Resilience assessment of multimodal container ports under operational disruptions: a global sensitivity analysis

Assessments of port operational resilience are often fragmented in the existing literature and practices, primarily concentrating on local-level risks related to individual components and/or subsystems. These evaluations treat each component and subsystem in a port independently, neglecting the interconnected ripple effects throughout the port from a multimodal perspective. Consequently, improvements targeting individual components may not yield an optimal outcome for the entire port system. Key components, including liner shipping, feeder shipping, railroads, and trucking, constitute the fundamental operational structure of a multimodal container port. As ports evolve to incorporate new technologies, the complexity of their operations increases, emphasising the need for accurate management of port operational resilience. In response, this paper introduces a novel methodology to assess multimodal port resilience by quantifying the impact of various disruptions and identifying the interactions among them that could lead to a ripple effect. In this framework, port operations are first simulated through System Dynamics (SD) modelling. The resulting performance is then transformed into resilience indicators, which are synthesised across subsystems using the Evidential Reasoning (ER) method. Finally, the Sobol Global Sensitivity Analysis (GSA) is employed to assess the influence of individual and joint disruptions. To assess the consistency of the results, the Intraclass Consistency Coefficient (ICC) is calculated for three different GSAs. Using historical failure data and field evidence, multiple disruption scenarios are explored. The outcomes indicate that failures of yard and quay cranes have the greatest impact on port resilience. It is further observed that many disruptions arise from interdependent failures rather than individual malfunctions, leading to amplified ripple effects. The results provide a data-driven foundation for policymakers and port managers to shift from experience-based to evidence-based allocation of emergency resources, with evidence generated through large-scale simulations of plausible but previously unobserved disruption scenarios. They also support cross-agency coordination for integrated resilience management against compound disruptions arising from ripple effects. In summary, this framework, for the first time, offers crucial insights for bolstering long-term resilience in multimodal container port operations from a systematic overall perspective.

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Publication Details

Journal
Transportation Research Part A Policy and Practice
Published
2026-03-28
DOI
https://doi.org/10.1016/j.tra.2026.104987
Primary Topic
Infrastructure Resilience and Vulnerability Analysis
Type
article
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article

Resilience assessment of multimodal container ports under operational disruptions: a global sensitivity analysis

Xiaoning Shi, Trung Thành Nguyễn, Rameshwar Dubey, JF Zhang et al.
Transportation Research Part A Policy and Practice
Infrastructure Resilience and Vulnerability Analysis
article

Resilience assessment of multimodal container ports under operational disruptions: a global sensitivity analysis

Xiaoning Shi, Trung Thành Nguyễn, Rameshwar Dubey, JF Zhang, Xuri Xin, Na Li, Zaili Yang
article en

Abstract

Assessments of port operational resilience are often fragmented in the existing literature and practices, primarily concentrating on local-level risks related to individual components and/or subsystems. These evaluations treat each component and subsystem in a port independently, neglecting the interconnected ripple effects throughout the port from a multimodal perspective. Consequently, improvements targeting individual components may not yield an optimal outcome for the entire port system. Key components, including liner shipping, feeder shipping, railroads, and trucking, constitute the fundamental operational structure of a multimodal container port. As ports evolve to incorporate new technologies, the complexity of their operations increases, emphasising the need for accurate management of port operational resilience. In response, this paper introduces a novel methodology to assess multimodal port resilience by quantifying the impact of various disruptions and identifying the interactions among them that could lead to a ripple effect. In this framework, port operations are first simulated through System Dynamics (SD) modelling. The resulting performance is then transformed into resilience indicators, which are synthesised across subsystems using the Evidential Reasoning (ER) method. Finally, the Sobol Global Sensitivity Analysis (GSA) is employed to assess the influence of individual and joint disruptions. To assess the consistency of the results, the Intraclass Consistency Coefficient (ICC) is calculated for three different GSAs. Using historical failure data and field evidence, multiple disruption scenarios are explored. The outcomes indicate that failures of yard and quay cranes have the greatest impact on port resilience. It is further observed that many disruptions arise from interdependent failures rather than individual malfunctions, leading to amplified ripple effects. The results provide a data-driven foundation for policymakers and port managers to shift from experience-based to evidence-based allocation of emergency resources, with evidence generated through large-scale simulations of plausible but previously unobserved disruption scenarios. They also support cross-agency coordination for integrated resilience management against compound disruptions arising from ripple effects. In summary, this framework, for the first time, offers crucial insights for bolstering long-term resilience in multimodal container port operations from a systematic overall perspective.

Transportation Research Part A Policy and PracticeVol. 208
Wuhan University of Technology (CN), Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE), Montpellier Business School (FR), Dalian Maritime University (CN), Liverpool John Moores University (GB)
Openalex Percentile: Top 5%
Infrastructure Resilience and Vulnerability Analysis
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