An empirical study on the key success factors of ppp-based PCA in the big data environment -- a case study of China

Abstract

Public-private partnerships (PPPS) are increasingly being used in the construction of public services such as infrastructure in China. In the process of PPP project implementation, there are successes and failures, and the key factors of success are not completely clear. In order to identify the key factors for the success of PPP projects in the big data environment, PCA analysis is used to solve the problem of how to identify the key factors for the success of PPP projects in the big data environment. By studying the big data of PPP project and relevant literature at home and abroad, 32 potential key factors for success were constructed. The key success factors of PPP project were analyzed by questionnaire survey and principal component analysis. The results show that the 32 key factors for success can be summarized into five categories: political and economic environment, project development and operation management, government support and participation, government credit and commitment, strength of stakeholders, and factors of project bidding and procurement. Among the five factors, the key factors for the success of PPP projects are the continuous optimization of PPP policies, the rational project risk sharing mechanism, the guarantee and commitment of the government, the integrity and stability of government personnel, the satisfaction of public interests, and the complete financial analysis. This PCA method effectively solves the key factors for the success of PPP projects in the big data environment, ensures the smooth implementation of PPP projects, and promotes the long-term development of PPP projects.