Critical value factors in business intelligence systems implementations

Business Intelligence (BI) systems have been rated as a leading technology for the last several years. However, organizations have struggled to ensure that high quality information is provided to and from BI systems. This suggests that organizations have recognized the value of information and the potential opportunities available but are challenged by the lack of success in Business Intelligence Systems Implementation (BISI). Therefore, our research addresses the preponderance of failed BI system projects, promulgated by a lack of attention to Systems Quality (SQ) and Information Quality (IQ) in BISI. The main purpose of this study is to determine how an organization may gain benefits by uncovering the antecedents and critical value factors (CVFs) of SQ and IQ necessary to derive greater BISI success. We approached these issues through adopting ‘critical value factors’ (CVF) as a conceptual ‘lens’. Following an initial pilot study, we undertook an empirical analysis of 1300 survey invitations to BI analysts. We used exploratory factor analysis (EFA) techniques to uncover the CVFs of SQ and IQ of BISI. Our study demonstrates that there is a significant effect in the relationships of perceived IQ of BISI to perceived user information satisfaction thereby confirming the importance BI system users place on information and the output produced. Our study also reported that there is a significant effect in the relationships of perceived IQ of BISI to perceived user system satisfaction thereby confirming the importance BI system users place on system output. We believe our research will be of benefit to both academics and practitioners in attempting to ensure BI systems implementation success.

[1]  Yair Levy,et al.  An empirical development of critical value factors (CVF) of online learning activities: An application of activity theory and cognitive value theory , 2008, Comput. Educ..

[2]  Yair Levy,et al.  Assessing the Value of E-learning Systems , 2005 .

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

[4]  Peter B. Seddon.  A Respecification and Extension of the DeLone and McLean Model of IS Success , 1997, Inf. Syst. Res..

[5]  Craig A. Mertler,et al.  Advanced and multivariate statistical methods: Practical application and interpretation: Sixth edition , 2001 .

[6]  Yair Levy,et al.  A Value-Satisfaction Taxonomy of IS Effectiveness (VSTISE): A Case Study of User Satisfaction with IS and User-Perceived Value of IS , 2009, Int. J. Inf. Syst. Serv. Sect..

[7]  Gurpreet Dhillon,et al.  Value Focused Assessment of Individual Privacy Concerns for Internet Commerce , 2002, ICIS.

[8]  Detmar W. Straub,et al.  Validating Instruments in MIS Research , 1989, MIS Q..

[9]  Gurpreet Dhillon,et al.  Value‐focused assessment of information system security in organizations , 2006, Inf. Syst. J..

[10]  Juhani Iivari,et al.  An empirical test of the DeLone-McLean model of information system success , 2005, DATB.

[11]  Matthias Jarke,et al.  Dwq : Esprit Long Term Research Project, No 22469 Data Warehouse Quality: a Review of the Dwq Project , 2022 .

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

[13]  Barbara Wixom,et al.  Antecedents of Information and System Quality: An Empirical Examination Within the Context of Data Warehousing , 2005, J. Manag. Inf. Syst..

[14]  Babita Gupta,et al.  The Current State of Business Intelligence in Academia: The Arrival of Big Data , 2014, CAIS.

[15]  Rahat H. Bokhari,et al.  The relationship between system usage and user satisfaction: a meta-analysis , 2005, J. Enterp. Inf. Manag..

[16]  Jae Hong Park,et al.  A Data Quality Management Maturity Model , 2006 .

[17]  Keng Siau,et al.  The value of mobile applications: a utility company study , 2005, CACM.

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

[19]  Barbara Wixom,et al.  The benefits of data warehousing: why some organizations realize exceptional payoffs , 2002, Inf. Manag..

[20]  Sammy W. Pearson,et al.  Development of a Tool for Measuring and Analyzing Computer User Satisfaction , 1983 .

[21]  Daniel J. Power,et al.  Understanding Data-Driven Decision Support Systems , 2008, Inf. Syst. Manag..

[22]  Yair Levy,et al.  An Empirical Study of Computer Self-Efficacy and the Technology Acceptance Model in the Military: A Case of a U.S. Navy Combat Information System , 2009, J. Organ. End User Comput..

[23]  Ralph L. Keeney,et al.  Value-Focused Thinking: A Path to Creative Decisionmaking , 1992 .

[24]  Ali F. Farhoomand,et al.  On end-user computing satisfaction , 1991 .

[25]  David Loshin,et al.  Business Intelligence: The Savvy Manager's Guide , 2003 .

[26]  Dale Goodhue,et al.  Understanding user evaluations of information systems , 1995 .

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

[28]  Juhani Iivari,et al.  User information satisfaction: IS implementability and effectiveness , 1994, Inf. Manag..

[29]  Graham Pervan,et al.  Eight key issues for the decision support systems discipline , 2008, Decis. Support Syst..

[30]  Saman Asadi.  Value focused assessment of information system security , 2014 .

[31]  Detmar W. Straub,et al.  Validation Guidelines for IS Positivist Research , 2004, Commun. Assoc. Inf. Syst..

[32]  Richard Y. Wang,et al.  Anchoring data quality dimensions in ontological foundations , 1996, CACM.

[33]  Ofer Arazy,et al.  On the measurability of information quality , 2011, J. Assoc. Inf. Sci. Technol..

[34]  R. Gorsuch,et al.  Beliefs, attitudes, and values , 1968 .

[35]  Arun Rai,et al.  Assessing the Validity of IS Success Models: An Empirical Test and Theoretical Analysis , 2002, Inf. Syst. Res..

[36]  Thomas D. Clark,et al.  The Dynamic Structure of Management Support Systems: Theory Development, Research Focus, and Direction , 2007, MIS Q..

[37]  Amy W. Gatian.  Is user satisfaction a valid measure of system effectiveness? , 1994, Inf. Manag..

[38]  Keng Siau,et al.  Understanding the values of mobile technology in education: a value-focused thinking approach , 2010, DATB.

[39]  Gerold Riempp,et al.  The State of Research on Information Systems Success , 2009, Bus. Inf. Syst. Eng..

[40]  Gary Shank,et al.  Six alternatives to mixed methods in qualitative research , 2006 .

[41]  Richard G. Lomax,et al.  A Beginner's Guide to Structural Equation Modeling , 2022 .

[42]  Thompson S. H. Teo,et al.  An empirical study of the performance impact of computerization in the retail industry , 1998 .

[43]  Jerry N. Luftman,et al.  Key Issues for IT Executives 2009: Difficult Economy’s Impact on IT , 2010, MIS Q. Executive.

[44]  J. Hair.  Multivariate data analysis , 1972 .

[45]  Gerold Riempp,et al.  A Methodological Examination of Empirical Research on Information Systems Success: 2003 to 2007 , 2008, AMCIS.

[46]  Ephraim R. McLean,et al.  Measuring information systems success: models, dimensions, measures, and interrelationships , 2008, Eur. J. Inf. Syst..

[47]  J. Creswell,et al.  Mixed Methods Research Designs in Counseling Psychology. , 2005 .

[48]  Diane M. Strong,et al.  AIMQ: a methodology for information quality assessment , 2002, Inf. Manag..

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

[50]  Diane M. Strong,et al.  Data quality in context , 1997, CACM.

[51]  Gee-Woo Bock,et al.  An Empirical Study on Measuring the Success of Knowledge Repository Systems , 2005, Proceedings of the 38th Annual Hawaii International Conference on System Sciences.

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

[53]  Ephraim R. McLean,et al.  Information Systems Success: The Quest for the Independent Variables , 2013, J. Manag. Inf. Syst..

[54]  R. Keeney,et al.  The Value of Internet Commerce to the Customer , 1999 .

[55]  T. E. Marshall,et al.  Business intelligence: an analysis of the literature , 2008 .

[56]  Cindi Howson,et al.  Successful Business Intelligence: Secrets to Making BI a Killer App , 2007 .

[57]  Yair Levy,et al.  A study of learners' perceived value and satisfaction for implied effectiveness of online learning systems , 2003 .

[58]  Anna Sidorova,et al.  Business intelligence success: The roles of BI capabilities and decision environments , 2013, Inf. Manag..

[59]  Keng Siau,et al.  Strategic implications of mobile technology: A case study using Value-Focused Thinking , 2005, J. Strateg. Inf. Syst..

[60]  Ephraim R. McLean,et al.  A meta-analytic assessment of the DeLone and McLean IS success model: An examination of IS success at the individual level , 2009, Inf. Manag..

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

[62]  Diane M. Strong,et al.  Beyond Accuracy: What Data Quality Means to Data Consumers , 1996, J. Manag. Inf. Syst..

[63]  Ruth C. King,et al.  Nonlinear and Noncompensatory Models in User Information Satisfaction Measurement , 1999, Inf. Syst. Res..

[64]  L. Marshall,et al.  Decision making in the context of business intelligence and data quality , 2009 .

[65]  Barbara Dinter,et al.  Towards a Life Cycle Oriented Business Intelligence Success Model , 2011, AMCIS.