Evaluation of the Global Competitiveness Index (GCI) by Multi-Criteria Decision-Making Methods Based on Intuitionistic Fuzzy Sets: Comparative Analysis

Introduction

Multiple criteria decision making (MCDM) is the most well-known branch of decision making. In the MCDM problems, an appropriate alternative among a finite number of feasible alternatives in the presence of multiple, generally conflicting criteria are chosen. MCDM problems are classified into two categories: multi-objective decision making (MODM) and multi-attribute decision making (MADM), depends on the domain of the alternatives, i.e. continuous or discrete. In the MADM, problems with discrete domain whose number of alternatives has been predetermined in order to select/prioritize/rank a finite number of alternatives are handled. On the other hand, problems with decision variables that are determined in a continuous/integer domain with either an infinitive or a large number of alternatives to satisfy the decision maker’s constraints and preference priorities are considered in the MODM (Rao, 2013). A typical MCDM method includes i) determining the number of criteria for the problem, ii) collecting the suitable data/information in which the preferences of DMs (i.e., construction of the preferences), iii) constructing a set of possible alternatives for attaining the goal (i.e., evaluation of the alternatives), iv) choosing a proper method for evaluating and ranking the alternatives (i.e., determination of the top alternative) (Tzeng and Huang, 2011). Various methods have been proposed in the field of MCDM, such as Analytic Hierarchy Process-AHP (Saaty, 1980), Technique for Order of Preference by Similarity to Ideal Solution-TOPSIS (Hwang and Yoon, 1981), COmplex PRoportional ASsessment-COPRAS (Zavadskas et al., 1994), VlseKriijumsko Optimizacijo I Kompromisno Resenje-VIKOR (Opricovic, 1998), Multi-Objective Optimization Method by Ratio Analysis-MOORA (Brauers and Zavadskas, 2006), MultiMOORA (Brauers and Zavadskas, 2010), Additive Ratio ASsessment-ARAS (Zavadskas and Turskis, 2010), Weighted Aggregated Sum Product ASsessment-WASPAS (Zavadskas et al., 2012), Evaluation based on Distance from Average Solution-EDAS (Ghorabaee et al., 2015), COmbinative Distance-based ASsessment-CODAS (Ghorabaee et al., 2016), etc.

Fuzzy set theory (FST) which was first introduced by Zadeh (1965) is a valuable tool to strengthen the comprehensiveness and reasonableness of the decision making process. Since the introduction of FST, some extensions have been developed, such as type-2 fuzzy sets, interval type-2 fuzzy sets, type-n fuzzy sets, intuitionistic fuzzy sets, interval-valued intuitionistic fuzzy sets, neutrosophic fuzzy sets, and hesitant fuzzy sets. Judgments and preferences of decision makers are affected by uncertainty, therefore the use of precise and crisp numbers in linguistic evaluations may not always be suitable for MCDM methods. Then, various MCDM methods based on fuzzy set theory and its extensions or generalizations have been proposed by several authors for selection, ordering and classification of the alternatives. In the literature, FMCDM methods have been comprehensively studied by various researchers and applied to different fields. Among them, intuitionistic fuzzy sets (IFS) based MCDM methods have attracted great attention by researchers and many studies have been conducted.

The Global Competitiveness Index (GCI) evaluates the performance of about 140 countries worldwide considering 12 pillars of competitiveness. The data handled in the evaluation are compiled and/or collected annually by the World Economic Forum. The GCI aims to measure national competitiveness defined as the set of institutions, policies and factors which indicates the productivity level of the countries. It helps policymakers to understand the complex and multifaceted nature of the development challenge and to set better policies based on public-private cooperation, as well as to act in a way that restores confidence in the possibilities for continued economic progress (GCI Report 2017-2018).