Study on Identification of Spurious Public–Private Partnership Projects in China
Qingxue Liang, Hao Hu
Abstract
Qingxue Liang, Hao Hu
Abstract
Public-private partnership (PPP) is effective in delivering infrastructure projects. In China, PPP has been widely adopted in project finance ever since the government has permitted the private sector to get involved in the investment and operation of urban infrastructure. However, there seem to be many spurious PPP projects emerging in the market, which may bring about losses to the stakeholders and lead PPP away from orderly and standardized development. This paper attempts to address this issue by applying the fuzzy analytic hierarchy process to investigate two infrastructure PPP projects, and analyze the characteristics of genuine and spurious PPP projects in China. Recommendations for mass implementation of PPP and ways of identifying spurious PPP projects are summarized to guide the regulation of infrastructure PPP projects. The paper also provides a reference for project selection and policy-making in the future.
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Public-private partnership (PPP) is effective in delivering infrastructure projects. In China, PPP has been widely adopted in project finance ever since the government has permitted the private sector to get involved in the investment and operation of urban infrastructure. However, there seem to be many spurious PPP projects emerging in the market, which may bring about losses to the stakeholders and lead PPP away from orderly and standardized development. This paper attempts to address this issue by applying the fuzzy analytic hierarchy process to investigate two infrastructure PPP projects, and analyze the characteristics of genuine and spurious PPP projects in China. Recommendations for mass implementation of PPP and ways of identifying spurious PPP projects are summarized to guide the regulation of infrastructure PPP projects. The paper also provides a reference for project selection and policy-making in the future.
Key concepts: Public–private partnership, China, Business, Government (linguistics), General partnership, Identification (biology), Private sector, Critical infrastructure