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Literature review on disruption recovery in the supply chain

Ivanov, Dmitry, Dolgui, Alexandre, Sokolov, Boris, Ivanova, Marina·2017·International Journal of Production Research

Abstract

Recent research underlines the crucial role of disruption events and recovery policies in supply chains. Despite a wealth of literature on supply chain design with disruption considerations, to the best of our knowledge there is no survey on supply chain with disruptions and recovery considerations. We analyse state-of-the-art research streams on supply chain design and planning with both disruptions and recovery considerations with the aim of relating the existing quantitative methods to empirical research. The paper structures and classifies existing research streams and application areas of different quantitative methods subject to different disruption risks and recovery measures. We identify gaps in current research and delineate future research avenues. The results of this study are twofold: operations and supply chain managers can observe which quantitative tools are available for different application areas; on the other hand, limitations and future research needs for decision-support methods in supply chain risk management domains can be identified.

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Metadata

Authors
Ivanov, D., Dolgui, A., Sokolov, B., & Ivanova, M.
Venue
International Journal of Production Research
Published
2017-06
Volume
55
Issue
20
Pages
6158-6174
ISSN
  • 0020-7543 (ISSN-L)
  • 1366-588X
OpenAlex
W2614819110
Cited by
690
References
0
FWCI
107.46
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Literature review on disruption recovery in the supply chain. https://app.cochat.ai/papers/10.1080/00207543.2017.1330572
The paper
Ivanov, D., Dolgui, A., Sokolov, B., & Ivanova, M. (2017). Literature review on disruption recovery in the supply chain. International Journal of Production Research. https://doi.org/10.1080/00207543.2017.1330572

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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.