The planning effectiveness of construction site layout greatly influences construction efficiency. Many previous studies assumed that all the facilities exist on the construction sites for the whole duration of the projects. Some researchers found the shortcomings and developed models to improve it. But these models also have different limitations, such as ignoring the future impact of the layout decision in early construction phases on the later layout quality, only considering transportation costs when optimize the layouts, etc. To address these issues, this study proposes a building information modeling (BIM)-based model that dynamically optimizes the multi-objective construction site layout. In this model, BIM and construction schedules provide the updated construction project information. This model introduces the construction phase impact on layout. The layout of each construction phase is optimized in order of corresponding phase impact. Considering the sustainable development for construction industry, the noise pollution level is chosen to be the optimization objective together with the total transportation cost. In order to balance the noise pollution level and total transportation cost, the multi-objective particle swarm optimization (MOPSO) is applied to obtain trade-off solutions. A case study is presented to demonstrate the capability of the proposed model. The results indicate that the proposed dynamic construction site layout plan (CSLP) reduces transportation cost by 43.45% and 11.46% compared with the original and static construction site layout. This study breaks the traditional site layout plan order and locates the facilities in order of their phase impact, which can greatly reduce the transportation cost on the site. It also incorporates the noise pollution reduction into CSLP to enhance on-site sustainability.

Many construction activities generate fine particles and severely threaten the physical health of construction workers. Although many dust control measures are implemented in the industry, the occupational health risks still exist. In order to improve the occupational health level, this study proposes a new method of reducing the construction dust pollution through a reasonable site layout plan. This method is based on the field measurement and dust diffusion law. The dust diffusion law can be fitted based on the field monitoring data. With diffusion law, the average dust concentration exposed to workers of different site layouts can be simulated. In addition, the cost of the dust control method is a concern for site managers. Therefore, the total transportation cost reduction is another optimization objective. Finally, the multi-objective particle swarm optimization (MOPSO) algorithm is used to search for an optimized site layout that can reduce dust pollution and transportation cost simultaneously. The result shows that average dust concentration exposed to workers and total transportation cost are significantly reduced by 60.62% and 44.3%, respectively. This paper quantifies the construction dust pollution and provides site managers with a practical solution to reduce the construction dust pollution at low cost.

Based on the theory of system dynamics, we investigated the factors influencing the trust relationship between owners and PMC contractors in a Chinese management scenario, and proposed effective management strategies to increase the level of trust between the two parties. In the early stages of PMC project implementation, calculative trust between the owner and the PMC contractor predominated, while relational trust predominated in the middle and late stages. The applicability of the PMC model and the control configuration between the owner and the PMC contractor are also vital factors influencing the trust level. Principal determinants of calculative trust are the management capability and reputation of the PMC contractor, the sufficiency of the owner’s authorization, and the efficacy of the owner’s supervisory measures. There are four factors that influence relational trust, in order of decreasing influence: the sufficiency of the owner’s authorization, the effectiveness of the owner’s supervisory measures, the social similarity between the owner and PMC contractor, and the management capability and reputation of the PMC contractor. The research can be used as a guide for enhancing PMC project management performance and achieving PMC project success.

Non-commercial resources provided by employers (NCRPE) are the imperative factors affecting the progress of engineering projects. However, the NCRPE with limited supply ability is rarely considered in the schedule optimization models in previous studies. The NCRPE schedule requirement may exceed its limitation, resulting in failing to optimize the schedule. Therefore, a new schedule optimization model is built from the perspective of NCRPE. First, the features of NCRPE and corresponding optimization theory are analyzed. Then, two optimization models are proposed in multi-contract environment before and during the construction of a project, aiming to minimize the unbalance coefficient, variance of NCRPE, and the requirement strength of NCRPE, respectively. Finally, a case study about the South-North Water Transfer Project Program X is conducted. The results show that the proposed model could effectively solve the NCRPE schedule optimization problem. A reasonable and practical program planning and adjustment within different stakeholders can be obtained. The NCRPE schedule optimization can minimize the peak demand amount of the program resources and achieve a relatively balanced total resource demand before the program implementation. Besides, it ensures that the original production system capacity can satisfy the actual demand in the program implementation. The research results can provide a basis for the bidding of each contracted project in the program and the resources optimization of each contracted project in the program implementation process.

In Public–Private Partnership (PPP) projects, the structure of the Special Purpose Vehicle (SPV) significantly impacts the value enhancement of projects. This study conducted a quantitative analysis of value enhancement in green PPP projects under single- and Dual-Role entity models and examined existing SPV private party compositions. A quantitative model was developed to enhance the value in green PPP projects through a Dual-Role “investor–builder” entity approach, comparing it with the single-role entity model. The findings indicate that in the Dual-Role entity mode, the construction party demonstrates a greater willingness to effort, resulting in shorter construction timelines and improved economic benefits for the project company. The preferred equity range for private parties escalates with the total project investment and the extent of “political support”. Nevertheless, a disproportionately high government stake in the equity is detrimental to the value enhancement in PPPs, and excessive government regulation and control should be avoided. This quantitative model serves as a decision-making criterion for selecting the SPV mode and provides an alternative approach for evaluating PPP project performance.

Water environment governance of large rivers is an essential measurement of ecological protection in China. The effectiveness of governance depends highly on the fulfillment of strategic CSR (corporate social responsibility) of Chinese leading enterprises. However, the fulfillment of strategic CSR often brings economic burden to the leading enterprises and needs government compensation support. Therefore, this paper explores the impact of government compensation on the fulfillment of strategic CSR of Chinese leading enterprises by constructing a multi-stage portfolio model. The main results show that (1) the prerequisite for leading enterprises to fulfill strategic CSR is sufficient profits; (2) the increase in government compensation can significantly affect the proportion of strategic CSR fulfillment of leading enterprises; (3) only when the portfolio considers both strategic CSR and project benefits, can the leading enterprises obtain the highest economic returns and better fulfill strategic CSR. The results can provide policy reference for the government to stimulate the fulfillment of leading enterprises’ strategic CSR and also give suggestions for the leading enterprises to alleviate the economic pressure brought by fulfilling strategic CSR.