YL
Y. Li
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1
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.
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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.
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.
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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.
Analyzing and Controlling Construction Engineering Project Gray Rhino Risks with Innovative MCDM Methods
Interference Fuzzy Analytical Network Process and Decision-Making Trial and Evaluation Laboratory
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.
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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.