Evaluation of sustainable energy performance for OECD countries
Energy Sources, Part B: Economics, Planning and Policy, ISSN: 1556-7257, Vol: 16, Issue: 6, Page: 491-514
2021
- 21Citations
- 19Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
This study aims to evaluate the sustainable energy performance of 36 OECD (Organization for Economic Cooperation and Development) countries. The sustainable energy performance evaluation of the countries was made with linear programming-based “DEA (Data Envelopment Analysis)” and multi-criteria decision-making-based “PROMETHEE (The Preference Ranking Organization Method for Enrichment Evaluation)”. Spearman Correlation Coefficients were calculated for the relationships between the rankings obtained from all methods. According to the Spearman’s Rank Correlation Coefficients (R) calculated for the performance rankings of OECD countries, the relations between all rankings of OECD countries were positive moderate (R = +0.6952) and positive high (R = +0.7959; R = +0.8919). The novelty of this article is to verify that DEA models and PROMETHEE technique, which are different from each other in terms of structure, algorithms, and basic purposes, can be used as an alternative performance evaluation tool.
Bibliographic Details
Informa UK Limited
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