This paper proposes a novel approach to evaluate European countries on Sustainable Development Goals (SDG) by means of Hierarchical Stochastic Multicriteria Acceptability Analysis (HSMAA). HSMAA produces rankings with Monte Carlo generation of weights, overcoming the need to choose one specific set of weights. The main contribution of this paper lies in the possibility of quantifying the probability by which each country receives a given ranking. Furthermore, HSMAA allows to take into account the hierarchical nature of SDG measurement given that each of the 17 Goals also consists of several indicators. Our results show that Denmark outperforms other European countries, while lower levels of performance are observed in Romania and Bulgaria. In between bottom and top performers, we also find that many countries’ rankings vary widely by the chosen set of weights, exemplifying the need to rank countries based on multiple weightings and to quantify the probabilities of each ranking.

Sustainable Development in Europe: A Multicriteria Decision Analysis

Resce G.
;
2020-01-01

Abstract

This paper proposes a novel approach to evaluate European countries on Sustainable Development Goals (SDG) by means of Hierarchical Stochastic Multicriteria Acceptability Analysis (HSMAA). HSMAA produces rankings with Monte Carlo generation of weights, overcoming the need to choose one specific set of weights. The main contribution of this paper lies in the possibility of quantifying the probability by which each country receives a given ranking. Furthermore, HSMAA allows to take into account the hierarchical nature of SDG measurement given that each of the 17 Goals also consists of several indicators. Our results show that Denmark outperforms other European countries, while lower levels of performance are observed in Romania and Bulgaria. In between bottom and top performers, we also find that many countries’ rankings vary widely by the chosen set of weights, exemplifying the need to rank countries based on multiple weightings and to quantify the probabilities of each ranking.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11695/94786
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