
PurposeThe 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.Design/methodology/approachThe 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.FindingsThe 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.Practical implicationsThis 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.Originality/valuePrevious 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.
Credibility theory, Fuzzy chance constrained programming, International construction projects, Risk response strategies, Risk preference, 650
Credibility theory, Fuzzy chance constrained programming, International construction projects, Risk response strategies, Risk preference, 650
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 15 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
