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Risk Assessment of High-Speed Rail Projects: A Risk Coupling Model Based on System Dynamics

Author

Listed:
  • Yutong Xue

    (School of Management Science & Real Estate, Chongqing University, Chongqing 400045, China)

  • Pengcheng Xiang

    (School of Management Science & Real Estate, Chongqing University, Chongqing 400045, China
    International Research Center for Sustainable Built Environment, Chongqing University, Chongqing 400045, China
    Construction Economics and Management Research Center, Chongqing University, Chongqing 400045, China)

  • Fuyuan Jia

    (School of Management Science & Real Estate, Chongqing University, Chongqing 400045, China)

  • Zhaowen Liu

    (Faculty of Civil Engineering and Geosciences, Delft University of Technology, 2628CN Delft, The Netherlands)

Abstract

Due to their characteristics and multiple objectives, high-speed rail (HSR) projects carry more complex risks than conventional projects and high correlation and conductivity are among the associated risk factors. Previous risk assessment frameworks for rail infrastructure have ignored the effects of risk interactions that inflate risk levels, namely, risk coupling effects. Based on a system dynamics method, this paper develops a risk coupling model for HSR project risk assessments. A risk factor list is established from a literature review, and relationships analysed using a case study and expert interviews. System dynamics equations are constructed and their parameters obtained by expert evaluations of risk factors. The proposed model is applied to a real-world HSR project to demonstrate it in detail. The model can evaluate the risk levels of HSR projects during a simulation period. In particular, it can identify the key coupling effects that are the main increased risk. It provides a significant resource, using which HSR project managers can identify and mitigate risks.

Suggested Citation

  • Yutong Xue & Pengcheng Xiang & Fuyuan Jia & Zhaowen Liu, 2020. "Risk Assessment of High-Speed Rail Projects: A Risk Coupling Model Based on System Dynamics," IJERPH, MDPI, vol. 17(15), pages 1-27, July.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:15:p:5307-:d:388690
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    References listed on IDEAS

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    Cited by:

    1. Xue, Gang & Liu, Shifeng & Ren, Long & Gong, Daqing, 2024. "Risk assessment of utility tunnels through risk interaction-based deep learning," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    2. Xiaoxiao Geng & Yongwei Lv & Li Zhao & Yingchen Wang, 2023. "Measurement and Simulation of Risk Coupling in Port Hazardous Chemical Logistics," IJERPH, MDPI, vol. 20(5), pages 1-27, February.
    3. Bugalia, Nikhil & Maemura, Yu & Dasari, Rohit & Patidar, Manoj, 2023. "A system dynamics model for effective management strategies of High-Speed Railway (HSR) projects involving private sector participation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).

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