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The Impact of Business Intelligence Tools on Performance: A User Satisfaction Paradox?

Author

Listed:
  • Bernhard Wieder

    (UTS Business School - Accounting, University of Technology, Sydney, Australia)

  • Maria-Luise Ossimitz

    (UTS Business School - Accounting, University of Technology, Sydney, Australia)

  • Peter Chamoni

    (Mercator School of Management, University Duisburg-Essen, Germany)

Abstract

While Business Intelligence (BI) initiatives have been a top-priority of CIOs around the world for several years, accounting for billions of USD of IT investments per annum (IDC), academic research on the actual benefits derived from BI tools and the drivers of these benefits remain sparse. This paper reports the findings of an exploratory, cross-sectional field study investigating the factors that define and drive benefits associated with the deployment of dedicated BI tools. BI is broadly defined as an analytical process which transforms fragmented data of enterprises and markets into action-oriented information or knowledge about objectives, opportunities and positions of an organization; BI tools are software products primarily designed and deployed to support this analytical process (e.g. data warehouse software, data mining software, digital dashboards applications). Building upon DeLoneand McLean’s (1992; 2002; 2003) information systems success model, we develop, test and refine a BI quality and performance model adapted for the specific purpose, application, user group and technology of BI tools. The ultimate performance predictors in this model are user satisfaction and the impact of BI tools on managerial decision quality, both of which are determined by data quality. Partial Least Square (PLS) modeling is used to analyze data collected in a survey administered to IT executives of large Australian Stock Exchange (ASX) listed companies. The results confirm some of the theoretical relationships established in – especially the original – DeLone-McLean model in the specific context of BI. More importantly, the results also confirm the important role of explicit BI management as antecedent of benefits derived from BI tools, and the key impact of data quality on managerial decision making and organizational performance. However, the results also reveal a ‘user satisfaction paradox’: In contrast to the predictions derived from the DeLone-McLean model, organizational performance is negatively associated with user satisfaction with BI tools. Financial performance data collected for ex-post verification of this unexpected result confirm this paradox. We discuss BI-specific interpretations of these unexpected findings and provide avenues for future research.

Suggested Citation

  • Bernhard Wieder & Maria-Luise Ossimitz & Peter Chamoni, 2012. "The Impact of Business Intelligence Tools on Performance: A User Satisfaction Paradox?," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 5(3), pages 7-32, December.
    • Handle: RePEc:tei:journl:v:5:y:2012:i:3:p:7-32
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    References listed on IDEAS

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    1. Elbashir, Mohamed Z. & Collier, Philip A. & Davern, Michael J., 2008. "Measuring the effects of business intelligence systems: The relationship between business process and organizational performance," International Journal of Accounting Information Systems, Elsevier, vol. 9(3), pages 135-153.
    2. John Hulland, 1999. "Use of partial least squares (PLS) in strategic management research: a review of four recent studies," Strategic Management Journal, Wiley Blackwell, vol. 20(2), pages 195-204, February.
    3. Éric Foley & Manon G. Guillemette, 2010. "What is Business Intelligence?," International Journal of Business Intelligence Research (IJBIR), IGI Global, vol. 1(4), pages 1-28, October.
    4. Michael J. Tippins & Ravipreet S. Sohi, 2003. "IT competency and firm performance: is organizational learning a missing link?," Strategic Management Journal, Wiley Blackwell, vol. 24(8), pages 745-761, August.
    5. Stanley F. Slater & Eric M. Olson, 2000. "Strategy type and performance: the influence of sales force management," Strategic Management Journal, Wiley Blackwell, vol. 21(8), pages 813-829, August.
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    Cited by:

    1. Gonzales, Rolando & Wareham, Jonathan, 2019. "Analysing the impact of a business intelligence system and new conceptualizations of system use," Journal of Economics, Finance and Administrative Science, Universidad ESAN, vol. 24(48), pages 345-368.
    2. Jae-Woong Jeong & Heon-Hwi Lee & Hun Park, 2022. "A Study on the Effect of Knowledge Services on Organizational Performances Based on the Concept of Balanced Scorecards for the Sustainable Growth of Firms: Evidence from South Korea," Sustainability, MDPI, vol. 14(19), pages 1-19, October.
    3. Benita M. Gullkvist, 2013. "Drivers of change in management accounting practices in an ERP environment," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 6(2), pages 149-174, September.
    4. Remigiusz Tunowski, 2020. "Sustainability of Commercial Banks Supported by Business Intelligence System," Sustainability, MDPI, vol. 12(11), pages 1-17, June.
    5. Andreas G. Georgantopoulos & Evangelos I. Poutos & Nikolaos Eriotis, 2018. "Recent Developments and Trends in Accounting Information Systems," Journal of Accounting, Business and Finance Research, Scientific Publishing Institute, vol. 3(1), pages 1-9.
    6. Dekar Urumsah & Heri Ramadhansyah, 2019. "Investigating The Influence Of Business Intelligence On The Quality Of Decision Making In An Indonesian Fertilizer Company," Journal of Contemporary Accounting, Master in Accounting Program, Faculty of Business & Economics, Universitas Islam Indonesia, Yogyakarta, Indonesia, vol. 1(2), pages 120-129, May.

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    More about this item

    Keywords

    Business Intelligence (BI); information systems success; data quality; user satisfaction; IT impact analysis;
    All these keywords.

    JEL classification:

    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • M40 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - General

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