Fine–kinney-based occupational risk assessment using fuzzy best and worst method (f-bwm) and fuzzy mairca

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Abstract

The best-worst method (BWM) proposed by Rezaei (Omega 53:49–57, [1]) is an MCDM method used to achieve the weights of the criteria by making fewer pairwise comparisons and using more consistent decision matrices. In this chapter, instead of crisp numbers, triangular fuzzy numbers that reflect the uncertainty well in real-world problems are used in integration with the BWM method (Guo and Zhao in Knowl Based Syst 121:23–31, [2]) in determining factor weights. Using the fuzzy best and worst method (F-BWM), a model based on Fine–Kinney occupational health and safety risk assessment method was developed for the first time in the literature. Three parameters of Fine–Kinney method are weighted by the mathematical models of F-BWM. Then, the risks are prioritized by fuzzy multi-attribute ideal real comparative analysis (F-MAIRCA). A case study was conducted to demonstrate the feasibility of the approach, and besides this case study, a comparative study was also conducted to test the validity of the proposed approach. This approach led to the conclusion that Fine–Kinney’s method, BWM, MAIRCA, and triangular fuzzy sets make the risk decision-making process more dynamic, taking into account the benefits of these methods individually or in integration.

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Gul, M., Mete, S., Serin, F., & Celik, E. (2021). Fine–kinney-based occupational risk assessment using fuzzy best and worst method (f-bwm) and fuzzy mairca. In Studies in Fuzziness and Soft Computing (Vol. 398, pp. 13–30). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-52148-6_2

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