A neutrosophic game theory approach for multi-objective telecom market share problem

Abstract

In the fast-evolving real world, multi-objective decision-oriented (MODO) problems are commonplace, where game theory plays a vital role. One example of a MODO problem that requires strategic decision-making to figure out a balance between conflicting objectives in a competitive market context is the telecom market share (TMS) problem. The proposed study focuses on the TMS problem, where two stakeholders, Player I representing the telecom company and Player II as the investor, aim to maximize profits and minimize risks. To address uncertainties in proposed problems, the parameters of the multi-objective telecom market share (MOTMS) problem are transformed into single-valued neutrosophic trapezoidal fuzzy numbers (SVNTFNs). In the proposed study, two different methodologies have been proposed and applied to solve the MOTMS problem with parameters of SVNTFNs. The first involves constructing linear programming problems (LPPs) and applying the Nash bargaining approach to balance conflicting interests in the telecom share market. The second uses the single-valued neutrosophic fuzzy goal programming (SVNFGP) approach. In the case of the TMS, the proposed approaches give decision-makers a clear method for determining a compromise between maximizing profits for telecom companies and minimizing risks for investors