Efficient resilience portfolio design in the supply chain with consideration of preparedness and recovery investments

Riccardo Aldrighetti, Daria Battini and Dmitry Ivanov

Omega, 2023, vol. 117, issue C

Abstract: Supply chain (SC) resilience is imperative to cope with disruptions using some preparedness and recovery capabilities such as network redundancy (e.g., backup suppliers) and process flexibility (e.g., capacity agility). These capabilities frame an SC resilience portfolio. Both designing a resilient portfolio and recovering in case of a real disruption require investments. This paper presents a new mathematical model for designing an efficient resilience portfolio in a multi-echelon SC. Through computational and comparative analyses using a real-life case-study, we demonstrate that our model allows increasing resilience at minimal costs by determining an optimal combination of preparedness and recovery investments. Interestingly, the optimal solutions (i.e., efficient resilient SC designs) increase SC efficiency even in business-as-usual scenarios. This result contributes to the literature on transforming resilience from an expensive spend to a value-creation asset. We illustrate our approach using a real-life industrial example that allows for the identification of important relations between disruption duration/magnitude and efficiency of preparedness and recovery strategies. Based on computational, comparative, and case-study analyses, we deduce and generalize managerial implications at the network, supplier, and manufacturer levels. We take an extra step by extrapolating our major findings and generalized managerial implications toward the COVID-19 pandemic setting. The outcome of our research can be instructive for SC managers when deciding on investments in resilient redundancy allocation as a part of preparedness strategy and efficient recovery deployment.

Keywords: Supply chain resilience; Disruption risk; Supply chain network design; Efficiency; Covid-19 pandemic (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (14)

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DOI: 10.1016/j.omega.2023.102841

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