A Novel Risk Assessment Approach Using a Hybrid Method Based On Fine–Kinney and Extended MCDM Methods Under Interval-Valued Intuitionistic Fuzzy Environment

Sukran Seker ()
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Sukran Seker: Department of Industrial Engineering, Yildiz Technical University, Istanbul 34349, Turkey

International Journal of Information Technology & Decision Making (IJITDM), 2022, vol. 21, issue 05, 1591-1616

Abstract: Subway construction is one of the most dangerous industries due to the highest number of occupational accidents. Risk assessment is an effective tool to evaluate risk factors and reduce the number of accidents in such industries. In this study, a novel risk assessment method is proposed using three-stage hybrid method based on Fine–Kinney risk assessment method to evaluate the risk factors encountered in subway constructions and take necessary precautions against possible accidents. Accordingly, in order to deal with the drawbacks of the Fine–Kinney risk assessment method, a novel hybrid approach, which includes Fine–Kinney, analytic hierarchy process (AHP), and multiple multi-objective optimization by ratio analysis (MULTIMOORA) methods, is suggested under interval-valued intuitionistic fuzzy (IVIF) environment to handle uncertainty in the risk evaluation. To demonstrate the applicability and benefits of the proposed hybrid risk assessment method, a real-life case study in subway construction is presented. To determine the weights of three risk parameters in Fine–Kinney method and the risk priority of occupational risk factors in subway construction, IVIF-AHP and IVIF-MULTIMOORA methods are performed, respectively. Then, a sensitivity analysis is applied to confirm the robustness of the proposed method. Finally, a comparative analysis is carried out to check the consistency of the ranking of risk factors obtained in proposed method. The results prove that the proposed risk assessment method generates consistent and reliable results.

Keywords: Fine–Kinney; AHP; MULTIMOORA; IVIF sets (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S0219622022500250

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