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A hybrid risks-informed approach for the selection of supplier portfolio

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  • Chao Fang
  • Xiangxiang Liao
  • Min Xie

Abstract

In conventional supplier selection approaches, cost consideration is usually emphasised and it renders a vulnerable supply chain with various risks. This article aims to develop a quantitative approach for modelling both supply chain operational risks and disruption risks to support decision-making with regard to order allocation and risk mitigation. We introduce two types of risk evaluation models: value-at-risk (VaR) and conditional value-at-risk (CVaR). Specifically, VaR is used to measure operational risks caused by improper selection and operations of a supplier portfolio to the stochastic demand, which may frequently occur but result in relatively small losses to supply chains; CVaR is used to evaluate disruption risks that are less frequent and tend to cause significant damage. After incorporating risk factors into a probability-based multi-criteria optimisation model, different methods and parameters are compared and tested to determine the factors that may influence the supplier selection process. Computational examples by simulation are presented to illustrate the approach and how decision-makers make trade-offs between costs and hybrid risks.

Suggested Citation

  • Chao Fang & Xiangxiang Liao & Min Xie, 2016. "A hybrid risks-informed approach for the selection of supplier portfolio," International Journal of Production Research, Taylor & Francis Journals, vol. 54(7), pages 2019-2034, April.
    • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:7:p:2019-2034
    DOI: 10.1080/00207543.2015.1076947
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    2. Marcus V. C. Fagundes & Bernd Hellingrath & Francisco G. M. Freires, 2021. "Supplier Selection Risk: A New Computer-Based Decision-Making System with Fuzzy Extended AHP," Logistics, MDPI, vol. 5(1), pages 1-17, March.
    3. Vijaya Dixit & Manoj Kumar Tiwari, 2020. "Project portfolio selection and scheduling optimization based on risk measure: a conditional value at risk approach," Annals of Operations Research, Springer, vol. 285(1), pages 9-33, February.
    4. Merve Er Kara & Seniye Ümit Oktay Fırat, 2018. "Supplier Risk Assessment Based on Best-Worst Method and K-Means Clustering: A Case Study," Sustainability, MDPI, vol. 10(4), pages 1-25, April.

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