Uncovering the multiplex network of global container shipping: Insights from shipping companies

被引:0
|
作者
Xu, Yang [1 ,2 ]
Peng, Peng [1 ,2 ]
Lu, Feng [1 ,2 ,4 ,5 ]
Claramunt, Christophe [1 ,3 ]
机构
[1] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[3] Naval Acad Res Inst, F-29240 Lanveoc, France
[4] Fuzhou Univ, Acad Digital China, Fuzhou 350002, Peoples R China
[5] Jiangsu Ctr Collaborat Innovat Geog Informat Resou, Nanjing 210023, Peoples R China
关键词
Global container shipping; Multiplex network; Shipping company; Vessel trajectory data; FLOWS; VULNERABILITY; CONNECTIVITY; PERSPECTIVE; CENTRALITY; COVERAGE; IMPACT; PORTS;
D O I
10.1016/j.jtrangeo.2024.103991
中图分类号
F [经济];
学科分类号
02 ;
摘要
Shipping companies are key drivers of maritime trade and crucial in the development of container shipping networks. Each company's strategy shapes differences in port services and shipping routes, creating a complex and interconnected global container shipping network that is difficult to analyze using single-layer or aggregated models. This paper introduces a novel multiplex network modeling approach that leverages a very large set of AIS data and applies a series of structural indices to reveal the unique characteristics and multiple key roles of various shipping company networks. By applying methods such as overlap ratio analysis, HITS analysis, and community detection, the study identifies differences in overlap between ports and routes, hub and authority properties of individual ports, as well as local and regional patterns within the global network. Furthermore, it examines structural differences between the multiplex network, the aggregated network, and individual layers, highlighting the importance of multiplex container networks in understanding ports' roles on both regional and global scales. The findings clarify how different shipping companies shape shipping network patterns, enhance the multiplex network's functional roles, and provide a better understanding of the complex structure of the Global Container Shipping Network (GCSN). Finally, it provides authorities with valuable insights on how to better understand maritime shipping networks.
引用
收藏
页数:13
相关论文
共 50 条
  • [1] Urban gravity in the global container shipping network
    Ducruet, Cesar
    Itoh, Hidekazu
    Berli, Justin
    [J]. JOURNAL OF TRANSPORT GEOGRAPHY, 2020, 85
  • [2] Assessing the impact of Arctic shipping routes on the global container shipping network's connectivity
    Poo, Mark Ching-Pong
    Yang, Zaili
    Lau, Yui-yip
    Jarumaneeroj, Pisit
    [J]. POLAR GEOGRAPHY, 2024, 47 (03) : 219 - 239
  • [3] Determinants of cargo and eco-efficiencies of global container shipping companies
    Kuo, Kuo-Cheng
    Lu, Wen-Min
    Kweh, Qian Long
    Le, Minh-Hieu
    [J]. INTERNATIONAL JOURNAL OF LOGISTICS MANAGEMENT, 2020, 31 (04) : 753 - 775
  • [4] Levels of internationalization in the container shipping industry: an assessment of the port networks of the large container shipping companies
    Gadhia, Hitesh K.
    Kotzab, Herbert
    Prockl, Guenter
    [J]. JOURNAL OF TRANSPORT GEOGRAPHY, 2011, 19 (06) : 1431 - 1442
  • [5] Measuring the effect of distance on the network topology of the Global Container Shipping Network
    Dimitrios Tsiotas
    César Ducruet
    [J]. Scientific Reports, 11
  • [6] Measuring the effect of distance on the network topology of the Global Container Shipping Network
    Tsiotas, Dimitrios
    Ducruet, Cesar
    [J]. SCIENTIFIC REPORTS, 2021, 11 (01)
  • [7] The vulnerability of the global container shipping network to targeted link disruption
    Viljoen, Nadia M.
    Joubert, Johan W.
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2016, 462 : 396 - 409
  • [8] An Analysis of Container Transportation Multiplex Networks from the Perspective of Shipping Company
    Xu, Yang
    Peng, Peng
    Claramunt, Christophe
    Lu, Feng
    [J]. WEB AND WIRELESS GEOGRAPHICAL INFORMATION SYSTEMS, W2GIS 2024, 2024, 14673 : 183 - 191
  • [9] A Bayesian network model for container shipping companies' organisational sustainability risk management
    Zhou, Yusheng
    Yuen, Kum Fai
    [J]. TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, 2024, 126
  • [10] Peripherality in the global container shipping network: the case of the Southern African container port system
    Fraser, Darren Ronald
    Notteboom, Theo
    Ducruet, Cesar
    [J]. GEOJOURNAL, 2016, 81 (01) : 139 - 151