Conceptualization of the Business Intelligence Extended Use Model

References

• Agarwal, R. & Karahanna, E. “Time Flies When You're Having Fun: Cognitive Absorption and Beliefs about Information Technology Usage,” MIS Quarterly, 24(4), 2000, 665–694.
   Web of Science ®Google Scholar
• Agarwal, R. & Prasad, J. “A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology,” Information Systems Research, 9(2), 1998, 204–215.
   Web of Science ®Google Scholar
• Benbasat, I. & Barki, H. “Quo Vadis, TAM?” Journal of the Association for Information Systems, 8(4), 2007, 211–218.
   Web of Science ®Google Scholar
• Bhattacherjee, A. “Understanding Information Systems Continuance: An Expectation-Confirmation Model,” MIS Quarterly, 25(3), 2001, 351–370.
   Web of Science ®Google Scholar
• Burton-Jones, A. & Straub, D. W. “Reconceptualizing System Usage: An Approach and Empirical Test,” Information Systems Research, 17(3), 2006, 228–246.
   Web of Science ®Google Scholar
• Burton-Jones, A. & Grange, C. “From Use to Effective Use: A Representation Theory Perspective,” Information Systems Research (Articles in Advance: Forthcoming Issue), 2013, 1–27.
   Google Scholar
• Carroll, J. M., & Swatman, P. A. “Structured-case: A Methodological Framework for Building Theory in Information System Research,” European Journal of Information Systems, 9(4), 2000, 235–242.
   Web of Science ®Google Scholar
• Choo, C. W., Bergeron, P., Detlor, B. & Heaton, L. “Information Culture and Information Use: An Exploratory Study of Three Organizations,” Journal of the American Society for Information Science and Technology, 59(5), 2008, 1–13.
   Google Scholar
• Chuttur, M. Y. “Overview of the Technology Acceptance Model: Origins, Development and Future Directions,” Sprouts: Working Papers on Information Systems, 9(37), 2009, USA: Indiana University.
   Google Scholar
• Cooper, R. B. & Zmud, R. W. “Information technology implementation research: A technological diffusion approach,” Management Science, 36(2), 1990, 123–139.
   Web of Science ®Google Scholar
• Davenport, T. H. Information Ecology. Oxford University Press: Oxford, 1997.
   Google Scholar
• Davis, F. D. “Perceived usefulness, perceived ease of use, and user acceptance of information technology,” MIS Quarterly, 13(3), 1989, 319–339.
   Web of Science ®Google Scholar
• Davis, F. D, Bagozzi, R. P. & Warshaw, P. R. “User Acceptance of Computer Technology: A Comparison of Two Theoretical Models,” Management Science, 35(8), 1989, 982–1003.
   Web of Science ®Google Scholar
• DeLone, W. H. & McLean, E. R. “Information Systems Success: The Quest for the Dependent Variable,” Information Systems Research, 3(1), 1992, 60–95.
   Web of Science ®Google Scholar
• DeLone, W. H. & McLean, E. R. “The DeLone and McLean Model of Information Systems Success: A Ten Year Update,” Journal of Management Information Systems, 19(4), 2003, 9–30.
   Web of Science ®Google Scholar
• Deng, X. N. & Chi, L. “Understanding Postadoptive Behaviors in Information Systems Use: A Longitudinal Analysis if System Use Problems in the Business Intelligence Context,” Journal of Management Information Systems, 29(3), 2013, 291–325.
   Web of Science ®Google Scholar
• Doll, W. J. & Torkzadeh, G. “Developing a multidimensional measure of system-use in an organizational context,” Information & Management, 33(4), 1998, 171–185.
   Web of Science ®Google Scholar
• Elbashir, M. Z., Collier, P.A. & Davern, M. J. “Measuring the effects of business intelligence systems: The relationship between business process and organizational performance,” International Journal of Accounting Information Systems, 9(3), 2008, 135–153.
   Google Scholar
• El Sawy, Omar A. “The IS Core IX: The 3 Faces of IS Identity: Connection, Immersion, and Fusion,” Communications of the Association for Information Systems, 12(1), 2003, 588–598.
   Google Scholar
• English, L. P. Business intelligence defined. Available at: http://www.webcitation.org/51WCbyuWs, 2005, July 6.
   Google Scholar
• Eppler, M. J. Managing Information Quality: Increasing the Value of Information in Knowledge-intensive Products and Processes. 2nd Ed., Springer Berlin: Berlin, Heidelberg, 2006.
   Google Scholar
• Furneaux, B. & Wade, M. “An Exploration of Organizational Level Information Systems Discontinuance Intentions,” MIS Quarterly, 35(3), 2011, 573–598.
   Web of Science ®Google Scholar
• Gartner Research. Gartner Executive Program Survey of More Than 2,000 CIOs Shows Digital Technologies Are Top Priorities in 2013. Available at http://www.gartner.com/newsroom/id/2304615, 2013
   Google Scholar
• Gibson, M. Arnott, D. & Jagielska, I. “Evaluating the Intangible Benefits of Business Intelligence: Review & Research Agenda,” In Proceedings: Decision Support in an Uncertain and Complex World: The IFIP TC8/WG8.3 International Conference 2004, 2004.
   Google Scholar
• Goodhue, D. L. & Thompson, R. L. “Task-Technology Fit and Individual Performance,” MIS Quarterly, 19(2), 1995, 213–236.
   Web of Science ®Google Scholar
• Grublješič, T. “Dejavniki sprejemanja poslovno-inteligenčnih sistemov,” Economic and Business Review, 15(2), 2013, 77–109.
   Google Scholar
• Huo, C.-H. “Examining the effect of user satisfaction on system usage and individual performance with business intelligence systems: An empirical study of Taiwan's electronic industry,” International Journal of Information Management, 32(6), 2012, 560–573.
   Web of Science ®Google Scholar
• Jasperson, J., Carter, P. E. & Zmud, R. W. “A Comprehensive Conceptualization of Post-Adoptive Behaviors Associated with Information Technology Enabled Work Systems,” MIS Quarterly, 29(3), 2005, 525–557.
   Web of Science ®Google Scholar
• Jourdan, Z., Rainer, R. K., & Marshall, T. E. “Business Intelligence: An Analysis of the Literature,” Information Systems Management, 25(2), 2008, 121–131.
   Web of Science ®Google Scholar
• Karahanna, E. & Straub, D. W. “The psychological origins of perceived usefulness and ease-of-use. Information & Management, 35(4), 1999, 237–250.
   Web of Science ®Google Scholar
• Karahanna, E., Straub, D. W. & Chervany, N. L. “Information Technology Adoption Across Time: A Cross-Sectional Comparison of Pre-Adoption and Post-Adoption Beliefs,” MIS Quarterly, 23(2), 1999, 189–213.
   Google Scholar
• King, W. R. & He, J. “A meta-analysis of the technology acceptance model,” Information & Management, 43(6), 2006, 740–755.
   Web of Science ®Google Scholar
• King, W. R. & Teo, T. S. H. “Key Dimensions of Facilitators and Inhibitors for the Strategic Use of Information Technology,” Journal of Management Information Systems, 12(4), 1996, 35–53.
   Google Scholar
• Kwahk, K.-Y. & Lee, J.-N. “The role of readiness for change in ERP implementation: Theoretical bases and empirical validation,” Information & Management, 45(1), 2008, 474–481.
   Google Scholar
• Lee, Y., Kozar, K. A. & Larsen, K. R. T. “The Technology Acceptance Model: Past, Present and the Future,” Communications of the AIS, 12(50), 2003, 752–780.
   Google Scholar
• Lee, G. & Xia, W. “Organizational size and IT innovation adoption: A meta-analysis,” Information & Management, 43(8), 2006, 975–985.
   Web of Science ®Google Scholar
• Legris, P., Ingham, J. & Collerette, P. “Why do people use information technology? A critical review of the technology acceptance model,” Information & Management, 40(3), 2003, 191–204.
   Web of Science ®Google Scholar
• Lyytinen, K., & Hirschheim, R. Information systems failures: a survey and classification of the empirical literature, Oxford University: Oxford, 1987.
   Google Scholar
• Marchand, D. A., Kettinger, W. J. & Rollins, J. D. Information Orientation: The link to business performance, New York: Oxford University Press, 2001.
   Google Scholar
• Miles, M. B. & Huberman, A. M. Qualitative Data Analysis: An Expended Sourcebook. Sage: USA, 1994.
   Google Scholar
• Moore, G. C. & Benbasat, I. “Development of an Instrument to Measure the Perceptions of Adoption and Information Technology Innovation,” Information Systems Research, 2(3), 1991, 192–222.
   Web of Science ®Google Scholar
• Myers, M. D. & Newman, M. “The Qualitative Interview in IS Research: Examining the Craft,” Information and Organization, 17(1), 2007, 2–26.
   Google Scholar
• Oliver, R. L. “A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions,” Journal of Marketing Research, 17, 1980, 460–469.
   Web of Science ®Google Scholar
• Ortiz de Guinea, A. & Markus, M. L. “Why Break the Habit of a Lifetime? Rethinking the Roles of Intention, Habit, and Emotion in Continuing Information Technology Use,” MIS Quarterly, 33(3), 2009, 433–444.
   Web of Science ®Google Scholar
• Pare, G. “Investigating Information Systems with Positivist Case Study Research,” Communications of the Association for Information Systems, 13(1), 2004, 233–264.
   Google Scholar
• Popovič, A., Coelho, P. S., & Jaklič, J. “The impact of business intelligence system maturity on information quality,” Information Research, 14(4), 2009.
   Web of Science ®Google Scholar
• Popovič, A., Hackney, R., Coelho, P. S., & Jaklič, J. “Towards business intelligence systems success: Effects of maturity and culture on analytical decision making,” Decision Support Systems, 54(1), 2012, 729–739.
   Web of Science ®Google Scholar
• Rogers, E. M. Diffusion of Innovations. Free Press: New York, 3rd Ed., 1983.
   Google Scholar
• Saga, V. L. & Zmud, R. W. “The nature and determinants of IT acceptance, routinization, and infusion,” In Levine, L. (Ed.), Diffusion, transfer and implementation of information technology. Software Engineering Institute: Pittsburgh, PA, 1994, 67–86.
   Google Scholar
• Saunders, M., Lewis, P., & Thornhill, A. Research Methods for Business Students. Financial Times/Prentice Hall, 2009.
   Google Scholar
• Seah, M., Hsieh, M. H. & Weng, P-U. “A case analysis of Savecom: The role of indigenous leadership in implementing a business intelligence system,” International Journal of Information Management, 30(4), 2010, 368–373.
   Web of Science ®Google Scholar
• Shanks, G., Bekmamedova, N., Adam, F., & Daly, M. “Embedding Business Intelligence Systems within Organisations”. In A. Respício & F. Burstein (Eds.), Fusing Decision Support Systems into the Fabric of the Context, Vol. 238, 2012, 113–124, IOS Press.
   Google Scholar
• Sharp, J. H. “Development, Extension, and Application: A Review of the Technology Acceptance Model,” Information Systems Education Journal, 5(9), 2007, 1–11.
   Google Scholar
• Straub, D. & Guidice, M. d. “Use,” MIS Quarterly, 36(4), 2012, iii–vii.
   Web of Science ®Google Scholar
• Taylor, S. & Todd, P. “Assessing IT usage: The role of prior experience,” MIS Quarterly, 19(4), 1995, 561–570.
   Web of Science ®Google Scholar
• Tornatzky, L. & Fleischer, M. The process of technology innovation, Lexington Book: Lexington, Massachusetts, 1990.
   Google Scholar
• Venkatesh, V. & Davis, F. “A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies,” Management Science, 46(2), 2000, 186–204.
   Web of Science ®Google Scholar
• Venkatesh, V., Morris, M. G., Davis, G. B. & Davis, F. D. “User Acceptance of Information Technology: Towards a Unified View,” MIS Quarterly, 27(3), 2003, 425–478.
   Web of Science ®Google Scholar
• Venkatesh, V. & Bala, H. “Technology Acceptance Model 3 and a Research Agenda on Interventions,” Decision Sciences, 39(2), 2008, 273–315.
   Web of Science ®Google Scholar
• Venkatesh, V., Brown, S. A., & Maruping, L. M., Bala, H. “Predicting Different Conceptualizations of System Use: The Competing Roles of Behavioral Intention, Facilitating Conditions, and Behavioral Expectation,” MIS Quarterly, 32(3), 2008, 483–502.
   Web of Science ®Google Scholar
• Wade, M. & Hulland, J. “Review: The resource based view and information systems research: Review, extension, and suggestions for future research,” MIS Quarterly, 28(1), 2004, 107–142.
   Web of Science ®Google Scholar
• Wixom, H. B. & Todd, P.A. “A Theoretical Integration of User Satisfaction and Technology Acceptance,” Information Systems Research, 16(1), 2005, 85–102.
   Web of Science ®Google Scholar
• Wixom, H. B. & Watson, H. J. “An Empirical Investigation of the Factors Affecting Data Warehouse Success,” MIS Quarterly, 25(1), 2001, 17–41.
   Web of Science ®Google Scholar
• Wixom, H. B., Watson, H., Reynolds, A. M. & Hoffer, J. A. “Continental Airlines Continues to Soar with Business Intelligence,” Information Systems Management, 25(2), 2008, 102–112.
   Web of Science ®Google Scholar
• Wixom, H. B. & Watson, H. “The BI Based Organization,” International Journal of Business Intelligence Research, 1(1), 2010, 13–28.
   Google Scholar
• Wu, J. & Lederer, A. “A Meta-Analysis of the Role of Environment-Based Voluntariness in Information Technology Acceptance,” MIS Quarterly, 33(2), 2009, 419–432.
   Web of Science ®Google Scholar
• Wu, K., Zhao, Y., Zhu, Q., Tan, X. & Zheng, H. “A meta-analysis of the impact of trust on technology acceptance model. Investigation of moderating influence of subject and context type,” International Journal of Information Management, 31(1), 2011, 572–581.
   Google Scholar
• Yeoh, W. & Koronios, A. “Critical Success Factors for Business Intelligence Systems,” Journal of computer Information systems, 50(3), 2010, 23–32.
   Web of Science ®Google Scholar
• Yousafzai, S. Y., Foxall, G. R. & Pallister, J. G. “Technology acceptance: A meta-analysis of the TAM: Part 1,” Journal of Modeling in Management, 2(3), 2007, 251–280.
   Google Scholar