  author =       "Chenglong Zhang and Varghese S. Jacob and Young U.
                 Ryu",
  title =        "Modeling Individual Fairness Beliefs and Its
                 Applications",
  journal =      j-TMIS,
  volume =       "15",
  number =       "3",
  pages =        "14:1--14:??",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3682070",
  ISSN =         "2158-656X (print), 2158-6578 (electronic)",
  ISSN-L =       "2158-656X",
  bibdate =      "Sat Sep 21 06:01:20 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/tmis.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3682070",
  abstract =     "One of the criticisms made about data and
                 algorithm-driven intelligent systems is that their
                 results are viewed as being unfair or inequitable by
                 individuals who believe in fairness \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Manag. Inf. Syst.",
  articleno =    "14",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "https://dl.acm.org/loi/tmis",
}

%%% TO DO: [19-Sep-2023] Check for new papers in last recorded issue