Title: A quantified hypervulnerability approach for assessing resilience in supply chain networks

Authors: Katherine Smith; Rafael Diaz; Yuzhong Shen

Addresses: Virginia Modeling, Analysis and Simulation Center, Old Dominion University, 1030 University Blvd., Suffolk, VA, 23435, USA ' School of Cybersecurity, Old Dominion University, 1113A Monarch Hall, Norfolk, VA 23529, USA ' Department of Electrical and Computer Engineering, Old Dominion University, 231 Kaufman Hall, Norfolk, VA 23529, USA

Abstract: The COVID-19 pandemic highlighted the vulnerability of supply chain networks to sources of concurrent disruption. This research investigates and broadens a quantified, generalised definition of vulnerability, which enables a group of entities to be identified as highly, or hyper, vulnerable. This concept of hypervulnerability thresholds is demonstrated on a conceptual example. The example explains and shows how the definition of hypervulnerability thresholds can be applied. A maritime supply chain case study with various risks and disruptions is presented and analysed to demonstrate the practical utility of the approach and provide valuable information to guide decision making in other applications. Finally, the article concludes with answers to research questions and directions for future work.

Keywords: supply chain; vulnerability; resilience; systems theory; disruption; risk.

DOI: 10.1504/IJSPM.2024.143849

International Journal of Simulation and Process Modelling, 2024 Vol.21 No.3, pp.166 - 178

Received: 18 Oct 2023
Accepted: 07 Jun 2024
Published online: 10 Jan 2025 *

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