Abstract
Supply chains are exposed to different risks, which can be mitigated by various strategies based on the characteristics and needs of companies. In collaboration with Ford, we develop a decision support framework to choose the best mitigation strategy against supply disruption risk, especially for companies operating with a small supplier base and low inventory levels. Our framework is based on a multistage stochastic programming model which incorporates a variety of plausible strategies, including reserving backup capacity from the primary supplier, reserving capacity from a secondary supplier, and holding backup inventory. We reflect disruption risk into the framework through decision makers’ input on the time to recover and the disruption probability. Our results demonstrate that relying on the strategy which is optimal when there is no disruption risk can increase the expected total cost substantially in the presence of disruption risk. However, this increase can be reduced significantly by investing in the mitigation strategy recommended by our framework. Our results also show that this framework removes the burden of estimating the time to recover and the disruption probability precisely since there is often a small loss associated with using another strategy that is optimal in the neighbourhood of the estimated values.
Original language | English |
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Pages (from-to) | 5956-5976 |
Number of pages | 21 |
Journal | International Journal of Production Research |
Volume | 60 |
Issue number | 19 |
Early online date | 23 Sept 2021 |
DOIs | |
Publication status | Published - 31 Dec 2022 |
Bibliographical note
Funding Information:This work is supported by a grant from the Ford Motor Company, project grant number N025042. We are thankful to Colleen Montgomery, Scott Moore, Christopher Recktenwald, Paul Prestel from Ford Purchasing and Varsha Venkatesh from Ford Global Data, Insight and Analytics for their valuable contribution. Also, we would like to extend our thanks to the associate editor and anonymous reviewers for their insightful comments and constructive suggestions to improve the manuscript.
Keywords
- Supply chain risk management
- contingency planning
- disruption risk mitigation
- multistage stochastic programming
- sourcing mitigation
ASJC Scopus subject areas
- Strategy and Management
- Management Science and Operations Research
- Industrial and Manufacturing Engineering