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Cited by 406

The DOI matches its Crossref record; 92 of the 92 references it cites were found in a registry or an index.

Theorizing, testing, and concluding for mediation in SCM research: Tutorial and procedural recommendations

Rungtusanatham, M., Miller, J.W., Boyer, K.K.·2014·Journal of Operations Management

Abstract

Empirical research in Supply Chain Management is increasingly interested in complex models involving mediation effects. We support these endeavors by directing attention to the practices for the theorizing of, the testing for, and the drawing of conclusions about mediation effects. Our paper synthesizes diverse literature in other disciplines to provide an accessible tutorial as to the mathematical foundation of mediation effects and the various methods available to test for these effects. We also provide guidance to SCM scholars in the form of eight recommendations aimed at improving the theorizing of, the testing for, and the drawing of conclusions about mediation effects. Recommendations pertaining to how mediation effects are hypothesized and stated and how to select among methods to test for mediation effects are novel contributions for and beyond the Supply Chain Management discipline.

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Metadata

Authors
Rungtusanatham, M., Miller, J. W., & Boyer, K. K.
Venue
Journal of Operations Management
Publisher
Wiley
Published
2014-01-20
Volume
32
Issue
3
Pages
99-113
ISSN
  • 0272-6963 (ISSN-L)
  • 1873-1317
OpenAlex
W2066211352
Cited by
406
References
92
FWCI
15.12
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Theorizing, testing, and concluding for mediation in SCM research: Tutorial and procedural recommendations. https://app.cochat.ai/papers/10.1016/j.jom.2014.01.002
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Rungtusanatham, M., Miller, J. W., & Boyer, K. K. (2014). Theorizing, testing, and concluding for mediation in SCM research: Tutorial and procedural recommendations. Journal of Operations Management. https://doi.org/10.1016/j.jom.2014.01.002

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.