Abstract
Although multidisciplinary by nature, the Hawaii International Conference on Systems Sciences (HICSS) has established itself as the leading international conference in business intelligence (BI), business analytics (BA) and, more recently, big data research. Given a large number of academic and industry conferences in these areas, it is worth reflecting on and learning from the long tradition of BI and BA research at HICSS. In this paper, we analyze the 28-year history of HICSS’ longest-running minitrack on BI and BA in order to identify its main research themes and reflect on their evolution over time. Our insights provide research grounding for the current thinking about the big data phenomenon, which, contrary to many statements, is not new. We also illustrate a practical method of combining a semantic text-mining tool (Leximancer) and collaborative sensemaking. Reflecting on the method, we argue that technology itself—regardless of how sophisticated it might be—does not generate meaningful insights. Rather, we argue that domain experts co-construct these insights through an iterative collaborative sensemaking process in a given context, an important point that other researchers interested in semantic text-mining tools should consider.
DOI
10.17705/1CAIS.04340
Recommended Citation
Marjanovic, O., & Dinter, B. (2018). Learning from the History of Business Intelligence and Analytics Research at HICSS: A Semantic Text-mining Approach. Communications of the Association for Information Systems, 43, pp-pp. https://doi.org/10.17705/1CAIS.04340
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