Life Insurance Selection Using Proportional Spherical Fuzzy MEREC & MARCOS Methodology

Abstract

One of the recent fuzzy set extensions, proportional spherical fuzzy sets (PSFSs), is characterized by proportions between membership, non-membership, and hesitancy degrees of an element in order to identify membership, non-membership, and hesitancy degrees with more accuracy and sensitivity. PSFSs are utilized to provide an effective technique to determine the mentioned degrees with more decimal digits and to enable the expert to assign more stable values. In this paper, PSFSs are used to extend the MEREC & MARCOS methodology for the evaluation of insurance policies under vagueness and imprecision. Besides, sensitivity analysis has been conducted on the weights of the criteria and the weights of the decision makers and a comparative analysis has been realized with the SF-CRITIC & TOPSIS, SF-CRITIC & CODAS and SF-CRITIC & WASPAS methodologies. The validity and robustness of the developed methodology are demonstrated by these sensitivity and comparative analyses.