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Behavioral Decision-Making of Key Stakeholders in Public-Private Partnerships: A Hybrid Method and Benefit Distribution Study

Guoshuai Sun1,2,3, Wanyi Zhang1, Jiuying Dong4,*, Shuping Wan2, Jiao Feng5

1 School of Economics and Management, Liaoning University of Technology, Jinzhou, 121001, China
2 School of Information Management, Jiangxi University of Finance and Economics, Nanchang, 330032, China
3 Post-Doctoral Research Center, Zhongda Construction Co., Ltd., Guangzhou, 510280, China
4 School of Science, Shanghai Institute of Technology, Shanghai, 201418, China
5 School of Maritime Economics and Management, Dalian Maritime University, Dalian, 116026, China

* Corresponding Author: Jiuying Dong. Email:

(This article belongs to this Special Issue: Decision making Modeling, Methods and Applications of Advanced Fuzzy Theory in Engineering and Science)

Computer Modeling in Engineering & Sciences 2023, 136(3), 2895-2934.


Public-private partnerships (PPPs) have been used by governments around the world to procure and construct infrastructural amenities. It relies on private sector expertise and funding to achieve this lofty objective. However, given the uncertainties of project management, transparency, accountability, and expropriation, this phenomenon has gained tremendous attention in recent years due to the important role it plays in curbing infrastructural deficits globally. Interestingly, the reasonable benefit distribution scheme in a PPP project is related to the behavior decision-making of the government and social capital, as well as the performance of the project. In this paper, the government and social capital which are the key stakeholders of PPP projects were selected as the research objects. Based on the fuzzy expected value model and game theory, a hybrid method was adopted in this research taking into account the different risk preferences of both public entities and private parties under the fuzzy demand environment. To alleviate the problem of insufficient utilization of social capital in a PPP project, this paper seeks to grasp the relationship that exists between the benefit distribution of stakeholders, their behavioral decision-making, and project performance, given that they impact the performance of both public entities and private parties, as well as assist in maximizing the overall utility of the project. Furthermore, four game models were constructed in this study, while the expected value and opportunity-constrained programming model for optimal decision-making were derived using alternate perspectives of both centralized decision-making and decentralized decision-making. Afterward, the optimal behavioral decision-making of public entities and private parties in four scenarios was discussed and thereafter compared, which led to an ensuing discussion on the benefit distribution system under centralized decision-making. Lastly, based on an example case, the influence of different confidence levels, price, and fuzzy uncertainties of PPP projects on the equilibrium strategy results of both parties were discussed, giving credence to the effectiveness of the hybrid method. The results indicate that adjusting different confidence levels yields different equilibrium points, and therefore signposts that social capital has a fair perception of opportunities, as well as identifies reciprocal preferences. Nevertheless, we find that an increase in the cost coefficient of the government and social capital does not inhibit the effort of both parties. Our results also indicate that a reasonable benefit distribution of PPP projects can assist them in realizing optimum Pareto improvements over time. The results provide us with very useful strategies and recommendations to improve the overall performance of PPP projects in China.


Cite This Article

Sun, G., Zhang, W., Dong, J., Wan, S., Feng, J. (2023). Behavioral Decision-Making of Key Stakeholders in Public-Private Partnerships: A Hybrid Method and Benefit Distribution Study. CMES-Computer Modeling in Engineering & Sciences, 136(3), 2895–2934.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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