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Evaluation of port disruption impacts in the global liner shipping network

Author

Listed:
  • Pablo E. Achurra-Gonzalez

    (Skempton Building, South Kensington Campus, Imperial College London)

  • Panagiotis Angeloudis

    (Skempton Building, South Kensington Campus, Imperial College London)

  • Nils Goldbeck

    (Skempton Building, South Kensington Campus, Imperial College London)

  • Daniel J. Graham

    (Skempton Building, South Kensington Campus, Imperial College London)

  • Konstantinos Zavitsas

    (Skempton Building, South Kensington Campus, Imperial College London)

  • Marc E. J. Stettler

    (Skempton Building, South Kensington Campus, Imperial College London)

Abstract

The global container shipping network is vital to international trade. Current techniques for its vulnerability assessment are constrained due to the lack of historical disruption data and computational limitations due to typical network sizes. We address these modelling challenges by developing a new framework, composed by a game-theoretic attacker-defender model and a cost-based container assignment model that can identify systemic vulnerabilities in the network. Given its focus on logic and structure, the proposed framework has minimal input data requirements and does not rely on the presence of extensive historical disruption data. Numerical implementations are carried in a global-scale liner network where disruptions occur in Europe’s main container ports. Model outputs are used to establish performance baselines for the network and illustrate the differences in regional vulnerability levels and port criticality rankings with different disruption magnitudes and flow diversion strategies. Sensitivity analysis of these outputs identifies network components that are more susceptible to lower levels of disruption which are more common in practice and evaluates the effectiveness of component-level interventions seeking to increase the resilience of the system.

Suggested Citation

  • Pablo E. Achurra-Gonzalez & Panagiotis Angeloudis & Nils Goldbeck & Daniel J. Graham & Konstantinos Zavitsas & Marc E. J. Stettler, 2019. "Evaluation of port disruption impacts in the global liner shipping network," Journal of Shipping and Trade, Springer, vol. 4(1), pages 1-21, December.
    • Handle: RePEc:spr:josatr:v:4:y:2019:i:1:d:10.1186_s41072-019-0043-8
    DOI: 10.1186/s41072-019-0043-8
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    3. Guerrero, David & Letrouit, Lucie & Pais-Montes, Carlos, 2022. "The container transport system during Covid-19: An analysis through the prism of complex networks," Transport Policy, Elsevier, vol. 115(C), pages 113-125.
    4. Ferrari, Claudio & Persico, Luca & Tei, Alessio, 2022. "Covid-19 and seaborne trade: The Italian perspective," Research in Transportation Economics, Elsevier, vol. 93(C).
    5. Daniele Crotti & Claudio Ferrari & Alessio Tei, 2022. "Understanding the impact of demand shocks on the container port industry," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 24(4), pages 778-805, December.
    6. Erick P. Massami & Malima M. Manyasi, 2021. "Analysis of determinants of work performance for seafarers based on fuzzy Electre model," Journal of Shipping and Trade, Springer, vol. 6(1), pages 1-20, December.
    7. Junayed Pasha & Maxim A. Dulebenets & Masoud Kavoosi & Olumide F. Abioye & Oluwatosin Theophilus & Hui Wang & Raphael Kampmann & Weihong Guo, 2020. "Holistic tactical-level planning in liner shipping: an exact optimization approach," Journal of Shipping and Trade, Springer, vol. 5(1), pages 1-35, December.
    8. Olabisi Michael Olapoju, 2023. "Appraising the impact of COVID-19 on trading volume of selected vessel types in sub-Saharan Africa," Journal of Shipping and Trade, Springer, vol. 8(1), pages 1-12, December.
    9. Ducruet, César, 2020. "The geography of maritime networks: A critical review," Journal of Transport Geography, Elsevier, vol. 88(C).
    10. Itoh, Ryo & Zhang, Anming, 2023. "How should ports share risk of natural and climate change disasters? Analytical modelling and implications for adaptation investments," Economics of Transportation, Elsevier, vol. 33(C).

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