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The long-run sustainability of the European Union countries: Assessing the Europe 2020 strategy through a fuzzy goal programming model

Authors :
Cinzia Colapinto
Davide La Torre
Aymeric Vié
Danilo Liuzzi
Vié, Aymeric
Colapinto, Cinzia
La Torre, Davide
Liuzzi, Danilo
Publication Year :
2019

Abstract

Purpose Energy and environmental concerns have gained a significant role in public policy agenda as well as in energy economics literature. As policies often rely on imprecise information on data and goals, fuzzy goal programming (FGP) modeling is a relevant choice to evaluate multi-criteria sustainability. This technique is suitable for the analysis of the Europe 2020 strategy plan dealing with several possibly conflicting objectives in economy, environment, energy and employment. The paper aims to discuss these issues. Design/methodology/approach The paper presents a FGP model for sustainable implementations for all European Union (EU) countries with respect to Europe 2020 policy goals and provides insights for decision makers to better satisfy conflicting criteria by suggesting optimal allocations of workers in several economic sectors. Findings The analysis shows an overall great performance of European Union countries in the environmental and social criteria and outlines the needs for significant additional policy measures to reduce energy consumption while increasing the economic output. Comparing the performance of countries within the European Union between those who adopted the euro and those who maintained national currencies shows that Euro countries tend to perform worse in terms of Europe 2020 sustainability, opening opportunities for further research to better investigate on the causes and determinants of these differences. Originality/value The paper presents a conceptual model of sustainable development that improves understanding of the concept and reconciles highly competing policy objectives in a common framework. Applying this model to all European Union countries offers both comparison and policy recommendations at a large new scale.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....e9b0f49dc10a691b49959d124f1686b1