A framework for enhancing the replicability of behavioral MIS research using prediction oriented techniques

Pratyush Nidhi Sharma, Marko Sarstedt, Christian M. Ringle, Jun Hwa Cheah, Anne Herfurth, Joseph F. Hair

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

The ongoing scientific discourse surrounding the replication crisis in behavioral research, including management information systems (MIS) research, underscores the importance of innovative and rigorous approaches to theory development and validation. This article proposes the EP-mixed framework, which addresses the necessity of an ontological distinction between explanation and prediction in MIS theories, along with the epistemological challenges associated with conflating exploratory and confirmatory research during the design of robust, replicable theories. EP-mixed refers to theories that explain and predict (i.e., EP theories) developed using a mixed mode that combines the strengths of both exploratory and confirmatory research. The EP-mixed framework guides researchers in selecting appropriate analytical approaches based on their research goals and the type of theory being developed. While it can be applied in conjunction with a broad spectrum of statistical methods to enhance the robustness and replicability of MIS theories, we elaborate on the predictive analytic tools available in partial least squares structural equation modeling (PLS-SEM) as an exemplar for operationalizing the framework.

Original languageEnglish
Article number102805
JournalInternational Journal of Information Management
Volume78
Early online date15 May 2024
DOIs
Publication statusPublished - Oct 2024

Keywords

  • Confirmation
  • EP-mixed
  • Explanation
  • Exploration
  • Open Science
  • PLS-SEM
  • Prediction
  • Replicability

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