Multicriteria and Statistical Approach to Support the Outranking Analysis of the OECD Countries

Abstract

Since 2011, the Organization for Economic Co-operation and Development (OECD) has maintained the Better Life Initiative, which proposes a quality-of-life index called Better Life Index (BLI), consisting of 11 dimensions. This paper presents a multivariate analysis approach that aims to reduce the BLI dimensions. For this purpose, we applied factor extraction by main components to reorganize BLI variables into three dimensions (factors): dimension 1 - personal development and support factors; dimension 2 - financial balance; and dimension 3 - insecurity with the labor market. These three factors were used as criteria for the PROMETHEE-SAPEVO-M1 multicriteria method. We applied the methodology to data from 38 countries (35 from OECD and 3 non-OECD economies). As a result, we verified that Denmark, Iceland and Switzerland stood out as the countries with the best performances after the proposed analysis. Among the 38 countries evaluated, 19 showed positive flows, allowing the distribution into two well-defined groups. Also, adopting this hybrid methodology of multivariate analysis and multicriteria was advantageous because it reduced the evaluation criteria that the decision-maker needs to evaluate. We compared the results obtained by PROMETHEE-SAPEVO-M1 with the <i>ViseKriterijumska Optimizacija</i> <inline-formula> <tex-math notation="LaTeX">$i$ </tex-math></inline-formula> <i>Kompromisno Resenje</i> (VIKOR) and <i>Elimination Et Choix Traduisant la Realit&#x00E9;</i>- Multicriteria Ordinal (ELECTRE-MOr) methods, with remarkably similar results. The main contribution of this study is to provide a hybrid methodology composed of a statistical structuring approach (factor analysis) in a problem with multiple conflicting criteria. After all, the approach proposed in this article represented a 94&#x0025; reduction in the decision maker&#x2019;s cognitive effort.