Some key ports exist in the Maritime Silk Road shipping network that have a high impact on the whole of maritime transportation. An efficient identification of these crucial ports is of great importance, to alleviate the spread of port congestion, control shipping delays, and improve transportation efficiency. This paper proposes a novel method to identify the key ports by comprehensively considering local propagation and global centrality (LPGC), based on the complex network theory. Taking the ports along the Maritime Silk Road shipping network as an example, the Susceptible–Infected–Susceptible (SIS) model and Kendall’s correlation coefficient are compared with several centrality measures to evaluate the feasibility and efficiency of the LPGC method. The obtained results demonstrate that, compared with the existing methods, the proposed method has higher accuracy and can more accurately identify the influential ports. Finally, the obtained port importance ranking also provides a theoretical basis for the selection of ports that should give a priority to maintaining or ensuring their service capacity in practice.


    Access

    Download

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Identifying Important Ports in Maritime Silk Road Shipping Network from Local and Global Perspective


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:
    Yang, Yanbin (author) / Liu, Wei (author) / Xu, Xu (author)


    Publication date :

    2022-06-06




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Identifying container shipping network bottlenecks along China’s Maritime Silk Road based on a spectral analysis

    Pan, Jingjing / Bell, Michael G. H. / Cheung, Kam-Fung et al. | Taylor & Francis Verlag | 2021


    Safety evaluation of the ports along the Maritime Silk Road

    Jiang, Meizhi / Lu, Jing / Qu, Zhuohua et al. | Taylor & Francis Verlag | 2022

    Free access

    Improved Link Prediction Method for Maritime Silk Road Shipping Network Using Composite Index

    Zhu, Junfeng / Yang, Yanbin / Jin, Yuping et al. | Transportation Research Record | 2023