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Robust Sourcing from Suppliers under Ambiguously Correlated Major Disruption Risks

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  • Ming Zhao
  • Nickolas K. Freeman

Abstract

As the severity and frequency of supply chain disruptions increases due to globalization and outsourcing, companies are faced with the challenge of managing correlated disruption risks. However, correctly estimating supplier correlations is difficult and relying on incorrect estimates can be costly. Motivated by these challenges, we consider models for managing disruption risks when suppliers are ambiguously correlated. Our models are based on profit‐oriented correlation structures that only require accurate estimates of the marginal disruption probabilities for available suppliers. Analysis of the models, along with extensive numerical studies, show that they offer high‐quality solutions and provide several important insights regarding supplier selection, appropriate budgets for efforts to better understand the prevailing correlation structure, and identifying subsets of the available suppliers that should be considered for strategic alliances. In addition to these benefits, we discuss a progressive, profit‐oriented approach for risk management that is based on these models and is easily implemented in situations with minimal in formation regarding supplier correlations.

Suggested Citation

  • Ming Zhao & Nickolas K. Freeman, 2019. "Robust Sourcing from Suppliers under Ambiguously Correlated Major Disruption Risks," Production and Operations Management, Production and Operations Management Society, vol. 28(2), pages 441-456, February.
    • Handle: RePEc:bla:popmgt:v:28:y:2019:i:2:p:441-456
    DOI: 10.1111/poms.12933
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    Cited by:

    1. Ivanov, Dmitry & Dolgui, Alexandre, 2021. "OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implications," International Journal of Production Economics, Elsevier, vol. 232(C).
    2. Dong, Binwei & Tang, Wansheng & Zhou, Chi & Ren, Yufei, 2021. "Is dual sourcing a better choice? The impact of reliability improvement and contract manufacturer encroachment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    3. Rebecca Stekelorum & Shivam Gupta & Issam Laguir & Sameer Kumar & Subodha Kumar, 2022. "Pouring cement down one of your oil wells: Relationship between the supply chain disruption orientation and performance," Production and Operations Management, Production and Operations Management Society, vol. 31(5), pages 2084-2106, May.
    4. Zhao, Yujie & Zhou, Hong & Leus, Roel, 2022. "Recovery from demand disruption: Two-stage financing strategy for a capital-constrained supply chain under uncertainty," European Journal of Operational Research, Elsevier, vol. 303(2), pages 699-718.
    5. Li, Yi & Shou, Biying, 2021. "Managing supply risk: Robust procurement strategy for capacity improvement," Omega, Elsevier, vol. 102(C).
    6. Ming Zhao & Nickolas Freeman & Kai Pan, 2023. "Robust Sourcing Under Multilevel Supply Risks: Analysis of Random Yield and Capacity," INFORMS Journal on Computing, INFORMS, vol. 35(1), pages 178-195, January.
    7. Vafadarnikjoo, Amin & Tavana, Madjid & Chalvatzis, Konstantinos & Botelho, Tiago, 2022. "A socio-economic and environmental vulnerability assessment model with causal relationships in electric power supply chains," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    8. Ivanov, Dmitry, 2020. "Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).

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