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Evaluation of the Global Competitiveness Index (GCI) by Multi-Criteria Decision-Making Methods Based on Intuitionistic Fuzzy Sets: Comparative Analysis
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Author(s): Nimet Yapıcı Pehlivan (Selçuk University, Turkey)and Yasemin Günter (Selçuk University, Turkey)
Copyright: 2022
Pages: 29
Source title:
Handbook of Research on Advances and Applications of Fuzzy Sets and Logic
Source Author(s)/Editor(s): Said Broumi (Laboratory of Information Processing, Faculty of Science Ben M’Sik, University Hassan II, Casablanca, Morocco & Regional Center for the Professions of Education and Training (CRMEF), Casablanca-Settat, Morocco)
DOI: 10.4018/978-1-7998-7979-4.ch016
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Abstract
Fuzzy set theory proposed by Zadeh is introduced to cope with the imprecision and uncertainty. Intuitionistic fuzzy sets (IFS) introduced by Atanassov are a generalization of fuzzy sets characterized by a membership function and a non-membership function. Various multi-criteria decision-making (MCDM) methods based on IFSs have been proposed. Global competitiveness index (GCI) provides information about the competitiveness of the countries based on data collected by the World Economic Forum in a report. Competitiveness of the country is the economic strength necessary for an economy to upgrade its economic prosperity and standard of living. In the report, three main criteria—factor, efficiency, and innovation—and related 12 sub-criteria are covered for the evaluation of the countries. In this chapter, MCDM methods of TOPSIS, WASPAS, and COPRAS based on IFSs are applied to data obtained from the GCI report, and ranking of the countries is obtained to investigate relationship.
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