Despite the importance of motivation in driving the formation of collaborative risk management, the existing literature lacks recognition of stakeholders’ motivations to participate in the collaborative risk management of mega infrastructure projects. By combining interview data with the theoretical framework based on previous literature, this study constructs a motivation framework for stakeholders to participate in collaborative risk management of mega infrastructure projects, comprising four groups of motivations formed by glue identity logic (organizational or individual level) and interest logic (intrinsic drive or extrinsic stimulus). Motivational differences between project owners and contractors are discussed based on the case study of the Hong Kong-Zhuhai-Macao Bridge, indicating that these differences are closely related to the identity of stakeholders and project progress. This study contributes a systematic perspective to recognize the motivations behind participation in collaborative risk management of mega infrastructure projects, aligns managerial intentions with actual motivations, and uncovers new insights into collaborative risk management. It enriches the collaborative risk management theory in mega infrastructure projects and provides guidance and inspiration for practitioners in decision-making and collaborative risk management in such projects.@en

Contemporary Chinese artist villages (CCAVs) have been developing rapidly and have become an important locus for developing cultural and creative industries, providing a strong pathway for China to achieve high-quality development and promote new urbanization. However, in practice, there are still many CCAVs that struggle with sustainable development. At present, the academic research on CCAVs mainly focuses on demonstrating the role of artist villages in promoting development in economic, social, artistic, and other fields without forming a systematic, sustainable development model or targeted policy recommendations. Therefore, the CCAV must be taken as a research object, and the influencing factors and mechanisms of its development must be analyzed through systematic quantitative research to provide a theoretical basis for the sustainable development (SD) of CCAVs. This paper identifies the factors influencing the sustainable development of CCAVs through grounded theory and expert interviews and creates a list of 21 influencing factors. Based on internal and external considerations, these influencing factors can be divided into the following four categories: artists, government, company/capital, and outside environment. This paper constructs a mechanism model for the SD of CCAVs with the help of a structural equation model, which is a quantitative analysis tool based on empirical research. The key mechanisms influencing the SD of CCAVs are obtained through research. Using quantitative research, the paper determines four categories of influencing factors and the mechanisms influencing the SD of CCAVs. This study provides an important resource for governments at all levels to promote the sustainable development of artist villages in the region.@en

As a development form of the creative industry, the Artist Village is a high concern of the Chinese government, and it has achieved rapid developments in China in recent years. However, many Artist Villages come to an untimely end a short period after their birth and fail to realize sustainable development. In this study, an empirical analysis on 80 Artist Villages in China was carried out. A field investigation and research on eight Artist Villages was implemented. Attention was paid to thoroughly analyze three typical Artist Villages of Guangzhou Xiaozhou Artist Village, Chongqing Gujianshan Artist Village and Beijing Songzhuang Artist Village. It has been found from studies that the development of Artist Villages in China has experienced initiation, development and maturity stages. The development of Artist Villages in China generally has many problems, such as an insufficient endogenous impetus, the excessive intervention of government, market capital “squeezing out” the original artists, and so on. This paper proposed a sustainable development model for Artist Villages during urbanization in China based on the findings and conclusions of this study. This study not only enriches research contents in this field, but can also provide meaningful references for the sustainable development of Artist Villages in China.@en

Operation risk (OR) has affected sustainable development of urban rail transit (URT) public–private partnership (PPP) projects in China. Balanced distribution of operational risks among stakeholders (the public, government, and private companies) involved in URT PPP projects can maximize overall profit. Quantitative analysis of operational risk allocation of urban rail transit PPP project is the key to achieve balance. Few existing studies have quantitatively analyzed operation risk allocation (ORA) in URT PPP project. The objective of this research is to construct a quantitative risk allocation model among three participants by using cooperative game theory. The risk allocation model was modified based on the consideration of four factors affecting the allocation of operational risks: controllability, risk loss, affordability, and handling cost. A case was used as an empirical example, and possible problems were illustrated. The result shows it is necessary and feasible to let the public bear part of the operational risk of the project by raising ticket prices. The results reveal that the public will play an important role in balancing risk allocation. This study shows that an ORA model can suggest how to make the risk allocation process more reasonable, fair, and stable. Meanwhile, the quantitative approach proposed can also be used by stakeholders in achieving fairness and stability of the partnership.

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Mega infrastructure projects (MIPs) are exposed to numerous interdependent risks of various natures which pose difficulties in risk management. Thus far, the research on the risk interactions of MIPs has been focused on developing static risk networks within a single category of risks, at certain stages of the project. It is essential to understand the risk interactions at various stages of MIPs to identify the key risks and key risk relationships that jeopardise their success. This is especially relevant nowadays, as MIPs are expected to be delivered sustainably. Therefore, to analyse the dynamic risk interaction of MIPs, initially, through literature analysis and expert interviews, combined with the four dimensions of sustainable development and the four stages of MIPs, 98 risk factors of MIPs were identified. Subsequently, semi-structured interviews were conducted to determine risk relationships and weights. Risk networks were developed for each stage of MIPs, and improved social network analysis was applied to these risk networks. Finally, the key risks and key risk relationships in each stage of MIPs were identified by analysing the changes of multi-level network indicators. This aided in determining risk control strategies. The results demonstrate that the key risks and key risk relationships are different for each stage of MIPs. Furthermore, the risks of different dimensions of sustainable development have different relationships at different stages. This research is the first to identify the risk relationships involved in MIPs by taking into consideration the whole project life cycle and its sustainable development. This research provides theoretical support for the risk management of MIPs, and strategic suggestions for controlling the risks at each stage of the project.@en

Construction engineering projects are costly and require large amounts of labor, physical, and financial resources. The failure of a construction engineering project typically brings huge losses. Previous studies have focused on the identification of risks, but insufficient attention has been given to strategic resource allocation for risk management after risk identification. Statistics show that most construction engineering project failures are caused by common risks. Common risks are called gray rhino risks. This metaphor illustrates that many risks are obvious but dangerous. This study was motivated by the challenge of efficiently managing gray rhino risks with limited inputs. The literature suggests that gray rhino risks are abundant in construction engineering projects and that there are mutual eliciting relationships between them, which make it difficult for the manager to devote enough resources to the prevention of key risks. Considerable resources are wasted on unimportant risks, resulting in key risk occurrence and failure of construction engineering projects. Therefore, this study describes an innovative multi-criteria decision making (MCDM) technique for ranking risks based on the strength of the eliciting relationships between them. This study used the fuzzy technique and created an interference fuzzy analytical network process (IF-ANP) method. By employing the IF-ANP alongside a decision-making trial and evaluation laboratory (DEMATEL) approach, the subjectivity can be effectively reduced and the accuracy improved during expert risk evaluation for construction engineering projects. IF-ANP was used to quantify eliciting relationships between risks and DEMATEL was used to rank risks based on the IF-ANP result. An empirical study was done to meticulously rank five risks that were selected from the gray rhino risks in the Chengdu–Chongqing Middle Line High-speed Railway construction engineering project. They are capital chain rupture, decision failure, policy and legal risk, economic downturn, and stakeholder conflict. The results showed that the policy and legal risk was the source of other risks, and that these other risks were symptoms rather than the disease.@en

Mega infrastructure projects (MIPs) have become increasingly important to the realization of sustainable development in China. Sustainable development is a process of dynamic balance, and coordinating the triple bottom line (the environmental, social, and economic dimensions) will enable more sustainable development of MIPs. However, previous studies have lacked consideration of coordination when applying sustainable development principles to the systematic identification of risks to MIPs. The goals of this study were to clarify the definition and dimensions of the sustainable development of MIPs and to identify the key risks of MIPs. A literature review was performed to extend the definition of sustainable development of MIPs by combining the triple bottom line with a fourth coordination dimension. A conceptual model of MIP risk identification was then proposed from an extended sustainable development perspective, 22 sustainability elements and 75 risk factors were identified, and the key risk factors were determined based on the interview responses and fuzzy set theory. The results show that economic risks have a high probability, social risks have a high loss, environmental risks have an intermediate probability and loss, and coordination risks have the greatest impact. In addition, the three most important key risk factors were found to be construction and installation cost overruns, land acquisition and resettling cost overruns, and information sharing with the public. Identifying key risk factors can provide information to help stakeholders understand the risk factors associated with MIPs and formulate reasonable risk response strategies.

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In recent years, more and more construction enterprises are expanding into overseas markets, especially in underdeveloped regions such as Africa. Compared to domestic construction projects, international construction projects have been faced with more uncertainties and increased levels of safety risks to the employees in the context of political turmoil, racism, and religious conflict in the host country. This study aims to answer what risk factors contribute to the threat to the safety of overseas employees and how safety risk factors interact, using employees from Chinese international construction companies (CICCs) in Africa as an example. A total of 39 safety risk factors were selected by literature review and case study based on Heinrich’s Domino Theory of Accident Causation. To identify the critical safety risk sources and significant risk paths, a questionnaire survey was conducted among 208 professionals who have participated in construction projects in Africa. Using structural equation modeling (SEM), a total of twelve critical risk paths and five controllable risk sources were identified. The improper behaviors of the CICCs and their employees were shown to have the largest impact on the safety of Chinese employees, through the mediating effect of the criminal offense. This study provides some insights into safety risk management in international construction projects. Meanwhile, the quantitative approach proposed can also be used by other international companies or governments in identifying the safety risk paths of their overseas workers involved in international construction projects. @en

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.

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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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