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Spatial heterogeneity of ports in the global maritime network detected by weighted ego network analysis

Author

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  • Chengliang Liu
  • Jiaqi Wang
  • Hong Zhang

Abstract

More extensive attention has been paid to the heterogeneity of maritime transport network in topological rather than in spatial aspects. However, the importance of links and the roles of neighbors of a node has been ignored if not all. To fill this gap, this article introduced the approach of weighted ego network analysis (WENA) to visualize the spatial heterogeneity of the maritime network at global and local levels. The topological connectivity graph of the global marine network was derived, and its structural properties were analyzed. It is found out that the values of the degree of ports follow power-law distribution, which indicates that the global marine network is scale-free, that is, there are few well-connected ports and a majority of less connected ports. The spatial disparities of the network can be described by a core–periphery pattern. In global, most of the hubs or ports with extremely high values of degree locate in the big-three maritime regions including Far East, North America, and West Europe. Along the peripheral belts of the three regions, there are lots of less connected small ports. A different hierarchical structure of six continents was captured by WENA. It is found that Europe, Asia, North America, and Africa showcase a pyramid-shaped hierarchical structure with a scale-free feature similar to the entire network, while South America and Oceania exhibit the fusiform hierarchy like small-world networks. It is proposed that such spatial inequality and heterogeneity were caused by the geographical environments such as the hub-and-spoke organization, the embedded trade pattern, and the proximity of location. These findings help us to understand the characteristics of the international trade pattern and shed light on the strategies of development for the industry stakeholders.

Suggested Citation

  • Chengliang Liu & Jiaqi Wang & Hong Zhang, 2018. "Spatial heterogeneity of ports in the global maritime network detected by weighted ego network analysis," Maritime Policy & Management, Taylor & Francis Journals, vol. 45(1), pages 89-104, January.
  • Handle: RePEc:taf:marpmg:v:45:y:2018:i:1:p:89-104
    DOI: 10.1080/03088839.2017.1345019
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    Cited by:

    1. Penghao Ye & Huarong Zhang & Siyi Ma & Fang Yang & Yanan Li, 2022. "A Knowledge Map Study of an Application of a Smart Land Planning Free-Trade Zone and China’s Contribution," Land, MDPI, vol. 11(6), pages 1-21, June.
    2. Laure Rousset & César Ducruet, 2020. "Disruptions in Spatial Networks: a Comparative Study of Major Shocks Affecting Ports and Shipping Patterns," Post-Print halshs-02588551, HAL.
    3. Zhang, Qiang & Pu, Shunhao & Luo, Lihua & Liu, Zhichao & Xu, Jie, 2022. "Revisiting important ports in container shipping networks: A structural hole-based approach," Transport Policy, Elsevier, vol. 126(C), pages 239-248.
    4. Asadabadi, Ali & Miller-Hooks, Elise, 2020. "Maritime port network resiliency and reliability through co-opetition," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 137(C).
    5. Chengliang Liu & Caicheng Niu & Ji Han, 2019. "Spatial Dynamics of Intercity Technology Transfer Networks in China’s Three Urban Agglomerations: A Patent Transaction Perspective," Sustainability, MDPI, vol. 11(6), pages 1-24, March.
    6. Laure Rousset & César Ducruet, 2020. "Disruptions in Spatial Networks: a Comparative Study of Major Shocks Affecting Ports and Shipping Patterns," Networks and Spatial Economics, Springer, vol. 20(2), pages 423-447, June.
    7. Bai, Xiwen & Ma, Zhongjun & Zhou, Yaoming, 2023. "Data-driven static and dynamic resilience assessment of the global liner shipping network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).
    8. Yu, Hongchu & Fang, Zhixiang & Lu, Feng & Murray, Alan T. & Zhang, Hengcai & Peng, Peng & Mei, Qiang & Chen, Jinhai, 2019. "Impact of oil price fluctuations on tanker maritime network structure and traffic flow changes," Applied Energy, Elsevier, vol. 237(C), pages 390-403.
    9. Liu, Chengliang & Duan, Dezhong, 2020. "Spatial inequality of bus transit dependence on urban streets and its relationships with socioeconomic intensities: A tale of two megacities in China," Journal of Transport Geography, Elsevier, vol. 86(C).
    10. Keigo Shibuya & Ryuichi Shibasaki, 2023. "Modeling Structural Changes in Intra-Asian Maritime Container Shipping Networks Considering Their Characteristics," Sustainability, MDPI, vol. 15(13), pages 1-22, June.
    11. Li, Weijun & Bai, Xiwen & Yang, Dong & Hou, Yao, 2023. "Maritime connectivity, transport infrastructure expansion and economic growth: A global perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).
    12. Nicanor García Álvarez & Belarmino Adenso-Díaz & Laura Calzada-Infante, 2021. "Maritime Traffic as a Complex Network: a Systematic Review," Networks and Spatial Economics, Springer, vol. 21(2), pages 387-417, June.
    13. Dadashpoor, Hashem & Arasteh, Mojtaba, 2020. "Core-port connectivity: Towards shaping a national hinterland in a West Asia country," Transport Policy, Elsevier, vol. 88(C), pages 57-68.
    14. Cheung, Kam-Fung & Bell, Michael G.H. & Pan, Jing-Jing & Perera, Supun, 2020. "An eigenvector centrality analysis of world container shipping network connectivity," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).

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