Multi-Component Resilience Assessment Framework for a Supply Chain System

Jie Zhao, Ji Yun Lee (), Dane Camenzind, Michael Wolcott, Kristin Lewis and Olivia Gillham
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Jie Zhao: Verisk Extreme Event Solutions, Boston, MA 02111, USA
Ji Yun Lee: Department of Civil & Environmental Engineering, Washington State University, Pullman, WA 99164, USA
Dane Camenzind: Department of Civil & Environmental Engineering, Washington State University, Pullman, WA 99164, USA
Michael Wolcott: Department of Civil & Environmental Engineering, Washington State University, Pullman, WA 99164, USA
Kristin Lewis: U.S. DOT Volpe Center, Cambridge, MA 02142, USA
Olivia Gillham: U.S. DOT Volpe Center, Cambridge, MA 02142, USA

Sustainability, 2023, vol. 15, issue 7, 1-25

Abstract: The goal of this paper is to develop a quantitative resilience assessment framework for a supply chain system exposed to multiple risk factors. Most existing studies on supply chain resilience have primarily focused on assessing the system’s ability to withstand and recover from disruptions caused by a single type of hazard. However, a supply chain system is exposed to multiple exogenous and endogenous events and conditions over a planning horizon, and a comprehensive assessment of resilience should take into account multiple risk factors. Moreover, contrary to the conventional resilience assessment methods focusing on the short duration during which the system is impacted by a disaster event, the proposed framework measures the resilience capacities of the system over a long-term horizon through multi-risk assessment and multi-component resilience assessment. Specifically, a new multi-component resilience index is proposed to measure (a) hazard-induced cumulative loss of functionality, (b) opportunity-induced cumulative gain of functionality, and (c) non-hazard-induced cumulative loss of functionality. The case study results indicate that all three types of risk factors contribute to the overall resilience index significantly and ignoring any one of them may result in inaccurate supply chain performance and resilience assessment.

Keywords: hazard analysis; risk assessment; resilience; supply chain; earthquake; multiple risks; probabilistic approach (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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