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.

Megaproject construction endeavors and technological innovation activities, led by industry–university–research (IUR) collaboration, demonstrate marked disparities in value orientations, implementing entities, and constituent components. These discrepancies lead to a mismatch between innovation demands and actual activities, as well as insufficient innovation motivation among construction entities, subsequently impacting innovation effectiveness and the commercialization of outcomes and failing to adequately support engineering construction needs. In response to this predicament, the academic community widely acknowledges IUR collaborative innovation as a solution. This research integrates fundamental theoretical analysis with a multi-case study approach and systematically dissects the distinctive features at the micro, meso, and macro levels, grounded in the collaborative innovation practices of IUR in three iconic railway engineering projects in China. Subsequently, it unravels the inherent operational mechanics of the IUR collaborative innovation system within large-scale projects. Specifically, at the micro level, the profound engagement of governments and project owners fosters a solid supportive environment and collaborative platform for IUR collaboration, while past successful cooperation experiences among key innovation entities enhance their technological and knowledge interactions. At the meso level, shared industry cognitions and values, hierarchical organizational structures, flexible institutional designs, and resource allocation strategies based on balancing risks and benefits collectively constitute the supporting system for megaproject collaborative innovation. At the macro level, the tight integration of the innovation chain and industrial chain promotes the formation of an open cooperation ecosystem, ensuring the continuity and systematic nature of innovation activities and accelerating the rapid commercialization and efficient utilization of innovation outcomes. This study not only enriches the theoretical connotations of IUR collaborative innovation in the context of major engineering projects but also provides theoretical foundations for strategy formulation and management practices for major project managers, holding significant value in guiding the innovation management of future major engineering projects.

The burgeoning development of railway construction in plateau regions of southwest China necessitates innovative and environmentally sustainable approaches, particularly in the realm of tunnel construction, where the transfer of muck poses significant operational and environmental challenges. This research, pivoting around the application and configuration of electric muck transfer equipment in plateau railway tunnels, seeks to dissect the potentialities and impediments of transitioning from conventional diesel-powered machinery to electric alternatives, with a spotlight on mitigating environmental impacts and enhancing operational efficiency. Through an analytical lens, the study employs a case study methodology, leveraging data and insights from existing electric equipment models and their applications, provided by major manufacturers in China, to weave a comprehensive narrative around the practicalities, specifications, and challenges embedded in the adoption of electric machinery in plateau environments. The findings unveil a nuanced landscape, where the environmental and operational advantages of electric equipment are juxtaposed against a backdrop of technological, financial, and infrastructural hurdles, thereby crafting a complex tapestry of opportunities and challenges. The research further extrapolates policy recommendations and practical guidelines, advocating for a harmonized amalgamation of governmental policies, technological advancements, and strategic planning to navigate through the identified challenges and optimize the integration of electric equipment in tunnel construction practices. Envisaging future research pathways, the study underscores the criticality of perpetuating technological innovations, policy adaptations, and interdisciplinary research to further refine and enhance the application of electric muck transfer equipment in plateau railway tunnel projects, thereby contributing to the broader narrative of sustainable construction practices in challenging terrains.

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.

Purpose: Construction safety resilience is gradually gaining attention in the field of engineering construction as a new management concept and way to improve safety performance. However, how to cope with the dilemma of the unclear relationship of construction safety resilience elements at the practice level and promote the harmonization of construction safety goals and resilience enhancement paths has become an urgent challenge for safe construction. Design/methodology/approach: This study analyzes the components of construction safety resilience elements. A relationship network model of construction safety resilience elements is developed by using the social network analysis method. The location and influence of each element in the network and the interrelationships among the elements are explored in depth. Findings: The findings reveal a robust interconnection among the elements of safety resilience in the construction industry. Key components such as safety behavior, risk prevention and control mechanisms, disaster prevention and mitigation technologies as well as information technology, are positioned at the core of the network. Notably, safety behavior exerts the most significant influence over the other elements, serving as the linchpin of safety management in the construction industry. Moreover, the interplay among safety resilience elements in the construction sector can alter the structure of the relationship network. Originality/value: This study adopts the social network approach to solve the problem that it is difficult to quantitatively analyze the elements of construction safety resilience and their interrelationships and to clarify the interactions among the core elements, which can help to further assist the construction project manager to continuously optimize safety resilience and improve construction safety.

This study optimizes the configuration of Electric Concrete Transport Vehicles (ECTVs) for long-distance tunnel construction, focusing on the critical factors of driving range and reliability. A comprehensive model integrating tunnel length, terrain, construction schedules, vehicle load capacities, driving range, and reliability is developed. The study acknowledges limitations of traditional fuel-powered vehicles and proposes ECTVs as a sustainable and reliable alternative. The model is validated through a case study in a plateau region of Southwest China. Key findings show that the number of ECTVs required increases with excavation distance, seasonal variations significantly impact configuration, and balancing loading capacities with driving range and reliability is crucial for optimization. The study contributes a new approach to ECTV configuration by incorporating driving range and reliability into the model, offering practical guidance for construction managers to reduce costs, minimize delays, enhance efficiency, and improve reliability.