The Influence of Organizational Absorptive Capacity on Business Intelligence Systems Output in Strategic Management Perspective

Abstract

The last decade has witnessed accelerated growth in investment in business intelligence (BI) systems. We still lack, however, a clear view as to when a particular system should be preferred over the others. This paper examines the role of the BI use for enhancing an organizational absorptive capacity (ACAP) for knowledge creation and proposes a model to investigate its direct effects on further firm’s performance. We collected survey data from 150 experts and decision-makers at the organizational level from several industries. For data analysis, we followed the general coding, aggregation and synthesis process with the use of the qualitative data analysis software. The results from the Partial Least Squares — Structural Equation Modelling (PLS-SEM) demonstrated that the BI use relates significantly to ACAP enhancement, thus fostering knowledge creation. Moreover, information quality and system quality are positively linked with BI use at the organizational level. The results demonstrate that organizational ACAP is critical to establishing appropriate technology infrastructure and to assimilating BI systems for organizational efficiency. Accordingly, the core contribution of the research provided a more comprehensive framework that serves managers and strategic professionals to assist them in classifying their ACAP measures before attempting to purchase state of the art BI systems with a high amount of expenditures. Instead, they should pay attention to the nature of use considering it as a very important determinant of the BI use and reconcile the nature of the use with the intended organizational benefits. Second, the mediation role of the BI use supports the notion that managers should carefully opt for both high system quality and information quality of the installed BI systems. This raises trust in BI and prevents managers from reverting to intuitive decision-making and the underuse of BI.