Due to the relatively long period and large capital flow of public-private partnership (PPP) projects, PPP participants are faced with a complex risk situation impeding the sustainable project delivery. In recent years, risk management of PPP projects has received increasing attention. In this paper, twenty risk factors associated with infrastructure PPP projects were identified by literature review and in-depth case studies. Relationship data for these twenty typical risk factors were obtained through structured interviews. Based on the obtained data, the risk relationship network within infrastructure PPP projects was identified, and the network structure characteristics were analyzed, including individual node attributes and the influence and cohesion of subgroups. The results indicate that key risk factor nodes can form a reaction chain via bridge nodes that can trigger a risk domino effect within PPP projects. Specifically, the key risk factors of PPP projects are divided into two categories, the first of which include risk factors that have powerful and independent influence, such as delay in government approval, government credit, and imperfect legal and regulatory systems. The second category includes risk factors that are highly vulnerable and easily influenced, such as completion risks, insufficient revenue in the market, and fee change. A key risk factor reaction chain is one in which legal change leads to a decline in government credit rating, triggering a contract risk. Twelve bridge nodes were identified that play an important intermediary role in the network, e.g., legal change, public objection, and financing risk. This paper extends the application of social network analysis in PPP projects management research and identifies the key risk factors and crucial factors influencing chain reactions in PPP projects. The results provide a more in-depth understanding of sustainable PPP project management for government agencies and private enterprises.

Lean construction has been viewed as an effective management approach for reducing the occurrence of no-value or destructive activities, such as wasting resources and safety-related accidents. However, few studies have systematically addressed how and to what extent lean construction practices influence construction safety. To bridge this gap, a conceptual model is developed and validated using a system dynamics approach. The construction system in this model comprises four sub-systems (i.e., environment system, equipment system, management system, and employee system). Data were collected from 448 projects in China. Simulations were conducted to determine the correlations between five types of lean tools and the four construction sub-systems. The results show that: (a) 5S management has significant positive impacts on the control of key locations and facilities at construction sites, and contributes to the mitigation of environmental impacts; (b) visual management can significantly improve safety compliance and safety management; (c) just-in-time management has significantly positive influences on the safety facilities layout and formulation of the safety plan; and (d) the Last Planner^® System and conference management are effective in improving safety training and the implementation of the safety plan. These findings provide new insights into the use of lean construction for improving construction safety through the implementation of a targeted lean approach.

This study aims to investigate the level of social capital between construction supervisors and workers and how this influences construction workers’ safety behavior. To fulfill these research aims, a structural equation model (SEM) was constructed to explore the relationships among social capital (including the structural, relational, and cognitive dimensions); safety competency; and safety behavior (i.e., safety compliance and safety participation), considering safety competency as a mediation variable. Data on these variables were collected via questionnaires answered by 535 construction workers who participated in 93 completed building projects in China. In regard to safety behavior, only the cognitive dimension, represented by shared language and shared goals, had a significant positive effect on safety behavior. The structural dimension, which includes network ties between supervisors and workers as well as the centralization of supervisors, had a significant negative effect on safety behavior. The relational dimension, characterized by mutual trust and reciprocity norms, had no direct or indirect effect on safety behavior. For the mediation effect, the cognitive dimension had an indirect, positive effect on this variable, considering safety competency as the mediation variable; the structural and the relational dimensions did not indirectly affect safety behavior. This paper provides a theoretical basis for construction supervisors to develop measures to improve workers’ safety behavior from the perspective of relationships between people, and it points out the important role of safety competency in safety behavior. Unlike assumptions, the high level of the network has a negative effect on safety behavior, which should cause supervisors to pay attention to workplace safety management. In general, this study can inform management methods for improving workers’ safety behavior and on-site safety conditions from the perspective of social capital.