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Hub-and-spoke structure: Characterizing the global crude oil transport network with mass vessel trajectories

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  • Peng, Peng
  • Yang, Yu
  • Cheng, Shifen
  • Lu, Feng
  • Yuan, Zimu

Abstract

Global crude oil trade is a direct reflection of global economic development and can be mathematically modeled as a network with mass trajectories of crude oil vessels between ports, as well as loading and unloading volume at ports. In this study, we build the global transport networks of crude oil between ports by using automatic identification system (AIS) data of crude oil vessels from 2009 to 2016 and design an assessment framework based on complex network indices—including centrality indexes, clustering and assortativity coefficient, and k-core decomposition—to evaluate the spatial-temporal characteristics of port-port crude oil transport networks. Compared with the original results obtained from statistical data of different countries, the port-port networks of global crude oil transport built with the AIS trajectories present a more complicated “hub-and-spoke” structure with an increasing number of hub ports and routes passing through the hub ports over time. The identified backbone networks have a significant impact on the entire crude oil transport network and have been strengthened over time. Moreover, Rotterdam, Singapore, and Antwerp ports remain the top three hub ports over time, they are also been identified the significant control capacities over the whole network.

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  • Peng, Peng & Yang, Yu & Cheng, Shifen & Lu, Feng & Yuan, Zimu, 2019. "Hub-and-spoke structure: Characterizing the global crude oil transport network with mass vessel trajectories," Energy, Elsevier, vol. 168(C), pages 966-974.
    • Handle: RePEc:eee:energy:v:168:y:2019:i:c:p:966-974
    DOI: 10.1016/j.energy.2018.11.049
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    7. Cai, Wenxue & Liang, Fenfen & Wan, Yanchun & Zhong, Huiling & Gu, Yimiao, 2021. "An innovative approach for constructing a shipping index based on dynamic weighted complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 578(C).
    8. Wu, Gang & Pu, Yue & Shu, Tianran, 2021. "Features and evolution of global energy trade network based on domestic value-added decomposition of export," Energy, Elsevier, vol. 228(C).
    9. Yan Yang & Qiang Zhou, 2023. "Modeling and Simulation of Crude Oil Sea–River Transshipment System in China’s Yangtze River Basin," Energies, MDPI, vol. 16(6), pages 1-16, March.
    10. Zhicheng Shen & Xinliang Xu & Jiahao Li & Shikuan Wang, 2019. "Vulnerability of the Maritime Network to Tropical Cyclones in the Northwest Pacific and the Northern Indian Ocean," Sustainability, MDPI, vol. 11(21), pages 1-14, November.
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