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Identification of the Key Influencing Factors of Urban Rail Transit Station Resilience against Disasters Caused by Rainstorms

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  • Liudan Jiao

    (School of Economics and Management, Chongqing Jiaotong University, Chongqing 400074, China)

  • Dongrong Li

    (School of Economics and Management, Chongqing Jiaotong University, Chongqing 400074, China)

  • Yu Zhang

    (School of Economics and Management, Chongqing Jiaotong University, Chongqing 400074, China)

  • Yinghan Zhu

    (School of Economics and Management, Chongqing Jiaotong University, Chongqing 400074, China)

  • Xiaosen Huo

    (School of Economics and Management, Chongqing Jiaotong University, Chongqing 400074, China)

  • Ya Wu

    (College of Resources and Environment, Southwest University, Chongqing 400715, China)

Abstract

Improving the ability of the urban rail transit system to cope with rainstorm disasters is of great significance to ensure the safe travel of residents. In this study, a model of the hierarchical relationship of the influencing factors is constructed from the resilience perspective, in order to research the action mechanisms of the influencing factors of urban rail transit stations susceptible to rainstorm disaster. Firstly, the concept of resilience and the three attributes (resistance, recovery, and adaptability) are interpreted. Based on the relevant literature, 20 influencing factors are discerned from the 3 attributes of the resilience of urban rail transit stations. Subsequently, an interpretative structural model (ISM) is utilised to analyse the hierarchical relationship among the influencing factors. The key influencing factors of station resilience are screened out using social network analysis (SNA). Combined with ISM and SNA for analysis, the result shows that the key influencing factors are: “Flood prevention monitoring capability”; “Water blocking capacity”; “Flood prevention capital investment”; “Personnel cooperation ability”; “Emergency plan for flood prevention”; “Flood prevention training and drill”; “Publicity and education of flood prevention knowledge”; and “Regional economic development level”. Therefore, according to the critical influencing factors and the action path of the resilience influencing factors, station managers can carry out corresponding flood control work, providing a reference for enhancing the resilience of urban rail transit stations.

Suggested Citation

  • Liudan Jiao & Dongrong Li & Yu Zhang & Yinghan Zhu & Xiaosen Huo & Ya Wu, 2021. "Identification of the Key Influencing Factors of Urban Rail Transit Station Resilience against Disasters Caused by Rainstorms," Land, MDPI, vol. 10(12), pages 1-21, November.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:12:p:1298-:d:688212
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    Cited by:

    1. Hu, Jie & Wen, Weiping & Zhai, Changhai & Pei, Shunshun, 2024. "Post-earthquake functionality assessment for urban subway systems: Incorporating the combined effects of seismic performance of structural and non-structural systems and functional interdependencies," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    2. Liudan Jiao & Fenglian Luo & Fengyan Wu & Yu Zhang & Xiaosen Huo & Ya Wu, 2022. "Exploring the Interactive Coercing Relationship between Urban Rail Transit and the Ecological Environment," Land, MDPI, vol. 11(6), pages 1-20, June.
    3. Nao Sugiki & Shogo Nagao & Fumitaka Kurauchi & Mustafa Mutahari & Kojiro Matsuo, 2021. "Social Dynamics Simulation Using a Multi-Layer Network," Sustainability, MDPI, vol. 13(24), pages 1-22, December.
    4. Hui Xu & Shuxiu Li & Yongtao Tan & Bin Xing, 2022. "Comprehensive Resilience Assessment of Complex Urban Public Spaces: A Perspective of Promoting Sustainability," Land, MDPI, vol. 11(6), pages 1-23, June.
    5. Chenlei Guan & Damin Dong & Feng Shen & Xin Gao & Linyan Chen, 2022. "Hierarchical Structure Model of Safety Risk Factors in New Coastal Towns: A Systematic Analysis Using the DEMATEL-ISM-SNA Method," IJERPH, MDPI, vol. 19(17), pages 1-17, August.

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