Major infrastructure projects (MIPs) possess significant strategic positions in the national economy and social development. However, recently, the rent-seeking behavior between supervision units and project contractors has intensified in project construction. This paper aims to study the behavior decision-making of stakeholders in rent-seeking behavior supervision system of MIPs. In the complex and uncertain environment of MIPs, game players have cognitive bias and value perception preference. Therefore, this study introduced prospect theory and constructed the perceived return matrix and evolutionary game model of MIP rent-seeking behavior supervision among project owners, supervision units, and project contractors. From the perspective of risk perception theory, the reasons for the behavioral tendencies of game participants and the conditions for the steady state of strategy selection were explored through system dynamics simulations. The results showed that the stable state of the optimal strategy in the rent-seeking behavior supervision system of MIPs is related to the cognitive bias of the game players and is influenced by the level of regulation cost, the intensity of punishment and the size of accident losses. The contribution of this study lies in providing theoretical basis and decision support for constructing a long-term preventive mechanism for rent-seeking activities in MIPs.

Failure Mode and Effect Analysis (FMEA) is a useful risk assessment tool used to identify, evaluate, and eliminate potential failure modes in numerous fields to improve security and reliability. Risk evaluation is a crucial step in FMEA and the Risk Priority Number (RPN) is a classical method for risk evaluation. However, the traditional RPN method has deficiencies in evaluation information, risk factor weights, robustness of results, etc. To overcome these shortcomings, this paper aims to develop a new risk evaluation in FMEA method. First, this paper converts linguistic evaluation information into corresponding interval-valued intuitionistic fuzzy numbers (IVIFNs) to effectively address the uncertainty and vagueness of the information. Next, different priorities are assigned to experts using the interval-valued intuitionistic fuzzy priority weight average (IVIFPWA) operator to solve the problem of expert weight. Then, the weights of risk factors are subjectively and objectively determined using the expert evaluation method and the deviation maximization model method. Finally, the paper innovatively introduces the interval-valued intuitionistic fuzzy weighted averaging (IVIFWA) operator, Tchebycheff Metric distance, and the interval-valued intuitionistic fuzzy weighted geometric (IVIFWG) operator into the ratio system, the reference point method, and the full multiplication form of MULTIMOORA sub-methods to optimize the information aggregation process of FMEA. The extended IVIF-MULTIMOORA method is proposed to obtain the risk ranking order of failure modes, which will help in obtaining more reasonable and practical results and in improving the robustness of results. The case of the Middle Route of the South-to-North Water Diversion Project’s operation risk is used to demonstrate the application and effectiveness of the proposed FMEA framework.

The transformation and upgrading of the construction industry has made obvious progress in China. However, the low degree of digitalization is still prominent. The digital transformation decision-making behavior of key participants in the construction industry is easily affected by economic interests, meaning that the implementation of digital transformation is a dynamic evolution process of repeated adjustment and continuous learning. Therefore, this study constructed a tripartite evolutionary game model of the government, service providers, and construction enterprises, and analyzed the strategy selection of each game player and the stability of the system equilibrium point. Moreover, the validity of the model and the influence of various factors on the system were verified and analyzed by numerical simulation. The results showed the following: (1) The government’s tax refund ratio and subsidy coefficient can significantly increase the motivation of construction enterprises and digital construction service providers within a certain threshold. (2) Whether enterprises carry out a comprehensive digital transformation depends on the revenue of the system solution strategy; the greater the revenue, the more positive the enterprises. (3) The adoption of high rewards and high penalties by the superior government can effectively encourage the local government to actively promote digital transformation. The contribution of this study lies in providing a theoretical basis and decision support for promoting the digital transformation of construction enterprises.

Ecological technology innovation with environmental benefits as the core has become an inevitable choice for water environment treatment PPP projects (WETP-PPP), and government supervision and public participation are essential driving factors for eco-technological innovation. To explore the influence of public participation on the behavior of the government and private sector in the WETP-PPP, this study constructed an asymmetric evolutionary game model of government supervision and private sector ecological technology innovation behavior under public participation. The main contribution of this study is to explore the mutual evolutionary regularity of the private sector and government supervision department and the influence of public participation level on public and private behavior in different scenarios. The results showed that the government can reduce the supervision cost by increasing the public’s active participation and improving environmental regulation measures to achieve a win-win situation of economic and environmental performance.

The tendency of infrastructure projects to be complex, large-scale, and long-term prompts temporary project organizations’ need to have resilience to deal with various risks, uncertainties, and crises. The resource and cognitive capacity of stakeholders are key factors in infrastructure project governance and crisis response in the face of shock generation. Moreover, previous studies on organizational resilience of infrastructure projects have lacked exploration from project governance perspectives. Hence, the objective of this study is to investigate the influence of contractual and relational governance on the organizational resilience of infrastructure projects from the perspectives of resource reconfiguration and organizational cognition. Firstly, this study established a conceptual model through a theoretical background and hypotheses development. Then, a questionnaire was designed for participants in the infrastructure projects to collect data on the respective effects of each variable. A total of 519 complete responses to the questionnaire were collected, and a path model was developed to quantitatively measure the impact of contractual and relational governance on organizational resilience using the partial least squares–structural equation modeling (PLS-SEM) method. Finally, the model was validated using reliability and validity testing, hypotheses testing, and mediating effect testing. The results of the study showed that the contractual and relational governance can enhance the level of organizational resilience. Resource reconfiguration and organizational cognition play a mediating role in the relationship between project governance and organizational resilience. This study extends the theoretical research on the impact of project governance on organizational resilience, and deepens the intrinsic link between the two from the perspective of resource reconfiguration and organizational cognition, so as to provide effective theoretical guidance for crisis response and sustainable operation of infrastructure projects.

The cost segregation study is a tax planning strategy employed to optimize cash flow by redefining real estate assets as personal property and land improvement, enabling accelerated tax depreciation. However, conventional cost segregation practices suffer from limitations, such as time-consuming procedures and high associated costs, which hinder their effectiveness. To overcome these challenges, this paper presents an innovative strategy that integrates Building Information Modelling (BIM) to develop an automated cost segregation system. The research aims to optimize the workflow by developing a BIM model and using 5D BIM to perform a cost segregation study by categorizing building elements under a Modified Accelerated Cost Recovery System (MACRS). This workflow aims at minimizing the time and financial resources expended with traditional methodologies. The proposed workflow enables precise identification and separate depreciation of building components, resulting in significant tax deductions that would otherwise be unattainable. The results indicate that performing cost segregation with BIM leads to a significant increase in depreciation amounts, particularly during the initial six years, while also raising the net present value of depreciation by 45%. The integration of BIM technology facilitates effective management and sharing of cost segregation data among stakeholders, enhancing collaboration and decision-making throughout the project lifecycle. Owners can optimize cost management and financial planning, identifying tax-saving opportunities and improving cash flow. General Contractors (GCs) can leverage the system during the bidding process, enhancing their competitiveness and project acquisition potential. Future research can explore the integration of cost segregation modules from BIM with asset management tools, enabling improved facility and fiscal management of building components. Such integration holds promise for enhancing the construction and real estate industry’s overall efficiency and performance.