business intelligence and analytics: from big data to big impact

More documents

Recommendations

Info

Chen et al./Introduction: Business Intelligence ResearchFinally, the six papers chosen for this special issue are themselvesa microcosm of the current state of BI&A research.These “best of the best” research papers showcase how highqualityacademic research can address real-world problemsand contribute solutions that are relevant and long lasting—exactly the challenge that our discipline continues to face.AcknowledgmentsWe wish to thank the Editor-in-Chief of MIS Quarterly, DetmarStraub, for his strong support for this special issue from its inception.He shared the belief that business intelligence and analytics isan emerging and critical IS research area. We appreciate thecontinued support from the incoming Editor-in-Chief, Paulo Goes,and his feedback on an earlier version of this paper. We also thankJanice DeGross and Jennifer Syverson from the MIS Quarterlyoffice for their professional editorial support and Cathy Larson forher support and assistance in managing the manuscripts andcoordinating the review process.We are grateful to our excellent group of 35 associate editors (listedbelow) and the reviewers (too numerous to name) who carried outthe review process in a timely manner while still meeting MISQuarterly's high expectations of scholarly quality. We thank theauthors of these 62 submissions who chose to submit their researchto our special issue. We are especially indebted to the associateeditors who handled the six accepted papers of the special issue.They and the reviewers they invited offered valuable critiques andsuggestions throughout the review process. This special issue wouldnot have been possible without their efforts.The research reported in this article was partially supported by thefollowing sources: National Science Foundation (NSF CMMI-1057624, CMMI-0926270, CNS-0709338), Defense Threat ReductionAgency (DTRA HDTRA-09-0058), J. Mack Robinson Collegeof Business at the Georgia State University, Carl H. Lindner Collegeof Business at the University of Cincinnati, and the Eller College ofManagement at the University of Arizona. We also thank thefollowing colleagues for their assistance or comments: Ee-PengLim, Ted Stohr, Barbara Wixom, Yukai Lin, and Victor Benjamin.Special Issue Associate EditorsGediminas Adomavicius, University of MinnesotaSue Brown, University of ArizonaMichael Chau, University of Hong KongCecil Chua, University of AucklandWendy Currie, Audencia, Ecole de ManagementAndrew Gemino, Simon Fraser UniversityPaulo Goes, University of ArizonaAlok Gupta, University of MinnesotaPaul Jen-Hwa Hu, University of UtahHemant Jain, University of Wisconsin – MilwaukeeRobert Kauffman, Singapore Management UniversityVijay Khatri, Indiana UniversityGondy Leroy, Claremont Graduate UniversityTing-Peng Liang, National Chengchi UniversityEe-Peng Lim, Singapore Management UniversityVijay Mookerjee, University of Texas at DallasSridhar Narasimhan, Georgia Institute of TechnologyJeffrey Parsons, Memorial University of NewfoundlandH. Raghav Rao, The State University of New York at BuffaloRaghu T. Santanam, Arizona State UniversityBalasubramaniam Ramesh, Georgia State UniversityRamesh Sharda, Oklahoma State UniversityMatti Rossi, Aalto University School of EconomicsMichael Jeng-Ping Shaw, University of Illinois, Urbana-ChampaignOlivia Sheng, University of UtahKeng Siau, Missouri University of Science and TechnologyAtish Sinha, University of Wisconsin – MilwaukeeAlexander Tuzhilin, New York UniversityVijay Vaishnavi, Georgia State UniversityDoug Vogel, City University of Hong KongChih-Ping Wei, National Taiwan UniversityBarbara Wixom, University of VirginiaCarson Woo, University of British ColumbiaDaniel Zeng, University of ArizonaJ. Leon Zhao, City University of Hong KongReferencesAdomavicius, G., and Tuzhilin, A. 2005. “Toward the NextGeneration of Recommender Systems: A Survey of the State-ofthe-Artand Possible Extensions,” IEEE Transactions onKnowledge and Data Engineering (17:6), pp. 734-749.Anderson, C. 2004. “The Long Tail,” WIRED Magazine (12:10)(http://www.wired.com/wired/archive/12.10/tail.html).Associated Press. 2012. “Columbia U Plans New Institute for DataSciences,” July 30 (http://www.cbsnews.com/8301-505245_162-57482466/columbia-u-plans-new-institute-for-data-sciences/,accessed August 3, 2012).Barabási, A. 2003. Linked: How Everything Is Connected toEverything Else and What it Means for Business, Science, andEveryday Life, New York: Plume.Batagelj, V., and Mrvar, A. 1998. “Pajek: A Program for LargeNetwork Analysis,” Connections (21), pp. 47-57.Bettencourt, L. M.A., Cintrón-Arias, A., Kaiser, D. I., and Castillo-Chávez, C. 2006. “The Power of a Good Idea: QuantitativeModeling of the Spread of Ideas from Epidemiological Models,”Physica A (364), pp. 513-536.Bitterer, A. 2011. “Hype Cycle for Business Intelligence,” Gartner,Inc., Stamford, CT.Blei, D. M. 2012. “Probabilistic Topic Models,” Communicationsof the ACM (55:4), pp. 77-84.Bloomberg Businessweek. 2011. “The Current State of BusinessAnalytics: Where Do We Go from Here?,” Bloomberg Business-22 MIS Quarterly Vol. 36No. 4/December 2012
Chen et al./Introduction: Business Intelligence Researchweek Research Services (http://www.sas.com/resources/asset/busanalyticsstudy_wp_08232011.pdf).Borgatti, S. P., Everett, M. G., and Freeman, L. C. 2002. UCInetfor Windows: Software for Social Network Analysis, Harvard,MA: Analytic Technologies.Brantingham, P. L. 2011. “Computational Criminology,” KeynoteAddress to the European Intelligence and Security InformaticsConference, Athens, Greece, September 12-14.Brin, S.,and Page, L. 1998. “The Anatomy of a Large-Scale HypertextualWeb Search Engine,” Computer Network and ISDNSystems (30), pp. 107-117.Brumfiel, G. 2911, “High-Energy Physics: Down the PetabyteHighway,” Nature (469), pp. 282-283.Chaudhuri, S., Dayal, U., and Narasayya, V. 2011. “An Overviewof Business Intelligence Technology,” Communications of theACM (54:8), pp. 88-98.Chen, H. 2006. Intelligence and Security Informatics for InternationalSecurity: Information Sharing and Data Mining, NewYork: Springer.Chen, H. 2009. “AI, E-Government, and Politics 2.0,” IEEEIntelligent Systems (24:5), pp. 64-67.Chen, H. 2011a. “Design Science, Grand Challenges, and SocietalImpacts,” ACM Transactions on Management InformationSystems (2:1), pp. 1:1-1:10.Chen, H. 2011b. “Smart Health and Wellbeing,” IEEE IntelligentSystems (26:5), pp. 78-79.Chen, H. 2012. Dark Web: Exploring and Mining the Dark Side ofthe Web, New york: Springer.Chen, H., Brandt, L., Gregg, V., Traunmuller, R., McIntosh, A.,Dawes, S., Hovy, E., and Larson, C. A. (eds.). 2007. DigitalGovernment: E-Government Research, Case Studies, and Implementation,New York: Springer.Chen, H., Reid, E., Sinai, J., Silke, A., and Ganor, B. (eds.). 2008.Terrorism Informatics: Knowledge Management and DataMining for Homeland Security, New York: Springer.Chiang, R. H. L., Goes, P., and Stohr, E. A. 2012. “BusinessIntelligence and Analytics Education and Program Development:A Unique Opportunity for the Information Systems Discipline,”ACM Transactions on Management Information Systems (3:3),forthcoming.Davenport, T. H. 2006. “Competing on Analytics,” HarvardBusiness Review (84:1), p. 98-107.Doan, A., Ramakrishnan, R., and Halevy, A. Y. 2011. “CrowdsourcingSystems on the World-Wide Web,” Communications ofthe ACM (54:4), pp. 86-96.Fortunato, S. 2010. “Community Detection in Graphs,” PhysicsReports (486:3-5), pp. 75-174.Frank, O., and Strauss, D. 1986. “Markov Graphs,” Journal of theAmerican Statistical Association (81:395), pp. 832-842.Freeman, T. 2005. The World is Flat: A Brief History of theTwenty-First Century, New York: Farrar, Straus, and Giroux.Gelfand, A. 2011/2012. “Privacy and Biomedical Research:Building a Trust Infrastructure—An Exploration of Data-Drivenand Process-Driven Approaches to Data Privacy,” BiomedicalComputation Review, Winter, pp. 23-28 (available athttp://biomedicalcomputationreview.org/content/privacy-andbiomedical-research-building-trust-infrastructure,accessedAugust 2, 2012).Hanauer, D. A. , Rhodes, D. R., and Chinnaiyan, A. M. 2009.“Exploring Clinical Associations Using ‘-Omics’ BasedEnrichment Analyses,” PLoS ONE (4:4): e5203.Hanauer, D. A., Zheng, K., Ramakrishnan, N., and Keller, B. J.2011. “Opportunities and Challenges in Association and EpisodeDiscovery from Electronic Health Records,” IEEE IntelligentSystems (26:5), pp. 83-87.Henschen, D. 2011. “Why All the Hadoopla?” Information Week,November 14, pp. 19-26.Hevner, A., March, S. T., Park, J., and Ram. S. 2004. “DesignScience Research in Information Systems,” MIS Quarterly(28:1), pp. 75-105.Hirsch, J. E. 2005. “An Index to Quantify an Individual’s ScientificResearch Output,” Proceedings of the National Academy ofSciences of the United States of America (102:46), pp.16569-16572.Hunter, D. R., Handcock, M. S., Butts, C. T., Goodreau, S. M., andMorris, M. 2008. “ergm: A Package to Fit, Simulate andDiagnose Exponential-Family Models for Network,” Journal ofStatistical Software (24:3) (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2743438/).IBM. 2011. “The 2011 IBM Tech Trends Report: The Clouds areRolling In...Is Your Business Ready?,” November 15(http://www.ibm.com/developerworks/techntrendsreport;accessed August 4, 2012)..Karpf, D. 2009. “Blogsphere Research: A Mixed-MethodsApproach to Rapidly Changing Systems,” IEEE IntelligentSystems (24:5), pp. 67-70.Liben-Nowell, D., and Kleinberg, J. 20007. “The Link-PredictionProblem for Social Networks,” Journal of American Society forInformation Science and Technology (58:7), pp. 1019-1031.Lin, Y., Brown, R. A., Yang, H. J., Li, S., Lu, H., and Chen, H.2011. “Data Mining Large-Scale Electronic Health Records forClinical Support,” IEEE Intelligent Systems (26:5), pp. 87-90.Lusch, R. F., Liu, Y., and Chen, Y. 2010. “The Phase Transition ofMarkets and Organizations: The New Intelligence and EntrepreneurialFrontier,” IEEE Intelligent Systems (25:1), pp. 71-75.Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh,C., and Byers, A. H. 2011. “Big Data: The Next Frontier forInnovation, Competition, and Productivity,” McKinsey GlobalInstitute (http://www.mckinsey.com/insights/mgi/research/technology_and_innovation/big_data_the_next_frontier_for_innovation; accessed August 4, 2012).Manning, C. D., and Schütze, H. 1999. Foundations of StatisticalNatural Language Processing, Cambridge, MA: The MIT Press.March, S. T., and Storey, V. C. 2008. “Design Science in theInformation Systems Discipline,” MIS Quarterly (32:4), pp.725-730.Maybury, M. T. (ed.). 2004. New Directions in QuestionAnswering, Cambridge, MA: The MIT Press.McCallum, A. 2002. “Mallet: A Machine Learning for LanguageToolkit,” University of Massachusetts, Amherst(http://mallet.cs.umass.edu/).MIS Quarterly Vol. 36 No. 4/December 2012 23
Page 1 and 2: SPECIAL ISSUE: BUSINESS INTELLIGENC
Page 3 and 4: Chen et al./Introduction: Business
Page 21: Chen et al./Introduction: Business

business intelligence and analytics: from big data to big impact

Create successful ePaper yourself

Delete template?

Save as template?