Wieder, Bernhard Ossimitz, Maria-Luise Chamoni, Peter
Year of Publication:
[Journal:] International Journal of Economic Sciences and Applied Research [ISSN:] 1791-3373 [Volume:] 5 [Year:] 2012 [Issue:] 3 [Pages:] 7-32
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.
Business Intelligence (BI) information systems success data quality user satisfaction IT impact analysis