Structuring Business Intelligence (BI)-related research

Abstract

The Business intelligence (BI) literature has grown rapidly during the last three decades. Yet the knowledge about its theoretical underpinnings and its links to strategy research remain elusive. This state of affairs draws from two different scientific communities (informatics and business) that have generated multiple research streams, which duplicate research, neglect each other’s contributions, and overlook the relationship between BI and strategy. In response, we structure the BI scientific landscape and map its evolution to offer scholars and managers a clear view of where we stand and the way forward. For this endeavor, we conduct a systematic review of articles published in top-tier journals and identify 90 articles covering more than 30 years of scientific research on BI. We then run a co-citation analysis of selected articles and their reference lists. This yielded the structuring of BI scholarly community around six research clusters: Environmental Scanning (ES), Competitive Intelligence (CI), Market Intelligence (MI), Decision Support Systems (DSS), Intelligence Technologies (IT), and Knowing as Practice (KAP). The co-citation network exposed overlapping and divergent theoretical roots across the six clusters and permitted to map the evolution of BI following two pendulum swings. In light of the structure and evolution of the BI research, we offer a future research agenda that links BI to strategy work. Our article, thus, contributes by 1) structuring the theoretical landscape of BI research, 2) deciphering the theoretical roots of BI literature, 3) mapping the evolution of BI scholarly community, and 4) suggesting an agenda for research conducive to strategy.