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Data-driven approach for port resilience evaluation

Bingmei Gu, Jiaguo Liu, Xiaoheng Ye, Yu Gong and Jihong Chen

Transportation Research Part E: Logistics and Transportation Review, 2024, vol. 186, issue C

Abstract: As pivotal nodes in international trade, ports have faced unprecedented challenges, particularly in the context of the COVID-19 pandemic. From the perspective of port congestion, this study investigates port resilience based on a quantitative approach. Port resilience is specifically evaluated using five novel metrics derived from resilience capacities and port congestion indexes, employing data-driven approaches, which are then applied to analyze nine global ports across six regions. The findings of the study indicate that: 1) The ports of Southampton and Shanghai display better resilience levels, whereas New York/New Jersey and Los Angeles/Long Beach show poorer resilience performance during the research period. 2) Ports in West Coast North America demonstrate relatively low resilience levels, while those in South East Asia showcase superior resilience. 3) The changing dynamics and evolution of port resilience rankings across different years underscore the multifaceted nature of port resilience and its capacity to adapt to external factors such as global events. Our study emphasizes the importance of quantifying port resilience, with a specific focus on port congestion. It provides valuable insights that have significant implications for port management and disaster preparedness within the maritime industry.

Keywords: Port resilience; Resilience metric; Data-driven; Machine learning; Port congestion (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.tre.2024.103570

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