The “trillion-dollar era” of megaprojects has increased the demand for the scope of mega infrastructure. To address the requirement for high-quality “investment, construction, and operation” integration, the EPC and PPP models must be combined. The complexity of megaprojects has resulted in the complexity of project risk variables under the new model. However, few existing studies have undertaken in-depth studies on the risk of EPC + PPP megaprojects. The interplay and dynamic evolution of risk factors, in particular, have not been taken into account. This research intends to fill this gap by systematically identifying and modeling the risk variables associated with the adoption of the EPC + PPP model for mega infrastructure projects. In this study, the Bayesian network is used to detect decision-making risk variables for large infrastructure projects in China. The findings indicate that (i) 22 influencing factors of megaproject decision making are identified, including organizational decision making, PPP investment and financing, EPC construction, operations management, and policy and law. (ii) Considering the real project decision-making process, a model based on a dynamic Bayesian network is built, and associated governance techniques and early warning protection mechanisms are designed for the decision-making process. (iii) Using the Yiwu Mall Avenue project as an example, the Bayesian simulation model of decision-making risks is applied to a typical case to validate its feasibility and correctness. These findings have significant theoretical and practical implications for research on the identification and governance of decision-making risks in megaprojects using the EPC + PPP model in China.

Existing research on risk sharing management often ignores the adverse consequences of secondary risks. This study addresses secondary risks that emerge from the implementation of specific risk mitigation measures. Addressing the limitations of existing research that overlooks secondary risks and exploring the impact of secondary risks on the outcome of risk sharing, this paper integrates secondary risks into a game model that examines risk sharing between the public and private sectors in EPC+PPP projects. Utilizing a risk-control benefit model, an evolutionary game model is established to determine the evolutionary stability strategy under various conditions. This encompasses factors such as project income distribution, risk control capability, imbalanced status, and risk compensation. The findings indicate that secondary risks impact the risk-sharing strategies of both parties. Furthermore, a stronger risk-control ability correlates with a greater inclination toward risk-taking. The public sector can motivate risk sharing for the private sector through risk compensation, with a discernible lower limit. Ultimately, risk sharing becomes an active choice for both public and private entities when the risk cost is below the difference in returns between risks.