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The Social Risk of High-Speed Rail Projects in China: A Bayesian Network Analysis

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  • 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)

Abstract

In China, high-speed rail projects have brought huge social and economic benefits to the affected regions after they are completed. However, the potential externalities of such projects cause competition for the station during the project planning phase, thus triggering social risks. This paper studies the mechanisms responsible for generating the social risk associated with such high-speed rail projects. Employing typical case studies, a social risk list for a given project is established. Based on the risk list, a Bayesian network model is developed and verified through case studies, expert interviews, and expert grading. Using the model’s functions of reverse inference and sensitivity analysis, the key risk factors, sensitive risk factors, and maximum causal chain are identified. Countermeasures are then proposed to mitigate the social risk, such as increasing the transparency of and democratizing the planning process for high-speed rail projects, improving the mechanism by which local governments can express interest in such projects, and enhancing emergency management mechanisms. The findings provide points of reference for social risk management when it comes to planning high-speed rail projects and, more generally, offer significant guidance for socially sustainable decision-making processes for mega projects with massive externalities.

Suggested Citation

  • Yutong Xue & Pengcheng Xiang, 2020. "The Social Risk of High-Speed Rail Projects in China: A Bayesian Network Analysis," Sustainability, MDPI, vol. 12(5), pages 1-23, March.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:5:p:2087-:d:330030
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    References listed on IDEAS

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