ASSESSMENT OF THE RENEWABLE ENERGY EFFICIENCY OF THE G20 COUNTRIES BY BALANCED PERFORMANCE WEIGHTS AND DATA ENVELOPMENT ANALYSIS
Abstract
Renewable
energy has been a too much used term for sustainable development and
environmental studies in recent years. The aim of this study is to reveal the
renewable energy performance of the G20 countries by means of data envelopment
analysis (DEA) and balanced performance weights. DEA is a nonparametric and
powerful technique which is used for performance measurement. Determining the
input and output weights in DEA is an important step that can greatly change
the result of the study. Several methods have been developed to determine the
weights. In this study, balanced performance weights method, that is developed
by Alp (2016) and calculated by using the correlations between inputs and
outputs, and the classical CCR method are used and the results are compared. In
the analysis, energy intensity and labor force are used as input, and per
capita national income, CO2 emission amount and the percentage of electricity
generated by renewable energy sources in total electricity generated are used
as output. According to the CCR results 7 countries are effective, and 1
country is effective in the result of analysis using balanced weights
calculated with the help of correlations. It has been observed that the results
of the analysis made with the balanced weights model give more discriminating results
than the classical model.
References
- Alp, İ. (2016). Another way to determine weights of balanced performance evaluations. Dumlupi-nar University Journal of Social Science, ICEBSS Özel Sayısı, 151-161.
- Banker, R.D., Charnes, A., Cooper, W.W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis, Management Science, 30, 1078– 1092.
- Chien, T., Hu, J.L. (2007). Renewable energy and macroeconomic efficiency of OECD and non-OECD economies. Energy Policy, 35(7), 3606-3615.
- Charnes, A., Cooper, W.W., Rhodes, E. (1978). Measuring the efficiency of decision making units, European Journal of Operational Research, 2, 429–44.
- Dünya ve Türkiye Enerjive Tabii Kaynaklar Görünümü. (2017). Erişim Adresi http://www.enerji.gov.tr/Resources/Sites/1/Pages/Sayi_15/mobile/index.html#p=1.
- IEO2017. (2017). Erişim Adresi https://www.eia.gov/outlooks/ieo/pdf/0484(2017).pdf.
- IRENA. (2017). REthinking Energy 2017. Erişim Adresi http://www.irena.org/documentdownloads/publications/irena_rethinking_energy_2017.pdf.
- Menegaki, A.N. (2013). Growth and renewable energy in Europe: Benchmarking with data enve-lopment analysis, Renewable Energy, 60, 363-369.
- Sözen, A., Alp, İ., Kılınç, C. (2012). Efficiency Assensment of the Hydro-power in Turkey by Using Data Envelopment Analysis. Renewable Energy, 46, 192-202.
- Wang, H. (2015). A generalized MCDA–DEA (multi-criterion decision analysis–data envelopment analysis) approach to construct slacks-based composite indicator. Energy, 80, 114-122.
- Woo, C., Chung, Y., Chun, D., Seo, H., Hong, S. (2015). The static and dynamic environmental effici-ency of renewable energy: A Malmquist index analysis of OECD countries. Renewable and Sustainable Energy Reviews, 47, 367-376.
- Yenilenebilir Enerji Müdürlüğü. (2017). Yenilenebilir Enerji Erişim Adresi http://www.eie.gov.tr/yenilenebilir.aspx .
- Zhou, P., Ang, B.W., Han, J.Y. (2010) Total factor carbon emission performance: A Malmquist index analysis. Energy Economics, 32(1), 194-201.
G20 ÜLKELERİNİN YENİLENEBİLİR ENERJİ ETKİNLİĞİNİN DENGELİ PERFORMANS AĞIRLIKLARI VE VERİ ZARFLAMA ANALİZİ İLE DEĞERLENDİRİLMESİ
Abstract
Yenilenebilir
enerji son yıllarda sürdürülebilir kalkınma ve çevre ile ilgili çalışmalarda
çok fazla kullanılan bir terim olmuştur. Bu çalışmanın amacı G20 ülkelerinin
yenilenebilir enerji performansını veri zarflama analizi (VZA) ve dengeli
performans ağırlıkları yöntemiyle ortaya koymaktır. VZA performans ölçümü için
kullanılan parametrik olmayan ve güçlü bir tekniktir. VZA’da girdi ve çıktı
ağırlıklarının belirlenmesi çalışmanın sonucunu büyük ölçüde değiştirebilecek
önemli bir aşamadır. Ağırlıkların belirlenmesinde çeşitli yöntemler
geliştirilmiştir. Bu çalışmada klasik CCR yöntemi ve Alp (2016) tarafından
geliştirilen girdi ve çıktılar arasındaki korelasyonlar kullanılarak hesaplanan
dengeli performans ağırlıkları yöntemi kullanılmış ve sonuçlar
karşılaştırılmıştır. Analizde girdi olarak enerji yoğunluğu ve işgücü, çıktı
olarak kişi başı milli gelir, CO2 emisyon miktarı ve yenilenebilir
enerji kaynakları tarafından üretilen elektriğin toplam üretilen elektrik
miktarı içindeki yüzdesi kullanılmıştır. CCR sonuçlarında 7 ülke, korelasyonlar
yardımıyla hesaplanan dengeli ağırlıklar kullanılarak yapılan analiz sonucunda
ise 1 ülke etkin olmuştur. Dengeli ağırlıklar modeliyle yapılan analiz
sonuçlarının klasik modele göre daha ayırıcı sonuçlar verdiği gözlemlenmiştir.
References
- Alp, İ. (2016). Another way to determine weights of balanced performance evaluations. Dumlupi-nar University Journal of Social Science, ICEBSS Özel Sayısı, 151-161.
- Banker, R.D., Charnes, A., Cooper, W.W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis, Management Science, 30, 1078– 1092.
- Chien, T., Hu, J.L. (2007). Renewable energy and macroeconomic efficiency of OECD and non-OECD economies. Energy Policy, 35(7), 3606-3615.
- Charnes, A., Cooper, W.W., Rhodes, E. (1978). Measuring the efficiency of decision making units, European Journal of Operational Research, 2, 429–44.
- Dünya ve Türkiye Enerjive Tabii Kaynaklar Görünümü. (2017). Erişim Adresi http://www.enerji.gov.tr/Resources/Sites/1/Pages/Sayi_15/mobile/index.html#p=1.
- IEO2017. (2017). Erişim Adresi https://www.eia.gov/outlooks/ieo/pdf/0484(2017).pdf.
- IRENA. (2017). REthinking Energy 2017. Erişim Adresi http://www.irena.org/documentdownloads/publications/irena_rethinking_energy_2017.pdf.
- Menegaki, A.N. (2013). Growth and renewable energy in Europe: Benchmarking with data enve-lopment analysis, Renewable Energy, 60, 363-369.
- Sözen, A., Alp, İ., Kılınç, C. (2012). Efficiency Assensment of the Hydro-power in Turkey by Using Data Envelopment Analysis. Renewable Energy, 46, 192-202.
- Wang, H. (2015). A generalized MCDA–DEA (multi-criterion decision analysis–data envelopment analysis) approach to construct slacks-based composite indicator. Energy, 80, 114-122.
- Woo, C., Chung, Y., Chun, D., Seo, H., Hong, S. (2015). The static and dynamic environmental effici-ency of renewable energy: A Malmquist index analysis of OECD countries. Renewable and Sustainable Energy Reviews, 47, 367-376.
- Yenilenebilir Enerji Müdürlüğü. (2017). Yenilenebilir Enerji Erişim Adresi http://www.eie.gov.tr/yenilenebilir.aspx .
- Zhou, P., Ang, B.W., Han, J.Y. (2010) Total factor carbon emission performance: A Malmquist index analysis. Energy Economics, 32(1), 194-201.
Details
| Journal Section | Articles |
|---|---|
| Authors | |
| Publication Date | January 16, 2018 |
| Published in Issue | Year 2018 18. EYI Special Issue |
Cited By
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https://doi.org/10.37094/adyujsci.755048
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Journal of Polytechnic
Berk Erbil YAĞCI
https://doi.org/10.2339/politeknik.859790
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