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There are a large number of interdependent risk factors in complex project. Risk response strategy without considering risk correlation cannot achieve good risk response. Therefore, the purpose of this paper is to propose a risk response strategy selection model considering risk correlation based on the grey K-shell algorithm.

This paper mainly focuses on the measurement of two aspects of risk factors. One is the ability of the risk factors to influence other risk factors, another is the degree affected by other risk factors. Both of the above are measured by the grey K-shell algorithm improved in this paper, and the weights of these are used for the constructing of risk response strategy selection model.

The risk response strategy considering risk relevance is more effective than the risk response strategy without considering risk relevance. Also, results indicate that as the risk response budget increases the risk response effect also increases, and the increasing trend is weakens. The relative gap between the effect of response strategies considering risk relevance and the strategy without considering risk relevance increases first and, then, decreases with the increase of budget.

The results of this paper demonstrate that the risk response strategy considering risk relevance is more effective than not considering risk relevance. The approach presented in this paper can guide project managers’ risk decisions and may also help to find the best risk response budget.

The objective of this research is to develop a decision method that can generate appropriate risk response strategies for international construction project managers (PMs) and allow these strategies to reflect their different risk preferences.

The optimal model approach is adopted. A credibility-based fuzzy chance constrained programming (CFCCP) model is developed, which simultaneously minimizes the expected losses of risk events and total costs of risk response. To solve this multi-objective model, a fuzzy interactive solution method is used. Moreover, the model performance is demonstrated by a real international industrial plant project. In addition, a sensitivity analysis of the model is conducted.

The result of the sensitivity analysis indicates that PMs with a greater risk aversion can lead to a higher mitigation ratio of expected losses of risk events and a higher total cost of risk response.

This research provides contractors with an effective decision-making model to develop a project risk response plan, and it will assist contractors to minimize risk losses and enhance the project performance in the international construction market.

Previous studies overlook the risk preference, which is an important behavioral factor influencing decisions in risk response strategy selection. This research proposed a novel risk response strategy selection decision method that considers different attitudes toward risk among decision makers.

The purpose of this paper is to propose a method integrating fault tree analysis and optimization model to allocate response budget from the preventive and protective perspectives.

The proposed method consists of two main steps. The first step is to analyze and calculate the probability and the loss of the risk. The second step is to build an optimization model for allocating response budget.

First, there exists an optimal response budget. Second, risk protection is preferred to risk prevention when the total budget is limited. Third, the protective budget should be first invested for the consequence event with greatest expected loss. Fourth, the preventive budget should be first allocated to the risk cause with highest occurrence probability that belongs to the OR set in the fault tree.

Managerially, our results indicate that project managers (PMs) should make a tradeoff between the budget invested for risk response and reduced expected loss of the risk. Then, in the case of inadequate response budget, PMs should pay more attention to risk protection and cope with the event that can cause severe loss. In addition, under this circumstance, PMs had to better allocate the risk preventive budget in proper order.

Project risk response is a critical issue in project risk management as PMs can take actions actively to cope with project risks in this phase. Effective risk response, in general, requires financial support in practice, and reasonable allocation of the total budget among risk response strategies can produce better response effects.

This paper discloses the risk management response strategies and the perceived effectiveness of the strategies employed by companies operating within manufacturing clusters in Puerto Rico from 2016 until 2020, the second year of the coronavirus disease 2019 (COVID-19) pandemic.

The research design consists of questionnaire-based survey responses from companies belonging to manufacturing clusters, followed by semi-structured interviews and secondary sources of information.

The results reveal the risk responses used to manage specific risk types. Albeit respondents' dependency on an assortment of company-centric and cluster-bound risk response strategies, the perception is that the former is more effective when adequate local sources are available and the latter when the cluster has strong interconnectedness among the cluster's members.

Furthermore, there is a generalized belief that long-term cluster-bound strategies are required to complement individual companies' overall risk management strategies.

This paper demonstrated that due to the volatility, uncertainty, complexity and ambiguity (VUCA) nature of the Caribbean region, mixed risk management might result in better and more favorable long-term performance.

Firms are increasingly accountable for their suppliers' social and environmental practices. Nonmarket stakeholders nowadays do not hesitate to confront buying firms for their suppliers' misconducts by mobilizing demonstrations, social media campaigns and boycotts. This paper aims to develop a typology of response strategies by targeted firms when they face such contentions and to empirically investigate why these strategies vary among those firms.

Drawing on social movement and stakeholder salience theories, the authors develop a set of hypotheses linking their typology of four response strategies to three key contextual factors – nonmarket stakeholder salience, nonmarket stakeholder ideology and the target firm reputation – and examine them using a vignette-based experiment methodology.

The results suggest that nonmarket stakeholder salience significantly impacts the nature of response (reject or concede), whereas the nonmarket stakeholder ideology is significantly related to the intensity of response (trivial or vigorous). Interestingly, the firms' reputation was found to have no significant effect on their response strategy when they faced stakeholder contentions.

This paper adds both theoretical and methodological value to the existing literature. Theoretically, the study develops and tests a comprehensive typology of response strategies to nonmarket stakeholder contentions. Methodologically, this study is original in leveraging a vignette-based experiment that allows establishing causal factors of response strategies following a supplier sustainability misconduct.

Under uncertain circumstances, digital technologies are taken as digital transformation enablers and driving forces to integrate with medical, healthcare and emergency management research for effective epidemic prevention and control. This study aims to adapt complex systems in emergency management. Thus, a digital transformation-driven and systematic circulation framework is proposed in this study that can utilize the advantages of digital technologies to generate innovative and systematic governance.

Aiming at adapting complex systems in emergency management, a systematic circulation framework based on the interpretive research is proposed in this study that can utilize the advantages of digital technologies to generate innovative and systematic governance. The framework consists of four phases: (1) analysis of emergency management stages, (2) risk identification in the emergency management stages, (3) digital-enabled response model design for emergency management, and (4) strategy generation for digital emergency governance. A case study in China was illustrated in this study.

This paper examines the role those digital technologies can play in responding to pandemics and outlines a framework based on four phases of digital technologies for pandemic responses. After the phase-by-phase analysis, a digital technology-enabled emergency management framework, titled “Expected digital-enabled emergency management framework (EDEM framework)” was adapted and proposed. Moreover, the social risks of emergency management phases are identified. Then, three strategies for emergency governance and digital governance from the three perspectives, namely “Strengthening weaknesses for emergency response,” “Enhancing integration for collaborative governance,” and “Engaging foundations for emergency management” that the government can adopt them in the future, fight for public health emergency events.

The novel digital transformation-driven systematic circulation framework for public health risk response and governance was proposed. Meanwhile, an “Expected digital-enabled emergency management framework (EDEM model)” was also proposed to achieve a more effective empirical response for public health risk response and governance and contribute to studies about the government facing the COVID-19 pandemic effectively.

The purpose of this paper is to identify the salient risks borne by private firms and to investigate their effective risk response strategies in public-private partnership (PPP) low-cost housing (LCH) projects in Thailand.

The paper employs grounded theory and case study methodologies to extensively analyze ten private firms’ risks and their strategic risk mitigation. As a result, the matrix of imperative risks’ root causes and the area of the project life cycle most exposed to their impacts were proposed. This included the framework of the risk response strategy application.

The private firm's risk mitigation strategies depended on the salient risks’ impact and the private firms’ predictability and controllability of the risk outcome. This included the private firm's participating objectives and core business, decision maker's risk attitude, risk perception, experience of risk, and risk assessment skill, and the project life cycle phase of risk occurrence.

Under the same characteristics of the immature PPP market in developing countries, the contractors’ effective risk management framework can be used as a guideline to complement the contractors’ decision making on risk response strategy selection and resource allocation in the PPP project life cycle.

Despite working under the familiar environment of construction risk and generous payment method in PPP-LCH projects, only few contractors were successful. The examination of risks borne and effectively responded by the private sector increases the likelihood of the project success.

The objective of this research is to investigate the capabilities of the ChatGPT GPT-4 model, a form of artificial intelligence (AI), in comparison to human experts in the context of construction project risk management.

Employing a mixed-methods approach, the study draws a qualitative and quantitative comparison between 16 human risk management experts from Finnish construction companies and the ChatGPT AI model utilizing anonymous peer reviews. It focuses primarily on the areas of risk identification, analysis, and control.

ChatGPT has demonstrated a superior ability to generate comprehensive risk management plans, with its quantitative scores significantly surpassing the human average. Nonetheless, the AI model's strategies are found to lack practicality and specificity, areas where human expertise excels.

This study marks a significant advancement in construction project risk management research by conducting a pioneering blind-review study that assesses the capabilities of the advanced AI model, GPT-4, against those of human experts. Emphasizing the evolution from earlier GPT models, this research not only underscores the innovative application of ChatGPT-4 but also the critical role of anonymized peer evaluations in enhancing the objectivity of findings. It illuminates the synergistic potential of AI and human expertise, advocating for a collaborative model where AI serves as an augmentative tool, thereby optimizing human performance in identifying and managing risks.

Environmental risks (ERs) are critical to any highway construction project (HCP). One of the main contracting parties responsible for ERs is the contractor. Hence, it has been crucial to look into ways to control ERs in HCPs from the contractor’s perspective. This study aims to investigate how ERs can be managed in HCP in Sri Lanka.

A quantitative research approach with three rounds of Delphi was used. Statistical techniques were used to analyse and validate the ERs, the parties to whom the risks were to be allocated, and risk management measures identified from the empirical data collection.

The study reveals the 11 most significant ERs for HCP. Further, the most significant ERs in HCP were mainly found to be the responsibility of contractors in Sri Lanka. Twenty-four most appropriate risk response measures were determined; 13 were found to be common measures that could be used to manage two or more risks, while the remaining 11 were unique to specific risks.

Overall, this research determines the most significant ERs in HCP, the best risk allocation among the parties and appropriate risk-handling strategies and measures for each significant ERs. Additionally, the study addresses the demand for ERs management in HCP.

Risk response decisions (RRDs) are vital for project risk mitigation. Although past research has focused on RRDs for independent single projects, it has scarcely explored how to make RRDs for single projects in project portfolios (SPPPs). Consequently, this study aims to bridge the gap in extant literature by developing an integrated approach to select risk response strategies (RRSs) for SPPPs considering objective adjustments and project interdependencies (PIs).

An integrated quality function deployment (QFD) method was used throughout this study. More so, a balanced score card (BSC) and stratified-Z-numbers-full consistency method (SZFUCOM) was applied to identify SPPP success criteria (SP3SC) to determine their weights. In addition, a spherical fuzzy set-design structure matrix (SFDSM) was used to quantify the correlation between the risks and the relationship between the risks and the predecessor projects. Consequently, the relationships between the risks and SP3SC and RRSs were described by the spherical fuzzy set (SFS) and Z-numbers, respectively. Besides, the results are weaved into QFD to transform SP3SC into risks and then into RRSs, while a linear optimization model is used to obtain the optimal RRSs. Lastly, a construction project portfolio (PP) was used to test the veracity of the results to prove their validity.

The approach to RRDs for single projects is observed to be different from that of SPPPs. In addition, this study finds that project portfolio objective adjustments (PPOAs) and PIs have significant impacts on RRDs given that they influence the risk priorities of independent single projects and SPPPs. Moreover, the application of an integrated QFD effectively synthesized the results from the findings of this study, as well as enabled companies to determine robust RRSs. Finally, the consistency results of the SZFUCOM were better than those of the triangular fuzzy number-full consistency method.

The study innovatively explores the method of RRDs for SPPP, which has been ignored by past research. SP3SC highly compatible with PP success is determined. Z-numbers are first used to evaluate the effect of RRSs to enhance the robustness of RRDs. The study proposes a method of RRDs comprehensively considering PPOAs and PIs, which provides robust methodological guidance for SPPP managers to control risks.