Of BI research: a tale of two communities

Abstract

Purpose The business intelligence (BI) literature is in a flux, yet the knowledge about its varying theoretical roots remains 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 important research gaps. In response, the authors structure the BI scientific landscape and map its evolution to offer scholars a clear view of where research on BI stands and the way forward. For this endeavor, the authors systematically review articles published in top-tier ABS journals and identify 120 articles covering 35 years of scientific research on BI. The authors then run a co-citation analysis of selected articles and their reference lists. This yields the structuring of BI scholarly community around six research clusters: environmental scanning (ES), competitive intelligence (CI), market intelligence (MI), decision support (DS), analytical technologies (AT) and analytical capabilities (AC). The co-citation network exposed overlapping and divergent theoretical roots across the six clusters and permitted mapping the evolution of BI research following two pendulum swings. This study aims to contribute by structuring the theoretical landscape of BI research, deciphering the theoretical roots of BI literature, mapping the evolution of BI scholarly community and suggesting an agenda for future research. Design/methodology/approach This paper follows a systematic methodology to isolate peer-reviewed papers on BI published in top-tier ABS journals. Findings The authors present the structuring of BI scholarly community around six research clusters: ES, CI, MI, DS, AT and AC. The authors also expose overlapping and divergent theoretical roots across the six clusters and map the evolution of BI following two pendulum swings. In light of the structure and evolution of the BI research, the authors offer a future research agenda for BI research. Originality/value This study contributes by elucidating the theoretical underpinnings of the BI literature and shedding light upon the evolution, the contributions, and the research gaps for each of the six clusters composing the BI body of knowledge.

Toward a taxonomy of dynamic capabilities – a systematic literature review

“…Its systematic and evidence-informed nature shall decrease the chance of bias by the researcher and increase rigor compared to traditional “narrative” reviews. This approach has become the gold standard in business science and has also been applied in several recent literature reviews (Kahn et al , 2020; Talaoui and Kohtamäki, 2020).…”

35 years of research on business intelligence process: a synthesis of a fragmented literature

“…The business intelligence (BI) process research has grown exponentially during the past three decades into a fragmented state drawing from a diverse set of studies with widely different contributions (Talaoui and Kohtamäki, 2020). Although this pluralism is necessary for the BI process research to generate momentum from insightful findings, it can yield a disjointed theoretical progress if it lacks proper literature reviews that uncover what is already known and set a direction for the way ahead (Hart, 1998; Rowe, 2014).…”

Innovation and Competitive Intelligence in Business. A Bibliometric Analysis

“…The rise of Information Communication Technologies (ICTs) has also been associated with Competitive Intelligence and innovation processes (Gordon et al 2008), where some authors highlight how the use of social networks, the spectacular development of the Web, big data and other tools have generated an exponential growth in the information available (Lichtenthaler 2005;Rothberg and Erickson 2017). Finally, it is worth highlighting those publications that address theoretical perspectives (Chevallier et al 2016;Hoppe 2013;Hughes 2017) and reviews on this subject (López-Robles et al 2019a;Talaoui and Kohtamäki 2020).…”