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Resilience Analysis of Container Port Shipping Network Structure: The Case of China

Author

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  • Yao He

    (College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China)

  • Yongchun Yang

    (College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
    Key Laboratory of Western China’s Environmental Systems, Ministry of Education of the People’s Republic of China, Lanzhou University, Lanzhou 730000, China)

  • Meimei Wang

    (College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China)

  • Xudong Zhang

    (College of Urban and Environmental Sciences, Peking University, Beijing 100871, China)

Abstract

The increased port outages caused by events such as war and public health emergencies have motivated the study of container port shipping network (CPSN) resilience. This paper proposes a resilience framework, which includes prevention, resistance, restoration, adaption, and optimization. The framework is used to analyze the resilience of the CPSN by detecting changing performance of the network indicators before and after the random attack or one of the deliberate attacks. The indicators include the network resilience index, degree distribution, independent path, cluster coefficient, network efficiency and connectivity. The comparative analysis is based on the statistics of China’s cases in 2005 and 2017. The results indicate that, first, the resilience of the structure of China’s container port shipping network (CCPSN) in 2017 has improved when comparing the 2015 situation. Second, the performance of indicators under betweenness attack (BA) decreases faster than other attacks; the resilience index of deliberate attacks is poorer, when compared with the random attack (RA). Third, network resilience can be improved by protecting and adding hub port nodes. Priority should be given to restoring the hub port nodes during the recovery process. The same network indicator recovers similarly after facing different attacks, while different indicator shows various recovery process. Thus, it is necessary to consider the different recovery performances of network indicators when the damaged CPSN selects recovery mode.

Suggested Citation

  • Yao He & Yongchun Yang & Meimei Wang & Xudong Zhang, 2022. "Resilience Analysis of Container Port Shipping Network Structure: The Case of China," Sustainability, MDPI, vol. 14(15), pages 1-17, August.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9489-:d:878551
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