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Cited by 1,657

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Building operations management theory through case and field research

Meredith, Jack·1998·Journal of Operations Management

Abstract

Case and field research studies continue to be rarely published in operations management journals, in spite of increased interest in reporting such types of studies and results. This paper documents the advantages and rigor of case/field research and argues that these methods are preferred to the more traditional rationalist methods of optimization, simulation, and statistical modeling for building new operations management theories. In the process of describing the constructs of inference and generalizability with reference to case research, we find the existing definitions inadequate and thus extend and refine them to better discriminate between alternate research methodologies. We also elaborate on methods for increasing the generalizability of both rationalist and case/field research studies. A major conclusion is that these alternate research methods are not mutually exclusive and, if combined, can offer greater potential for enhancing new theories than either method alone.

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Metadata

Authors
Meredith, J.
Venue
Journal of Operations Management
Publisher
Wiley
Published
1998-07
Volume
16
Issue
4
Pages
441-454
ISSN
  • 0272-6963 (ISSN-L)
  • 1873-1317
OpenAlex
W2042893014
Cited by
1,657
References
2
FWCI
8.69
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Building operations management theory through case and field research. https://app.cochat.ai/papers/10.1016/s0272-6963(98)00023-0
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Meredith, J. (1998). Building operations management theory through case and field research. Journal of Operations Management. https://doi.org/10.1016/s0272-6963(98)00023-0

Data sources

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.