Integrating explanatory/predictive and prescriptive science in information systems research

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Abstract

The scholarly information systems (IS) field has a dual role. As an explanatory and predictive science, the field contributes to explaining the pervasive IS that shape the digital age and sometimes also makes predictions about those phenomena. As a prescriptive science, it participates in creating IS-related innovations by identifying means-ends relationships. The two can beneficially interact, such as when explanatory theory provides the basis for generating prescriptions or when applicable knowledge produces explanatory insights. In this commentary, we contribute to integrating these two roles by proposing a framework to help IS researchers navigate the field’s duality to extend the cumulative scholarly knowledge that it creates in terms of justified explanations and predictions and justified prescriptions. The process we describe builds on ongoing, dynamic, iterative, and interrelated research cycles. We identify a set of integrative research practices that occur at the interface between explanatory and predictive science and prescriptive science—the explanation-prescription nexus. We derive guidelines for IS research.

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APA

Seidel, S., & Watson, R. T. (2020). Integrating explanatory/predictive and prescriptive science in information systems research. Communications of the Association for Information Systems, 47, 284–314. https://doi.org/10.17705/1CAIS.04714

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