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Analysis of vulnerabilities in maritime supply chains

Liu, H, Tian, Z, Huang, A and Yang, Z (2017) Analysis of vulnerabilities in maritime supply chains. Reliability Engineering and System Safety, 169. pp. 475-484. ISSN 0951-8320

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Abstract

This paper aims to analyze the different concepts of “vulnerability” used in maritime supply chains, and to develop a novel framework with supporting models to identify and analyze the relevant vulnerabilities in the chains. A real case of the Maersk shipping line in its Asia-Europe route is studied to demonstrate the applicability of the proposed framework. We find that the investigated network has stronger robustness against random failures than that when facing deliberate attacks. Furthermore, to identify vulnerable nodes (i.e. ports) of the network, two different types of analysis are undertaken through a multi-centrality model and a robustness analysis model, respectively. Consequently, the vulnerabilities estimated through robustness analysis can ascertain those by the classical centrality methods when they appear on both analysis results. More importantly, the similarity between the two outcomes can help gain more confidence on the accuracy in terms of the identification of the vulnerabilities in the system, while the difference (if any) such as those identified by the robustness analysis but not by the centrality analysis (or vice versa) can trigger a further investigation to find the comprehensive vulnerable nodes against different threats/hazards. It will aid rational decision on design and operation of resilient and robust maritime supply chains. © 2017 Elsevier Ltd

Item Type: Article
Uncontrolled Keywords: 09 Engineering, 15 Commerce, Management, Tourism And Services, 01 Mathematical Sciences
Subjects: H Social Sciences > HF Commerce > HF5001 Business
H Social Sciences > HF Commerce > HF5001 Business > HF5410 Marketing. Distribution of Products
Divisions: Maritime & Mechanical Engineering (merged with Engineering 10 Aug 20)
Publisher: Elsevier
Date Deposited: 05 Dec 2017 11:58
Last Modified: 04 Sep 2021 10:56
DOI or ID number: 10.1016/j.ress.2017.09.018
URI: https://researchonline.ljmu.ac.uk/id/eprint/7668
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