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Modular gateway-ness connectivity and structural core organization in maritime network science

Author

Listed:
  • Mengqiao Xu

    (Dalian University of Technology)

  • Qian Pan

    (Dalian University of Technology)

  • Alessandro Muscoloni

    (Biomedical Cybernetics Group, Biotechnology Center (BIOTEC), Center for Molecular and Cellular Bioengineering (CMCB), Center for Systems Biology Dresden (CSBD), Cluster of Excellence Physics of Life (PoL), Department of Physics, Technische Universität Dresden. Tatzberg 47/49)

  • Haoxiang Xia

    (Dalian University of Technology)

  • Carlo Vittorio Cannistraci

    (Biomedical Cybernetics Group, Biotechnology Center (BIOTEC), Center for Molecular and Cellular Bioengineering (CMCB), Center for Systems Biology Dresden (CSBD), Cluster of Excellence Physics of Life (PoL), Department of Physics, Technische Universität Dresden. Tatzberg 47/49
    Tsinghua University. 160 Chengfu Rd., SanCaiTang Building, Haidian District)

Abstract

Around 80% of global trade by volume is transported by sea, and thus the maritime transportation system is fundamental to the world economy. To better exploit new international shipping routes, we need to understand the current ones and their complex systems association with international trade. We investigate the structure of the global liner shipping network (GLSN), finding it is an economic small-world network with a trade-off between high transportation efficiency and low wiring cost. To enhance understanding of this trade-off, we examine the modular segregation of the GLSN; we study provincial-, connector-hub ports and propose the definition of gateway-hub ports, using three respective structural measures. The gateway-hub structural-core organization seems a salient property of the GLSN, which proves importantly associated to network integration and function in realizing the cargo transportation of international trade. This finding offers new insights into the GLSN’s structural organization complexity and its relevance to international trade.

Suggested Citation

  • Mengqiao Xu & Qian Pan & Alessandro Muscoloni & Haoxiang Xia & Carlo Vittorio Cannistraci, 2020. "Modular gateway-ness connectivity and structural core organization in maritime network science," Nature Communications, Nature, vol. 11(1), pages 1-15, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-16619-5
    DOI: 10.1038/s41467-020-16619-5
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    Cited by:

    1. Jasper Verschuur & Raghav Pant & Elco Koks & Jim Hall, 2022. "A systemic risk framework to improve the resilience of port and supply-chain networks to natural hazards," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 24(3), pages 489-506, September.
    2. Naima Saeed & Kevin Cullinane & Victor Gekara & Prem Chhetri, 2021. "Reconfiguring maritime networks due to the Belt and Road Initiative: impact on bilateral trade flows," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(3), pages 381-400, September.
    3. Wen, Tao & Gao, Qiuya & Chen, Yu-wang & Cheong, Kang Hao, 2022. "Exploring the vulnerability of transportation networks by entropy: A case study of Asia–Europe maritime transportation network," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    4. Yap, Wei Yim & Hsieh, Cheng-Hsien & Lee, Paul Tae-Woo, 2023. "Shipping connectivity data analytics: Implications for maritime policy," Transport Policy, Elsevier, vol. 132(C), pages 112-127.
    5. Peng, Wenhao & Bai, Xiwen, 2022. "Prospects for improving shipping companies’ profit margins by quantifying operational strategies and market focus approach through AIS data," Transport Policy, Elsevier, vol. 128(C), pages 138-152.
    6. Ge, Jiawei & fu, Qiang & Zhang, Qiang & Wan, Zheng, 2022. "Regional operating patterns of world container shipping network: A perspective from motif identification," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    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. Wei, Na & Xie, Wen-Jie & Zhou, Wei-Xing, 2022. "Robustness of the international oil trade network under targeted attacks to economies," Energy, Elsevier, vol. 251(C).
    9. Jin, Lianjie & Chen, Jing & Chen, Zilin & Sun, Xiangjun & Yu, Bin, 2022. "Impact of COVID-19 on China's international liner shipping network based on AIS data," Transport Policy, Elsevier, vol. 121(C), pages 90-99.
    10. Feng, Xiao & He, Shiwei & Li, Guangye & Chi, Jushang, 2021. "Transfer network of high-speed rail and aviation: Structure and critical components," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    11. Sugimura, Yoshihisa & Akakura, Yasuhiro & Yotsushima, Tatsuki & Kawasaki, Tomoya, 2023. "Evaluation of Japanese port policies through network analysis," Transport Policy, Elsevier, vol. 135(C), pages 59-70.
    12. Zhang, Yin-Ting & Zhou, Wei-Xing, 2023. "Quantifying the status of economies in international crop trade networks: A correlation structure analysis of various node-ranking metrics," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    13. J. Verschuur & E. E. Koks & J. W. Hall, 2022. "Ports’ criticality in international trade and global supply-chains," Nature Communications, Nature, vol. 13(1), pages 1-13, December.

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