Business intelligence systems’ success: A comprehensive approach
Business intelligence (BI) systems have been questioned as regards the benefits and returns obtained after implementation. These questions arise because the product of BI is intelligence (i.e., some kind of processed information) and the value of information is difficult to assess. This research aims to address the issue of evaluation of BI systems using the information systems success model (ISSM) proposed by DeLone and McLean, going beyond the traditional interrelated dimensions of BI capabilities, quality of information, user satisfaction, and usage level. Decision approach is included as a variable since a key objective of BI systems is to process data from different sources to produce information that serves as a basis for the decision-making process. The research problem was addressed by a web-based survey methodology, and of the 483 responses, 246 were usable. The structural equation modeling (SEM) was used to analyze the data with the software SMART-PLS. The results empirically proved all the causal relationships proposed between success dimensions of BI systems, except for the moderation effect of the variable of decision-making approach on the relationship between satisfaction and usage level. The results show that BI success can be defined in terms of BI capability, the quality of information, user satisfaction, decision-making approach, and usage level. The main practical implication of this research is that promoting analytical decision-making reduces subjectivity and increases success in BI systems implementations.