Spherical fuzzy analytic hierarchy process and linear assignment model based MCGDM method with its application in ranking of states for their business climate

Abstract

Ranking of the states for business climate is often done by survey analysis and hence prejudiced by untrustworthy and instable responses of the participants. In the present study, we integrate spherical fuzzy set (SFS) and linear assignment model (LAM) with analytic hierarchy process (AHP) to develop a multi criteria group decision making (MCGDM) method to rank Indian states for their business climate and potential index. The proposed MCGDM method is developed using state investment potential index (SIPI) published by the National Council of Applied Economic Research (NCAER), New Delhi to analyse the 'ease of doing business' aspects of various states based on six parameters. We take these six parameters, sub parameters as criteria and sub criteria in proposed MCGDM method and find their global weight using AHP method. Advantages of the proposed method are that it uses SFSs which are more efficient than other extensions of fuzzy sets in handling non-determinacy, and applies LAM to avoid subjectivity in the preferences of decision makers. We also do the sensitivity analysis of the ranking by changing the weights of the criteria and sub criteria to confirm the robustness of the proposed MCGDM method.