Purpose: Construction projects involve with various risks during all phases of project lifecycle. Failure mode and effective analysis (FMEA) is a useful tool for identifying and eliminating possible risk of failure modes (FMs) and improving the reliability and safety of systems in a broad range of industries. The traditional FMEA method applies risk priority number method (RPN) to calculate risk of FMs. RPN method cannot consider the direct and indirect interdependencies between the FMs and is not appropriate for complex system with numerous components. The purpose of this study is to propose an approach to consider interdependencies between FMs and also using fuzzy theory to consider uncertainties in experts' judgments.Design/methodology/approach: The proposed approach consist of three stages: the first stage of hybrid model used fuzzy FMEA method to identify the failure mode risks and derive the RPN values. The second stage applied Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL) method to determine the interdependencies between the FMs which are defined through fuzzy FMEA. Then, analytic network process (ANP) is applied in the third stage to calculate the weights of FMs based on the interdependencies that are generated through FDEMATEL method. Finally, weight of FMs through fuzzy FMEA and FDEMATEL–ANP are multiplied to generate the final weights for prioritization. Afterward, a case study for a commercial building project is introduced to illustrate proficiency of model.Findings: The results showed that the suggested approach could reveal the important FMs and specify the interdependencies between them successfully. Overall, the suggested model can be considered as an efficient hybrid FMEA approach for risk prioritization.Originality/value: The originality of approach comes from its ability to consider interdependencies between FMs and uncertainties of experts' judgments.

Construction projects always deal with different types of risks such as financial problems, legal factors, availability of resources and other issues during the project lifecycle. According to the type, size and complexity of the project, the number and intensity of risks could be different and many projects cannot reach the project goals due to exposure to multiple risks. This study aims to propose a hybrid DEMATEL-ANP model for risk prioritization in construction projects and the originality of the work comes from its ability to consider interdependencies between risk factors. The first stage of model applied Delphi method to use experts’ judgments for risk identification. The second stage used Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to define the interdependencies’ relative intensity among the risks. Afterwards, Analytic Network Process (ANP) method is used in the third stage to assess the relative importance of the risk factors to define risk priorities in project. A case study of oil pipeline project is reported to indicate efficiency and performance of the proposed model. The results indicated that the proposed methodology could successfully reveal the important risk factors and define the interdependencies between them in the case study. On the whole, the proposed methodology can be considered as an efficient approach for risk assessment in construction projects.

The majority of countries attempting to switch from conventional energy sources to renewable energy sources have decided to make significant investments in these projects. This study aims to identify critical risks for renewable energy (RE) investment projects using a novel hybrid approach based on interval type 2 hesitant fuzzy sets (IT2HFS) and alpha level sets. The hybrid model integrates interval type 2 hesitant fuzzy (IT2HF) DEMATEL-based analytic network processing (DANP) with qualitatively flexible multiple criteria (QUALIFLEX). In the first stage, the dimensions and criteria for RE investment risks are defined. In the second stage, the importance levels of these attributes are assessed. Finally, the risk awareness levels of strong, average, and weak investors are graded using the IT2HF-QUALIFLEX. The results indicate that the cost of the investment and technological maturity are the substantial criteria for RE investment projects. Also, the sensitivity analysis is conducted, and the stability of the results for the proposed approach is verified. Eventually, five different scenarios are designed, and the results are interpreted accordingly. The findings of this study will be valuable to investors, enterprises, and authorities involved in evaluating their investment in RE projects.