Vulnerability Threshold Identification in Maritime Silk Road Networks: Socio-Spatial Clustering Enhanced Resilience Assessment Model

The resilience and vulnerability of the Maritime Silk Road transportation network (MSRTN) have become critical issues in the face of external disruptions and emergencies. To address these challenges, this study develops a comprehensive evaluation framework grounded in complex network theory, aiming to systematically investigate the structural and functional attributes of the MSRTN. Initially, by integrating socio-geographical data, an optimized clustering algorithm is employed to measure the connectivity strength among ports across diverse regions, forming a robust socio-spatial network. Then, the fuzzy comprehensive evaluation method is applied to evaluate the competitive potential of individual ports. Subsequently, a gravity model is utilized to simulate the interactions and flow dynamics within the MSRTN. Finally, advanced complex network analysis techniques are implemented to uncover the network’s topological properties and resilience patterns. The results in the defined scenario application demonstrate that the MSRTN exhibits high accessibility and distinct small-world characteristics. In addition, the network displays significant resilience when exposed to external risks, only transitioning to a vulnerable state under sustained pressure, validating the robustness of the proposed model. This study provides critical insights into the operational dynamics of the MSRTN and offers strategic recommendations for fostering sustainable growth and resilience in ports along the Maritime Silk Road.

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Publication Details

Journal
Transportation Research Record Journal of the Transportation Research Board
Published
2025-12-27
DOI
https://doi.org/10.1177/03611981251398750
Primary Topic
Infrastructure Resilience and Vulnerability Analysis
Type
article
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article

Vulnerability Threshold Identification in Maritime Silk Road Networks: Socio-Spatial Clustering Enhanced Resilience Assessment Model

Shenping Hu, Jianjun Wu, Xiaoming Zhu, Weifeng Zhang et al.
Transportation Research Record Journal of the Transportation Research Board
Infrastructure Resilience and Vulnerability Analysis
article

Vulnerability Threshold Identification in Maritime Silk Road Networks: Socio-Spatial Clustering Enhanced Resilience Assessment Model

Shenping Hu, Jianjun Wu, Xiaoming Zhu, Weifeng Zhang, Zhuang Li
article en

Abstract

The resilience and vulnerability of the Maritime Silk Road transportation network (MSRTN) have become critical issues in the face of external disruptions and emergencies. To address these challenges, this study develops a comprehensive evaluation framework grounded in complex network theory, aiming to systematically investigate the structural and functional attributes of the MSRTN. Initially, by integrating socio-geographical data, an optimized clustering algorithm is employed to measure the connectivity strength among ports across diverse regions, forming a robust socio-spatial network. Then, the fuzzy comprehensive evaluation method is applied to evaluate the competitive potential of individual ports. Subsequently, a gravity model is utilized to simulate the interactions and flow dynamics within the MSRTN. Finally, advanced complex network analysis techniques are implemented to uncover the network’s topological properties and resilience patterns. The results in the defined scenario application demonstrate that the MSRTN exhibits high accessibility and distinct small-world characteristics. In addition, the network displays significant resilience when exposed to external risks, only transitioning to a vulnerable state under sustained pressure, validating the robustness of the proposed model. This study provides critical insights into the operational dynamics of the MSRTN and offers strategic recommendations for fostering sustainable growth and resilience in ports along the Maritime Silk Road.

Transportation Research Record Journal of the Transportation Research Board
Shanghai Chengtou (China) (CN), Guangdong Ocean University (CN), Shanghai Maritime University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 36%
Infrastructure Resilience and Vulnerability Analysis
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