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Due to their characteristics and multiple objectives, high-speed rail (HSR) projects carry more complex risks than conventional projects and high correlation and conductivity are among the associated risk factors. Previous risk assessment frameworks for rail infrastructure have ignored the effects of risk interactions that inflate risk levels, namely, risk coupling effects. Based on a system dynamics method, this paper develops a risk coupling model for HSR project risk assessments. A risk factor list is established from a literature review, and relationships analysed using a case study and expert interviews. System dynamics equations are constructed and their parameters obtained by expert evaluations of risk factors. The proposed model is applied to a real-world HSR project to demonstrate it in detail. The model can evaluate the risk levels of HSR projects during a simulation period. In particular, it can identify the key coupling effects that are the main increased risk. It provides a significant resource, using which HSR project managers can identify and mitigate risks.

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The main participants in construction projects are the client, contractors, material suppliers, and consultants such as the project supervisor. They play the most important roles in implementing construction projects, and their behavior has a significant impact on the project’s performance. Because each participant has their own particular interests, by virtue of proprietary information advantage, each individual participant is driven to achieve maximum benefit, which can result in improper behavior with respect to each other. The risk of this resulting in moral hazard and adverse selection based on information asymmetry is called behavioral risk among principal construction participants. Behavior is affected by various risk factors; successful implementation of construction projects depends on effective management of the key risk factors. This paper identifies and ranks the critical behavioral risk factors from the perspective of principal construction participants in the Chinese construction industry. The data used for analysis is based on an interview and questionnaire survey. Factor analysis is conducted with the assistance of SPSS17.0. Forty-one potential behavioral risk factors are identified, with 30 of those being critical, including “client changes project objective or investment direction”, “designer uses technological capability advantage to obtain profit”, and others. These findings contribute to the understanding of risk management in the construction industry in China. They also serve as a useful reference for further studies on the subject.

Mega infrastructure projects provide a basic guarantee for social development, economic construction, and livelihood improvement. Their operation and maintenance (O&M) management are of great significance for the smooth operation and the realization of the value created by the projects. In order to provide an approach for effectively evaluating O&M management, this study develops a holistic indicator system using a mixed-review method from the national macro perspective in China. In this study, literature analysis, policy texts, expert interviews, and grounded theory were used to collect relevant data at home and abroad, and establish an initial evaluation indicator system with 23 indicators covering two dimensions and five aspects. Then the questionnaire survey and factor analysis were used to score and categorize the indicators, and finally an evaluation indicator system for O&M management of mega infrastructure projects was formed. The results show that social relations, environmental benefits, macro policy, and operational capacities play an important role in the evaluation of the O&M of mega infrastructure projects. This study helps the management team to avoid negative impacts in the O&M management of mega infrastructure projects and lays a theoretical foundation for future research. The indicator system in this study is based on the Chinese context, and it remains to be verified whether the indicator system is applicable to other countries due to the differences in political and cultural backgrounds in different regions.