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Cited by 385

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Supply chain operational risk mitigation: a collaborative approach

Open access
Chen, Jie, Sohal, Amrik S., Prajogo, Daniel I.·2013·International Journal of Production Research

Abstract

Along with increasing supply chain risks due to economic and environmental changes, it is imperative to answer the question of how to reduce supply chain risks. This study examines supply chain collaboration as a risk mitigation strategy. The study examines three types of risks, namely supply risk, demand risk and process risk in relation to three types of collaboration, namely supplier collaboration, customer collaboration and internal collaboration, as a mechanism to mitigate those risks. The proposed relationship model is tested with data collected from 203 manufacturing companies in Australia. The results show that each area of collaboration effectively reduces its respective supply chain risk, but only the mitigation of process risk and demand risk has a direct effect on supply chain performance. In addition, both supply risk and demand risk increase process risk. We offer theoretical and practical implications of the findings.

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Metadata

Authors
Chen, J., Sohal, A. S., & Prajogo, D. I.
Venue
International Journal of Production Research
Published
2013-04
Volume
51
Issue
7
Pages
2186-2199
ISSN
  • 0020-7543 (ISSN-L)
  • 1366-588X
OpenAlex
W2082632948
Cited by
385
References
4
FWCI
21.11
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Supply chain operational risk mitigation: a collaborative approach. https://app.cochat.ai/papers/10.1080/00207543.2012.727490
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Chen, J., Sohal, A. S., & Prajogo, D. I. (2013). Supply chain operational risk mitigation: a collaborative approach. International Journal of Production Research. https://doi.org/10.1080/00207543.2012.727490

Data sources

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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.