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Cited by 858

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Bridging organization theory and supply chain management: The case of best value supply chains

Ketchen, David J., Hult, G. Tomas M.·2007·Journal of Operations Management

Abstract

Rivalry is increasingly being contested at the supply chain level of analysis. Rather than competing “firm versus firm,” today's organizations are battling “supply chain versus supply chain.” Within this context, best value supply chains are emerging as a means to create competitive advantages and superior performance. While traditional supply chains often focus primarily on one key outcome such as speed or cost, best value supply chains excel along an array of uniquely integrated priorities—cost, quality, speed, and flexibility. We describe how key organizational theories help to distinguish traditional supply chains from best value supply chains. To provide a foundation for future inquiry, we offer theory‐based research questions that are focused on best value supply chains.

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Registry

Crossref · 10.1016/j.jom.2006.05.010

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Metadata

Authors
Ketchen, D. J., & Hult, G. T. M.
Venue
Journal of Operations Management
Publisher
Wiley
Published
2006-06-16
Volume
25
Issue
2
Pages
573-580
ISSN
  • 0272-6963 (ISSN-L)
  • 1873-1317
OpenAlex
W2146614620
Cited by
858
References
7
FWCI
18.75
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Bridging organization theory and supply chain management: The case of best value supply chains. https://app.cochat.ai/papers/10.1016/j.jom.2006.05.010
The paper
Ketchen, D. J., & Hult, G. T. M. (2007). Bridging organization theory and supply chain management: The case of best value supply chains. Journal of Operations Management. https://doi.org/10.1016/j.jom.2006.05.010

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.