%%% -*-BibTeX-*-
%%% ====================================================================
%%% BibTeX-file{
%%%     author          = "Nelson H. F. Beebe",
%%%     version         = "1.07",
%%%     date            = "15 April 2014",
%%%     time            = "17:46:33 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             = "http://www.math.utah.edu/~beebe",
%%%     checksum        = "17477 3244 16605 162403",
%%%     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 ????, ISSN 2158-656X),
%%%                        covering all journal issues from 2010 --
%%%                        date.
%%%
%%%                        At version 1.07, the COMPLETE journal
%%%                        coverage looked like this:
%%%
%%%                             2010 (   7)    2012 (  16)    2014 (   5)
%%%                             2011 (  26)    2013 (  24)
%%%
%%%                             Article:         78
%%%
%%%                             Total entries:   78
%%%
%%%                        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|http://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 =          "http://dx.doi.org/10.1145/1877725.1877726",
  ISSN =         "2158-656X",
  bibdate =      "Mon Mar 28 11:02:24 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/1877725.1877727",
  ISSN =         "2158-656X",
  bibdate =      "Mon Mar 28 11:02:24 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/1877725.1877728",
  ISSN =         "2158-656X",
  bibdate =      "Mon Mar 28 11:02:24 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/1877725.1877729",
  ISSN =         "2158-656X",
  bibdate =      "Mon Mar 28 11:02:24 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/1877725.1877730",
  ISSN =         "2158-656X",
  bibdate =      "Mon Mar 28 11:02:24 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/1877725.1877731",
  ISSN =         "2158-656X",
  bibdate =      "Mon Mar 28 11:02:24 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/1877725.1877732",
  ISSN =         "2158-656X",
  bibdate =      "Mon Mar 28 11:02:24 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/1929916.1929917",
  ISSN =         "2158-656X",
  bibdate =      "Mon Mar 28 11:02:25 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/1929916.1929918",
  ISSN =         "2158-656X",
  bibdate =      "Mon Mar 28 11:02:25 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/1929916.1929919",
  ISSN =         "2158-656X",
  bibdate =      "Mon Mar 28 11:02:25 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/1929916.1929920",
  ISSN =         "2158-656X",
  bibdate =      "Mon Mar 28 11:02:25 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/1929916.1929921",
  ISSN =         "2158-656X",
  bibdate =      "Mon Mar 28 11:02:25 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/1929916.1929922",
  ISSN =         "2158-656X",
  bibdate =      "Mon Mar 28 11:02:25 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/1985347.1985348",
  ISSN =         "2158-656X",
  bibdate =      "Fri Jul 22 08:37:49 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/1985347.1985349",
  ISSN =         "2158-656X",
  bibdate =      "Fri Jul 22 08:37:49 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/1985347.1985350",
  ISSN =         "2158-656X",
  bibdate =      "Fri Jul 22 08:37:49 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/1985347.1985351",
  ISSN =         "2158-656X",
  bibdate =      "Fri Jul 22 08:37:49 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/1985347.1985352",
  ISSN =         "2158-656X",
  bibdate =      "Fri Jul 22 08:37:49 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/1985347.1985353",
  ISSN =         "2158-656X",
  bibdate =      "Fri Jul 22 08:37:49 MDT 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/2019618.2019619",
  ISSN =         "2158-656X",
  bibdate =      "Sun Nov 6 07:18:27 MST 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/2019618.2019620",
  ISSN =         "2158-656X",
  bibdate =      "Sun Nov 6 07:18:27 MST 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/2019618.2019621",
  ISSN =         "2158-656X",
  bibdate =      "Sun Nov 6 07:18:27 MST 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/2019618.2019622",
  ISSN =         "2158-656X",
  bibdate =      "Sun Nov 6 07:18:27 MST 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/2019618.2019623",
  ISSN =         "2158-656X",
  bibdate =      "Sun Nov 6 07:18:27 MST 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/2019618.2019624",
  ISSN =         "2158-656X",
  bibdate =      "Sun Nov 6 07:18:27 MST 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =          "http://dx.doi.org/10.1145/2019618.2019625",
  ISSN =         "2158-656X",
  bibdate =      "Sun Nov 6 07:18:27 MST 2011",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/tmis.bib",
  acknowledgement = ack-nhfb,
  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 =       "Jr. Jay F. Nunamaker 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 =          "http://dx.doi.org/10.1145/2070710.2070711",
  ISSN =         "2158-656X",
  bibdate =      "Fri Mar 16 15:06:39 MDT 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2070710.2070712",
  ISSN =         "2158-656X",
  bibdate =      "Fri Mar 16 15:06:39 MDT 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2070710.2070713",
  ISSN =         "2158-656X",
  bibdate =      "Fri Mar 16 15:06:39 MDT 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2070710.2070714",
  ISSN =         "2158-656X",
  bibdate =      "Fri Mar 16 15:06:39 MDT 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2070710.2070715",
  ISSN =         "2158-656X",
  bibdate =      "Fri Mar 16 15:06:39 MDT 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2070710.2070716",
  ISSN =         "2158-656X",
  bibdate =      "Fri Mar 16 15:06:39 MDT 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2070710.2070717",
  ISSN =         "2158-656X",
  bibdate =      "Fri Mar 16 15:06:39 MDT 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2151163.2151164",
  ISSN =         "2158-656X",
  bibdate =      "Tue Nov 6 19:02:08 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2151163.2151165",
  ISSN =         "2158-656X",
  bibdate =      "Tue Nov 6 19:02:08 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2151163.2151166",
  ISSN =         "2158-656X",
  bibdate =      "Tue Nov 6 19:02:08 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2151163.2151167",
  ISSN =         "2158-656X",
  bibdate =      "Tue Nov 6 19:02:08 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2151163.2151168",
  ISSN =         "2158-656X",
  bibdate =      "Tue Nov 6 19:02:08 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2151163.2151169",
  ISSN =         "2158-656X",
  bibdate =      "Tue Nov 6 19:02:08 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2229156.2229157",
  ISSN =         "2158-656X",
  bibdate =      "Tue Nov 6 19:02:09 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2229156.2229160",
  ISSN =         "2158-656X",
  bibdate =      "Tue Nov 6 19:02:09 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2229156.2229159",
  ISSN =         "2158-656X",
  bibdate =      "Tue Nov 6 19:02:09 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2229156.2229158",
  ISSN =         "2158-656X",
  bibdate =      "Tue Nov 6 19:02:09 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2229156.2229161",
  ISSN =         "2158-656X",
  bibdate =      "Tue Nov 6 19:02:09 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2361256.2361257",
  ISSN =         "2158-656X",
  bibdate =      "Tue Nov 6 19:02:10 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2361256.2361258",
  ISSN =         "2158-656X",
  bibdate =      "Tue Nov 6 19:02:10 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2361256.2361259",
  ISSN =         "2158-656X",
  bibdate =      "Tue Nov 6 19:02:10 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2361256.2361260",
  ISSN =         "2158-656X",
  bibdate =      "Tue Nov 6 19:02:10 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2361256.2361261",
  ISSN =         "2158-656X",
  bibdate =      "Tue Nov 6 19:02:10 MST 2012",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2407740.2407741",
  ISSN =         "2158-656X",
  bibdate =      "Tue Apr 30 18:40:39 MDT 2013",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2407740.2407742",
  ISSN =         "2158-656X",
  bibdate =      "Tue Apr 30 18:40:39 MDT 2013",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2407740.2407743",
  ISSN =         "2158-656X",
  bibdate =      "Tue Apr 30 18:40:39 MDT 2013",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2407740.2407744",
  ISSN =         "2158-656X",
  bibdate =      "Tue Apr 30 18:40:39 MDT 2013",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2445560.2445561",
  ISSN =         "2158-656X",
  bibdate =      "Tue Apr 30 18:40:41 MDT 2013",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2445560.2445562",
  ISSN =         "2158-656X",
  bibdate =      "Tue Apr 30 18:40:41 MDT 2013",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2445560.2445563",
  ISSN =         "2158-656X",
  bibdate =      "Tue Apr 30 18:40:41 MDT 2013",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2445560.2445564",
  ISSN =         "2158-656X",
  bibdate =      "Tue Apr 30 18:40:41 MDT 2013",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2499962.2499963",
  ISSN =         "2158-656X",
  bibdate =      "Thu Mar 13 06:54:56 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2500750",
  ISSN =         "2158-656X",
  bibdate =      "Thu Mar 13 06:54:56 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2489790",
  ISSN =         "2158-656X",
  bibdate =      "Thu Mar 13 06:54:56 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2490860",
  ISSN =         "2158-656X",
  bibdate =      "Thu Mar 13 06:54:56 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2499962.2499967",
  ISSN =         "2158-656X",
  bibdate =      "Thu Mar 13 06:54:56 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2524263",
  ISSN =         "2158-656X",
  bibdate =      "Thu Mar 13 06:54:58 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2517309",
  ISSN =         "2158-656X",
  bibdate =      "Thu Mar 13 06:54:58 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2517310",
  ISSN =         "2158-656X",
  bibdate =      "Thu Mar 13 06:54:58 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2517084",
  ISSN =         "2158-656X",
  bibdate =      "Thu Mar 13 06:54:58 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2523025.2523026",
  ISSN =         "2158-656X",
  bibdate =      "Thu Mar 13 06:54:58 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2555810.2555811",
  ISSN =         "2158-656X",
  bibdate =      "Thu Mar 13 06:54:59 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2544105",
  ISSN =         "2158-656X",
  bibdate =      "Thu Mar 13 06:54:59 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2544102",
  ISSN =         "2158-656X",
  bibdate =      "Thu Mar 13 06:54:59 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2544104",
  ISSN =         "2158-656X",
  bibdate =      "Thu Mar 13 06:54:59 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2544103",
  ISSN =         "2158-656X",
  bibdate =      "Thu Mar 13 06:54:59 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2543900",
  ISSN =         "2158-656X",
  bibdate =      "Thu Mar 13 06:54:59 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2591676",
  ISSN =         "2158-656X",
  bibdate =      "Tue Apr 15 17:44:19 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2576233",
  ISSN =         "2158-656X",
  bibdate =      "Tue Apr 15 17:44:19 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2555596",
  ISSN =         "2158-656X",
  bibdate =      "Tue Apr 15 17:44:19 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://www.math.utah.edu/pub/tex/bib/gnu.bib;
                 http://www.math.utah.edu/pub/tex/bib/java2010.bib;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2576756",
  ISSN =         "2158-656X",
  bibdate =      "Tue Apr 15 17:44:19 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  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 =          "http://dx.doi.org/10.1145/2576757",
  ISSN =         "2158-656X",
  bibdate =      "Tue Apr 15 17:44:19 MDT 2014",
  bibsource =    "http://www.acm.org/pubs/contents/journals/tmis/;
                 http://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,
  articleno =    "5",
  fjournal =     "ACM Transactions on Management Information Systems
                 (TMIS)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1320",
}