Abstract
PurposeThe paper aims to propose a practical model for market segment selection and evaluation. The paper carries out a technique of order preference similarity to the ideal solution (TOPSIS) approach to make an operation systematic dealing with multi-criteria decision- making problem.Design/methodology/approachIntroducing a multi-criteria decision-making problem based on TOPSIS approach. A new entropy and new similarity measure under neutrosopic environment are proposed to evaluate the weights of criteria and the relative closeness coefficient in TOPSIS model.FindingsThe outcomes show that the TOPSIS model based on new entropy and similarity measure is effective for evaluation and selection market segment. Profitability, growth of the market, the likelihood of sustainable differential advantages are the most important insights of criteria.Originality/valueThis paper put forward an effective multi-criteria decision-making dealing with uncertain information.
Highlights
The selection and evaluation of market segments boost the competitive advantage of companies
Several popular multiple criteria decisionmaking (MCDM) approaches using fuzzy sets, intuitionistic fuzzy sets and/or neutrosophic sets have been proposed in literature to solve the market segment selection and evaluation problems such as a technique of order preference similarity to the ideal solution (TOPSIS), analytic hierarchy process (AHP), quality function deployment (QFD) (Dat et al, 2015; Aghdaie, 2015; Ghorabaee et al, 2017; Tian et al, 2018)
This study proposes a new entropy and new similarity measures for neutrosophic sets to calculate the importance weight of criteria in MCDM approach
Summary
The selection and evaluation of market segments boost the competitive advantage of companies. Several popular MCDM approaches using fuzzy sets, intuitionistic fuzzy sets and/or neutrosophic sets have been proposed in literature to solve the market segment selection and evaluation problems such as a technique of order preference similarity to the ideal solution (TOPSIS), analytic hierarchy process (AHP), quality function deployment (QFD) (Dat et al, 2015; Aghdaie, 2015; Ghorabaee et al, 2017; Tian et al, 2018). In other research, Aghdaie (2015) combined AHP with TOPSIS for selecting target market with three cluster criteria, including related segments, financial and economic, technological aspects For this purpose, Ghorabaee et al (2017) approached the generalization of combinative distance-based assessment (CODAS) utilizing trapezoidal fuzzy numbers. Weakness of fuzzy AHP is time-consuming due to a large number of pairwise comparison be employed To overcome this problem, this study proposes a new entropy and new similarity measures for neutrosophic sets to calculate the importance weight of criteria in MCDM approach. A new entropy and similarity measure on the neutrosophic set This section recalls some concepts of a single-valued neutrosophic set (SVNS), which was introduced by Wang et al (2010) as well as introduce a new similarity and entropy measure of am SVNS
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