The Perils and Promises of Big Data Research in Information Systems

Authors

Varun Grover, University of ArkansasFollow
Aron Lindberg, Stevens Institute of TechnologyFollow
Izak Benbasat, University of British ColumbiaFollow
Kalle Lyytinen, Case Western Reserve UniversityFollow

Abstract

With the proliferation of “big data” and powerful analytical techniques, information systems (IS) researchers are increasingly engaged in what we label as big data research (BDR)—research based on large digital trace datasets and computationally intensive methods. The number of such research papers has been growing rapidly in the top IS journals during the last decade, with roughly 16% of papers in 2018 employing this approach. In this editorial, we propose five conjectures that articulate the potential consequences of increasing BDR prevalence for the IS field’s research goals and outputs. We discuss ways in which IS researchers may be able to better leverage big data and new analysis techniques to conduct more impactful research. Our intent with these conjectures and analyses is to stimulate debate in the IS community. Indeed, we need a productive discussion about how emerging new research methods, digital trace data, and the development of indigenous theory relate to and can support one another.

Recommended Citation

Grover, Varun; Lindberg, Aron; Benbasat, Izak; and Lyytinen, Kalle (2020) "The Perils and Promises of Big Data Research in Information Systems," Journal of the Association for Information Systems, 21(2), .
DOI: 10.17705/1jais.00601
Available at: https://aisel.aisnet.org/jais/vol21/iss2/9

DOI

10.17705/1jais.00601