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城市地下综合管廊PPP 项目风险分担研究
引用本文:邵宇,刘菁.城市地下综合管廊PPP 项目风险分担研究[J].工程管理学报,2020,34(2):117-122.
作者姓名:邵宇  刘菁
作者单位:北京交通大学 经济管理学院
摘    要:制约城市地下综合管廊PPP 项目发展的关键是合理的风险分担问题。项目参与各方之间存在权力不平等、利益诉求差异等因素,使得地下综合管廊PPP 项目中庞杂的风险无法在项目各参与方之间合理分担。依托长春市城区地下综合管廊PPP 项目,针对私营部门各参与方之间的风险分担,引入风险承担能力、风险应对能力、合作机制及风险属性等影响因素,运用熵权-ANP 模型计算风险分担指标主客观组合权重,优化Shapley 值,进而得到风险分担的最优比例。改进后的风险分担机制克服了以往综合管廊PPP 项目风险分担考虑因素不全面、分担方法不科学、承担主体不明确的研究瓶颈,可为地下综合管廊PPP 项目风险分担提供合理的借鉴。

关 键 词:地下综合管廊  PPP  风险分担  熵权-ANP  Shapley  

Research on Risk Allocation of PPP Project inUrban Underground Utility Tunnel
SHAO Yu,LIU Jing.Research on Risk Allocation of PPP Project inUrban Underground Utility Tunnel[J].Journal of Engineering Management,2020,34(2):117-122.
Authors:SHAO Yu  LIU Jing
Affiliation:School of Economics and Management,Beijing Jiaotong University
Abstract:The key to restrict the development of urban underground utility tunnel PPP project is the reasonable risk allocation. Therisks in the underground utility tunnel PPP project cannot be reasonably shared among the parties involved due to the unequal powerand different interest demands among the parties in the project. Based on the project of the underground utility tunnel PPP inChangchun city,for risk allocation among private sector participants,this paper introduces the risk-bearing capacity,risk-copingcapacity,cooperation mechanism and risk attribute. The entropy weight-ANP model is used to calculate the subjective and objectivecombination weights of risk-allocation index,and the Shapley value model is optimized. Finally, the optimal proportion of riskallocation is obtained. The research shows that the improved risk allocation mechanism overcomes the bottlenecks of previousresearch including incomplete risk allocation factors,unscientific allocation method and unclear main body of risk allocation in theunderground utility tunnel PPP project. This research provides reasonable reference for the risk allocation of the underground tunnelPPP project.
Keywords:underground utility tunnel  PPP  risk allocation  entropy weight-ANP  Shapley value
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