首页|Logistics project risk response decision-making for global supply chain resilience and agility: an optimised case-based reasoning

Logistics project risk response decision-making for global supply chain resilience and agility: an optimised case-based reasoning

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ABSTRACT Logistics projects are critical to the functioning of the global supply chains (GSC), encountering various disruptions and risks. Sound Risk Response Decisions (RRDs) on logistics projects are imperative to ensure the GSC’s resilience and agility. Besides risk correlations, Project Interdependencies (PIs) and Limited Historical Information (LHI) impede RRDs. To address these challenges, an optimised Case-Based Reasoning combining the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Stratified Ordinal Priority Approach (SOPA) is proposed. Risks are categorised as referable and non-referable based on LHI using the Jaccard similarity. The strategies for referable risks are derived from similar cases retrieved through the weights of risks and project attributes and three similarities considering PIs. SOPA is developed to find weights with the Interdependent Uncertain Events (IUEs). DEMATEL is employed to access risk centrality degree similarity considering PIs and risk correlations. Expert input is sought for non-referable risk strategies. An optimisation model incorporating secondary risk correlations is built to generate strategies for all risks. The proposed approach is validated through a numerical example. Analysis informs that (1) PIs, LHI, and IUEs are necessary for sound RRDs; (2) decision outcomes are sensitive to logistics project managers who are risk-averse or exhibit moderate consideration of secondary risks.

Risk responselogistics projectcase-based reasoningsupply chain resilienceproject interdependency

Xu Zhang、Mark Goh、Sijun Bai、Libiao Bai

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Hohai University||Northwestern Polytechnical University||National University of Singapore

National University of Singapore

Northwestern Polytechnical University

Chang’an University

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2025

International journal of production research

International journal of production research

ISSN:0020-7543
年,卷(期):2025.63(7/8)
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