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

Sharma, Pratyush Nidhi, Sarstedt, Marko, Ringle, Christian M., Cheah, Jun Hwa ORCID: https://orcid.org/0000-0001-8440-9564, Herfurth, Anne and Hair, Joseph F. (2024) A framework for enhancing the replicability of behavioral MIS research using prediction oriented techniques. International Journal of Information Management, 78. ISSN 0268-4012

[thumbnail of 03. Manuscript-IJIM-PLS_Final-Accepted 29-4-2024] PDF (03. Manuscript-IJIM-PLS_Final-Accepted 29-4-2024) - Accepted Version
Restricted to Repository staff only until 15 May 2026.
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Request a copy

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.

Item Type: Article
Uncontrolled Keywords: confirmation,ep-mixed,explanation,exploration,open science,pls-sem,prediction,replicability,management information systems,information systems,computer networks and communications,information systems and management,marketing,library and information sciences,artificial intelligence ,/dk/atira/pure/subjectarea/asjc/1400/1404
Faculty \ School: Faculty of Social Sciences > Norwich Business School
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 02 Jul 2024 09:32
Last Modified: 08 Jul 2024 07:32
URI: https://ueaeprints.uea.ac.uk/id/eprint/95750
DOI: 10.1016/j.ijinfomgt.2024.102805

Actions (login required)

View Item View Item