Multiple-criteria decision-making for service quality selection based on Shapley COPRAS method under hesitant fuzzy sets

Hesitant fuzzy set (HFS) is employed to handle with the circumstances in which the decision experts hesitate among several values to assess an alternative, variable, etc. Recently, hesitant fuzzy multi-criteria decision making (MCDM) has received more concentration and different methods have been proposed to handle this issue. As the entropy and divergence measures play very important role in the study of uncertainty, therefore, in this paper, firstly, new entropy and divergence measures are proposed for HFSs. Further, this study extends an analytical decision making approach named as COPRAS, in an uncertain environment with hesitant fuzzy information and interdependent characteristics among the criteria. The proposed entropy measure is employed to compute criteria's weights in terms of Shapley function. Lastly, a numerical example of service quality decision making is demonstrated under hesitant fuzzy doctrine, which exhibits their advantages and feasibility. A comparative study with Shapley TOPSIS is presented to validate the proposed approach.