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Under China’s modern development concept, it is necessary to promote the application of electric equipment to improve the construction environment of high-altitude railway tunnels and to address the efficiency reduction in high-altitude construction of traditional fuel oil equipment. Based on the analysis of the development status of electric equipment for tunneling projects in China, a tripartite evolutionary game approach is used to establish the game payment matrix of the government, equipment manufacturers, and construction units. The impact of the relevant parameters on the tripartite strategy is investigated based on numerical simulations. It has been shown that in the early stages of popularization and application, the government should actively regulate and control, and in the later stages of popularization and application, the government should play a leading role in market mechanisms. Evolutionary stability strategies are affected by the brand revenue that manufacturers earn through technological innovation on electric equipment and the additional research and development costs that need to be paid. The conclusions of this study can help provide a reference for the promotion and application strategy of electric equipment in China’s plateau railway tunnels.

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The construction of mega infrastructure projects has the characteristics of repeatability, long duration, and high complexity. Therefore, it is particularly important to implement dynamic decision-making in projects. This study takes data-driven decision-making mechanisms as the entry point and constructs a dynamic decision-making system for mega infrastructure projects consisting of an information collection subsystem, an information processing and transformation subsystem, a human–computer collaborative decision-making subsystem and an evaluation and feedback subsystem. On this basis, we established a system dynamics model of dynamic decision-making for mega infrastructure projects. Vensim PLE 9.3.5 software was used to simulate and analyze the operation law of dynamic decision-making for mega infrastructure projects from a data-driven perspective, and the sensitivity of the application rate of information management technology, the application rate of data analysis methods, the participation rate of experts in decision-making, the historical case information on this project, and the information on similar projects on the effectiveness of program implementation were simulated and analyzed. The results of the study showed that all five key influencing factors have a positive impact on the effectiveness of program implementation. In addition, the application rate of information management technology and the application rate of information analysis methods have a higher sensitivity to the effectiveness of program implementation, the participation rate of experts in decision-making and historical case information on this project have average sensitivity to the effectiveness of program implementation, and information on similar projects has lower sensitivity to the effectiveness of program implementation. This study provides some ideas and suggestions to promote the effective use of information technology and digital technology by each participant in the construction of mega infrastructure projects while improving their dynamic decision-making efficiency, scientificity, and accuracy.

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