Risk analysis of supply chains: The role of supporting structures and infrastructure

Fabrizio Nocera, Alessandro Contento and Paolo Gardoni

Reliability Engineering and System Safety, 2024, vol. 241, issue C

Abstract: Supply chains include multimodal transportation infrastructure that span multiple countries for sourcing and supplying goods and services. Natural hazards may damage components of the multimodal transportation infrastructure making transportation segments unavailable, requiring alternative routes, and limiting the performance of hubs. Past events have shown that the economic consequences of the disaster-related damage and failure of infrastructure are typically significantly larger than the direct economic impact, i.e., the cost of repair of such infrastructure. Also, the impact often is not limited to the immediate aftermath of a natural hazard but can be longstanding. While extensive research has been devoted to assessing the performance of infrastructure when facing a natural hazard, limited studies focused on the cascading effects of the failure of infrastructure on the performance of supply chains and businesses. This paper proposes a mathematical formulation to model and quantify the impact of hazards on supply chains by modeling the dependency of supply chain operations on the performance of structures and infrastructure and their potential damage. To capture such an impact, the formulation estimates the losses of retailers due to lack of goods to sell to their customers. The formulation presented in the paper is illustrated with two examples. The first example is a simplified supply chain. The second example is a full-scale, realistic example based on a portion of the supply chain of a nationwide business.

Keywords: Risk analysis; Supply chains; System-of-Systems modeling; Multimodal transportation infrastructure (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:241:y:2024:i:c:s0951832023005379

DOI: 10.1016/j.ress.2023.109623

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