A novel picture fuzzy CRITIC & REGIME methodology: Wearable health technology application

Abstract

Picture fuzzy sets (PFSs) are one of the most promising extensions of ordinary fuzzy sets with three parameters, namely positive membership, neutral membership, and negative membership, for defining the membership status of an element to a set. CRiteria Importance Through Intercriteria Correlation (CRITIC) & REGIME methods are recently developed multi criteria decision making (MCDM) methods for calculating the criteria weights and ranking alternatives, respectively. CRITIC method determines the criteria weights by using the values in the decision matrix. REGIME method is a compensatory MCDM method employing superiority and guide indices, superiority identifier and impacts, and REGIME matrices. In this paper, an integrated CRITIC & REGIME methodology is developed for the first time by using single-valued PFSs in order to use the advantage of PFSs in handling ambiguity and impreciseness. The main contribution of our study is to demonstrate theoretically and practically how to transform superiority and guide indices, superiority identifier and impacts, and REGIME matrices to the PF environment. A new interval valued Relative Magnitude Index scale and an original Percentile Rank under Vagueness function have been developed. The developed methodology is applied to the selection problem of wearable health technology (WHT). Comparative and sensitivity analyses are presented. These analyses show that CRITIC & REGIME methodology produces very effective and valid results, and unlike the other methods, it shows slight ranking differences due to the statistical-based calculations it contains.