Intuitionistic fuzzy divergence measure-based ELECTRE method for performance of cellular mobile telephone service providers

Abstract

In India, Telecom sector has been enduring a massive growth for over two and half decades in the bandwidth, preference of services and depth of penetration in urban, semi-urban and rural areas. Exploring the service providers or selecting the best cellular mobile telephone service providers (CMTSPs/TSPs) according to operational performance parameter can help to achieve the goal of telecom service provider selection (TSPS). Here, this assessment generally comprises various TSPs alternatives and different operational performance criteria; therefore, TSPS could be considered as a multi-criteria decision-making (MCDM) problem. The analytical data have been taken from the Telecom Regulatory Authority of India (TRAI), Jan–Mar 2017. Most of the data vary from 1 month to another. Thus, these small ranges of variation in the data are incorporated with the intuitionistic fuzzy numbers (IFNs). In this paper, we develop an outranking method, intuitionistic fuzzy ELECTRE (IF-ELECTRE), for MCDM problems. Proposed method is based on divergence measure, operators of IFNs, some modifications of classical ELECTRE method. In the MCDM, the criterion weight determination is a vital issue for the accuracy of evaluation results. In the process of calculation of criterion weight, concordance and discordance values, we propose new Jensen–Shannon divergence (JS-divergence) for IFSs to overcome the shortcoming of the existing ones and demonstrate different elegant properties of the proposed one. Since the uncertainty is an inevitable feature of MCDM problems, the proposed method can be a valuable tool for decision-making in an uncertain atmosphere to determine the partial-preference outranking order. To express the strength and reasonableness of the proposed method in the real-world MCDM problems, a TSPS problem is implemented. Using the proposed framework, a decision expert can make a strategy to improve the performance by benchmarking operational parameters. Finally, a comparison is discussed between the results of the proposed method and the existing ones for validating the proposed method. This analysis shows that the proposed method is efficient and well consistent with the other methods.