Abstract
The European Union (EU) energy policy for sustainable development has been the topic of continuous debate, research, and analysis, which frequently focused on objectives and the evaluation of quantitative and qualitative performance. Different approaches can be used for the assessment of sustainable development goals. The authors of the article conducted a literature review of relevant research papers dated 2016–2020. The most common are quantitative methods based on hard data. Some qualitative studies based on soft data are also available but rare. This article proposes hybrid Rough Set Data Envelopment Analysis (DEA) and Rough Set Network DEA models that integrate both approaches. Also, the models allow the inclusion of uncertainty in the underlying data. The article uses hard data of the International Energy Agency (IEA) and the results of the EU survey regarding the influence of the socio-economic environment on CO2 emissions in EU countries. The authors demonstrate that multifaceted and objective assessment is possible by merging concepts from the set theory and operational research.
Highlights
Energy is the main driver for economic growth; it is the leading cause of CO2 emissions [1]
The article offers to use hybrid models, i.e., Rough Set Data Envelopment Analysis (DEA) and Rough Set Network DEA, to deal with uncertainty in the underlying data used for assessing the performance of sustainable development goals in European Union (EU) countries
Data Envelopment Analysis (DEA) is a linear programming technique that allows evaluating the relative efficiency of Decision-Making Units (DMUs)
Summary
Energy is the main driver for economic growth; it is the leading cause of CO2 emissions [1]. It is important to compare the progress of countries considering many aspects of sustainable energy and development as well as find ways to aggregate the final assessment [11,12,13]. The success of a policy to reduce CO2 emissions depends on economic prosperity measured by GDP per capita and on priorities, set directly and indirectly by the public The significance of both factors is evident in the midst of unprecedented challenges faced by societies, such as the expected recession and global changes resulting from the COVID-19 pandemic. The article offers to use hybrid models, i.e., Rough Set Data Envelopment Analysis (DEA) and Rough Set Network DEA, to deal with uncertainty in the underlying data used for assessing the performance of sustainable development goals in EU countries.
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