Supply Chain Resilience Assessment With Financial Considerations: A Bayesian Network-Based Method

• Published in: IEEE transactions on engineering management Vol. 70; no. 6; pp. 2241 - 2256
• Main Authors: Shi, Wanying, Mena, Carlos
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Bayes methods; Bayesian analysis; Bayesian networks (BNs); Financial factors; Lead time; Network reliability; Performance evaluation; Probability distribution; Random variables; Recoverability; Reliability; Reliability aspects; Resilience; Resists; supply chain finance (SCF); supply chain resilience (SCR); Supply chains
• ISSN: 0018-9391; 1558-0040
• DOI: 10.1109/TEM.2021.3066600

Supply chain resilience assessment and strengthening has become a strategic topic in supply chain management. Extant literature on the subject of supply chain resilience assessment mainly focuses on evaluating the operational performance (e.g., inventory, capacity, lead time) while overlooking aspects of the financial performance. This article presents an event-based Bayesian approach as an effective tool for modeling the causal relationships among variables at different time intervals to evaluate resilience across operational and financial criteria. The model focuses on two key elements of resilience-reliability (the ability of the system to sustain an original state) and recoverability (the ability of a system to recover following a disruption), which allows us to investigate how different operational and financial factors affect the network reliability, recoverability, and resilience. This article contributes to the literature in three ways-first, we incorporate a financial perspective to the quantitative study of supply chain resilience; second, we evaluate both the financial and operational aspects from a longitudinal perspective; third, we show that the financial performance of individual supply chain entities has a strong influence on the overall supply chain resilience. From a practical standpoint, the article presents a model that can help managers identify the weakest nodes in their supply chain, considering operational and financial aspects over time, allowing them to design and operate more resilient supply networks.