Conceptualization of the Business Intelligence Extended Use Model

Business intelligence systems (BIS) are considered a potential source of competitive advantage but their benefits can be fully realized only when using BIS and the information provided by BIS become fully embedded into the routines of decision makers. This study thus adds to previous research of IS acceptance by investigating diverse post-adoptive use behaviors, which are the intensity, extent of use and embeddedness of BIS. We followed an exploratory approach to conceptualize a business intelligence extended use model. The findings show that personal innovativeness and readiness for change boost the transition to the embeddedness of BIS into workers routines. The relevance of the information provided by BIS is crucial for the deep structural usage of BIS, which has not been highlighted in previous models of IT acceptance. Besides taking pre- and post-implemental issues that address acceptance determinants into consideration, for the success of BIS we must consider trans-implemental issues.

[1]  Michael R. Wade,et al.  An Exploration of Organizational Level Information Systems Discontinuance Intentions , 2011, MIS Q..

[2]  John Ingham,et al.  Why do people use information technology? A critical review of the technology acceptance model , 2003, Inf. Manag..

[3]  Anol Bhattacherjee,et al.  Understanding Information Systems Continuance: An Expectation-Confirmation Model , 2001, MIS Q..

[4]  Ephraim R. McLean,et al.  The DeLone and McLean Model of Information Systems Success: A Ten-Year Update , 2003, J. Manag. Inf. Syst..

[5]  E. Rogers,et al.  Diffusion of innovations , 1964, Encyclopedia of Sport Management.

[6]  William R. King,et al.  A meta-analysis of the technology acceptance model , 2006, Inf. Manag..

[7]  Albert L. Lederer,et al.  A Meta-Analysis of the Role of Environment-Based Voluntariness in Information Technology Acceptance , 2009, MIS Q..

[8]  Ritu Agarwal,et al.  A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology , 1998, Inf. Syst. Res..

[9]  Michael D. Myers,et al.  The qualitative interview in IS research: Examining the craft , 2007, Inf. Organ..

[10]  Liz Lee-Kelly Information orientation: the link to business performance: Donald A. Merchand, William J. Kettinger and John D. Rollins, Oxford University Press (2002), 314 pp., £30.00 , 2003 .

[11]  IbrahimRoliana,et al.  Predicting different conceptualizations of system use , 2013 .

[12]  Ana Ortiz de Guinea,et al.  Why break the habit of a lifetime? rethinking the roles of intention, habit, and emotion in continuing information technology use , 2009 .

[13]  Detmar W. Straub,et al.  Editor's Comments: Use , 2012 .

[14]  Elena Karahanna,et al.  Time Flies When You're Having Fun: Cognitive Absorption and Beliefs About Information Technology Usage , 2000, MIS Q..

[15]  Lei Chi,et al.  Understanding Postadoptive Behaviors in Information Systems Use: A Longitudinal Analysis of System Use Problems in the Business Intelligence Context , 2012, J. Manag. Inf. Syst..

[16]  Henryk Sienkiewicz,et al.  Quo Vadis? , 1967, American Association of Industrial Nurses journal.

[17]  Fred D. Davis Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[18]  Viswanath Venkatesh,et al.  Technology Acceptance Model 3 and a Research Agenda on Interventions , 2008, Decis. Sci..

[19]  Philip E. T. Lewis,et al.  Research Methods for Business Students , 2006 .

[20]  R. Zmud,et al.  Information technology implementation research: a technological diffusion approach , 1990 .

[21]  Izak Benbasat,et al.  Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation , 1991, Inf. Syst. Res..

[22]  Ming-Huei Hsieh,et al.  A case analysis of Savecom: The role of indigenous leadership in implementing a business intelligence system , 2010, Int. J. Inf. Manag..

[23]  Barbara H Wixom,et al.  A Theoretical Integration of User Satisfaction and Technology Acceptance , 2005, Inf. Syst. Res..

[24]  Peter A. Todd,et al.  Assessing IT usage: the role of prior experience , 1995 .

[25]  Robert W. Zmud,et al.  A Comprehensive Conceptualization of Post-Adoptive Behaviors Associated with Information Technology Enabled Work Systems , 2005, MIS Q..

[26]  Jurij Jaklic,et al.  The Impact of Business Intelligence System Maturity on Information Quality , 2009, Inf. Res..

[27]  Brian Detlor,et al.  Information culture and information use: An exploratory study of three organizations , 2008, J. Assoc. Inf. Sci. Technol..

[28]  Robert W. Zmud,et al.  The Nature and Determinants of IT Acceptance, Routinization, and Infusion , 1993, Diffusion, Transfer and Implementation of Information Technology.

[29]  Martin J. Eppler Managing Information Quality , 2003 .

[30]  Gordon R. Foxall,et al.  Technology acceptance: a meta‐analysis of the TAM: Part 1 , 2007 .

[31]  E. Rogers Diffusion of Innovations , 1962 .

[32]  R. Kelly Rainer,et al.  Business intelligence: an analysis of the literature , 2008, IEEE Engineering Management Review.

[33]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[34]  Mohammad Chuttur,et al.  Overview of the Technology Acceptance Model: Origins, Developments and Future Directions , 2009 .

[35]  Michael J. Davern,et al.  Measuring the effects of business intelligence systems: The relationship between business process and organizational performance , 2008, Int. J. Account. Inf. Syst..

[36]  William R. King,et al.  Key Dimensions of Facilitators and Inhibitors for the Strategic Use of Information Technology , 1996, J. Manag. Inf. Syst..

[37]  Chung-Kuang Hou,et al.  Examining the effect of user satisfaction on system usage and individual performance with business intelligence systems: An empirical study of Taiwan's electronics industry , 2012, Int. J. Inf. Manag..

[38]  Graeme G. Shanks,et al.  Embedding Business Intelligence Systems within Organisations , 2012, DSS.

[39]  Venkateshviswanath,et al.  A Theoretical Extension of the Technology Acceptance Model , 2000 .

[40]  Ephraim R. McLean,et al.  Information Systems Success: The Quest for the Dependent Variable , 1992, Inf. Syst. Res..

[41]  Detmar W. Straub,et al.  The psychological origins of perceived usefulness and ease-of-use , 1999, Inf. Manag..

[42]  Kalle Lyytinen,et al.  Information systems failures—a survey and classification of the empirical literature , 1988 .

[43]  Detmar W. Straub,et al.  Reconceptualizing System Usage: An Approach and Empirical Test , 2006, Inf. Syst. Res..

[44]  Viswanath Venkatesh,et al.  Predicting Different Conceptualizations of System Use: The Competing Roles of Behavioral Intention, Facilitating Conditions, and Behavioral Expectation , 2008, MIS Q..

[45]  Weidong Xia,et al.  Organizational size and IT innovation adoption: A meta-analysis , 2006, Inf. Manag..

[46]  Barbara Wixom,et al.  The BI-Based Organization , 2010, Int. J. Bus. Intell. Res..

[47]  Barbara Wixom,et al.  Continental Airlines Continues to Soar with Business Intelligence , 2008, Inf. Syst. Manag..

[48]  Barbara Wixom,et al.  An Empirical Investigation of the Factors Affecting Data Warehousing Success , 2001, MIS Q..

[49]  William J. Kettinger,et al.  Information Orientation: The Link to Business Performance , 2001 .

[50]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[51]  M. Wade,et al.  Review: the resource-based view and information systems research: review, extension, and suggestions for future research , 2004 .

[52]  P. Swatman,et al.  Structured-case: a methodological framework for building theory in information systems research , 2000, ECIS.

[53]  Younghwa Lee,et al.  The Technology Acceptance Model: Past, Present, and Future , 2003, Commun. Assoc. Inf. Syst..

[54]  D. Arnott,et al.  Evaluating the intangible benefits of Business Intelligence: review and research agenda , 2004 .

[55]  Omar El Sawy,et al.  The IS Core IX: The 3 Faces of IS Identity: Connection, Immersion, and Fusion , 2003, Commun. Assoc. Inf. Syst..

[56]  Detmar W. Straub,et al.  Information Technology Adoption Across Time: A Cross-Sectional Comparison of Pre-Adoption and Post-Adoption Beliefs , 1999, MIS Q..

[57]  G. Paré Investigating Information Systems with Positivist Case Study Research , 2004 .

[58]  Jason H. Sharp Development, Extension, and Application: A Review of the Technology Acceptance Model , 2006 .

[59]  R. Oliver A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions , 1980 .

[60]  William Yeoh,et al.  Critical Success Factors for Business Intelligence Systems , 2010, J. Comput. Inf. Syst..

[61]  Jae-Nam Lee,et al.  The role of readiness for change in ERP implementation: Theoretical bases and empirical validation , 2008, Inf. Manag..

[62]  Guy Paré,et al.  Investigating Information Systems with Positivist Case Research , 2004, Commun. Assoc. Inf. Syst..

[63]  Izak Benbasat,et al.  Quo vadis TAM? , 2007, J. Assoc. Inf. Syst..

[64]  Dale Goodhue,et al.  Task-Technology Fit and Individual Performance , 1995, MIS Q..

[65]  William J. Doll,et al.  Developing a multidimensional measure of system-use in an organizational context , 1998, Inf. Manag..

[66]  Qinghua Zhu,et al.  A meta-analysis of the impact of trust on technology acceptance model: Investigation of moderating influence of subject and context type , 2011, Int. J. Inf. Manag..

[67]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[68]  Andrew Burton-Jones,et al.  From Use to Effective Use: A Representation Theory Perspective , 2013, Inf. Syst. Res..

[69]  Aleš Popovič,et al.  Towards business intelligence systems success: Effects of maturity and culture on analytical decision making , 2012, Decis. Support Syst..