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An eigenvector centrality analysis of world container shipping network connectivity

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  • Cheung, Kam-Fung
  • Bell, Michael G.H.
  • Pan, Jing-Jing
  • Perera, Supun

Abstract

Container shipping accounts for most of the world merchandise trade. Better maritime connectivity leads to lower freight rates and greater economic growth. This paper presents a novel max–min integer optimization model to facilitate better shipping network connectivity by analysing the largest eigenvalue and its corresponding eigenvector of the (asymmetric) frequency weighted adjacency matrix. An algorithm is presented that can quickly identify which link not currently in the container shipping network would best improve its connectivity. A demand matrix is not required by this method of analysis and network symmetry is not assumed. The method could strengthen direct connection between port pairs.

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  • 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).
    • Handle: RePEc:eee:transe:v:140:y:2020:i:c:s1366554520306426
    DOI: 10.1016/j.tre.2020.101991
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    References listed on IDEAS

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    13. 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).

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