Public-private partnership (PPP) projects remain one of the key initiatives of the Chinese government. The key characteristics of the PPP projects include the long construction period and large investment amount, while constant monitoring is required to determine the risks of the projects within a comprehensive environmental management framework. Over the years, the government has used the PPP model to implement various projects, capitalizing on a few methods to assess the riskiness of the entire life cycle of the comprehensive environmental PPP projects. However, we argue that the principal component analysis (PCA) can be used to determine the various factors that may have a high influence on the risk potential of PPP projects. In fact, it plays an important role in ensuring the smooth implementation of projects while reducing the losses caused by various risks. According to the risk factors of the whole life cycle of the comprehensive environmental governance PPP project, an indicator system of five first-level indicators, 18 second-level indicators, and 43 third-level indicators has been established. Principal component analysis is used to analyze the influence and weight of risk factors at each stage. The analysis shows that among the four stages, environmental pollution risk, project approval delay risk, completion risk, interest rate and financial fluctuation risk, and franchise life risk are the most influential risks in the implementation of PPP projects. Therefore, suggestions are made based on the risk factors at each stage of the comprehensive environmental management PPP project. Building on this, we argue that the ability to resist any PPP projects with higher risk can be improved, thus ensuring a smooth implementation of the project while promoting the long-term development of comprehensive environmental management PPP projects in the future.
CITATION STYLE
Hu, Q., & Entebang, H. (2023). Life Cycle Risk Assessment of Public-Private Partnership Project of Comprehensive Environmental Management Based on Principal Component Analysis. Future Cities and Environment, 9(1). https://doi.org/10.5334/fce.178
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