734
Views
12
CrossRef citations to date
0
Altmetric
Research Article

Evaluation of sustainable energy performance for OECD countries

, , & ORCID Icon

References

  • Abdullah, L., W. Chan, and A. Afshari. 2019. Application of PROMETHEE method for green supplier selection: A comparative result based on preference functions. Journal of Industrial Engineering International 15 (2):271–85. doi:10.1007/s40092-018-0289-z.
  • Aceleanu, M. I., A. C. Șerban, D. M. Pociovălișteanu, and G. C. Dimian. 2017. Renewable energy: A way for a sustainable development in romania. Energy Sources, Part B: Economics, Planning, and Policy 12 (11):958–63. doi:10.1080/15567249.2017.1328621.
  • Adedoyin, F. F., M. I. Gumede, F. V. Bekun, M. U. Etokakpan, and D. Balsalobre-lorente. 2020. Modelling coal rent, economic growth and CO2 emissions: Does regulatory quality matter in BRICS economies. Science of the Total Environment 710:136284. doi:10.1016/j.scitotenv.2019.136284.
  • Akgobek, O., I. Nisanci, S. Kaya, and T. Eren. 2015. Veri zarflama analizi yaklaşimini kullanarak bir eğitim kurumunun şubelerinin performanslarini ölçme. Social Sciences Research Journal 4 (3):43–54.
  • Aladag, Z., A. Alkan, E. Guler, and Y. Ozdin. 2018. Akademik birimlerin veri zarflama analizi ve PROMETHEE yöntemleri ile performans değerlendirmesi: Kocaeli üniversitesi örneği. Erciyes University Journal of Institute of Science and Technology 34 (1):1–13. https://dergipark.org.tr/en/pub/erciyesfen/issue/37078/406003.
  • Alidrisi, H., and B. O. Al-Sasi. 2017. Utilization of energy sources by G20 countries: A TOPSIS-BASED approach. Energy Sources, Part B: Economics, Planning, and Policy 12 (11):964–70. doi:10.1080/15567249.2017.1336812.
  • Alola, A. A., and U. V. Alola. 2018. Agricultural land usage and tourism impact on renewable energy consumption among coastline Mediterranean countries. Energy & Environment 29 (8):1438–54. doi:10.1177/0958305X18779577.
  • Andersen, P., and N. C. Petersen. 1993. A procedure for ranking efficient units in data envelopment analysis. Management Science 39 (10):1261–64. doi:10.1287/mnsc.39.10.1261.
  • Anwar, A., M. Siddique, E. Dogan, and A. Sharif. 2020. The moderating role of renewable and non-renewable energy in environment-income nexus for ASEAN countries: Evidence from method of moments quantile regression. Renewable Energy 956–67. doi:10.1016/j.renene.2020.09.128.
  • Atan, S., and E. Sahin. 2017. Türkiye ile bazı OECD ülkelerinin elektrik üretim sektörleri için verimlilik ve etkinliklerinin karşılaştırmalı analizi. Gazi University Journal of Faculty of Economics and Administrative Sciences 19 (3):845–67.
  • Bagherikahvarin, M., and Y. De Smet. 2016. A ranking method based on DEA and PROMETHEE II (a rank based on DEA & PR. II). Measurement 89:333–42. doi:10.1016/j.measurement.2016.04.026.
  • Banker, R. D., A. Charnes, and W. W. Cooper. 1984. Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science 30 (9):1078–92. doi:10.1287/mnsc.30.9.1078.
  • Brans, J. P., and B. Mareschal. 2005. PROMETHEE Methods. In Multiple criteria decision analysis, state of the art survey, ed. V. Figueira. New York: Springer Science, pp. 163-186.
  • Brans, J. P., P. Vincke, and B. Mareschal. 1986. How to select and how to rank projects: The PROMETHEE method. European Journal of Operational Research doi. 24 (2):228–38. doi:10.1016/0377-2217(86)90044-5.
  • Cerqueira, P. A., E. Soukiazis, and S. Proença. 2020. Assessing the linkages between recycling, renewable energy and sustainable development: Evidence from the OECD countries. Environment, Development and Sustainability 1–26. doi:10.1007/s10668-020-00780-4.
  • Chang, T. P., and J. L. Hu. 2010. Total-factor energy productivity growth, technical progress, and efficiency change: An empirical study of china. Applied Energy 87 (10):3262–70. doi:10.1016/j.apenergy.2010.04.026.
  • Charnes, A., W. Cooper, A. Y. Lewin, and L. M. Seiford. 1997. Data envelopment analysis theory, methodology and applications. Journal of the Operational Research Society 48 (3):332–33. doi:10.1057/palgrave.jors.2600342.
  • Charnes, A., W. W. Cooper, and E. Rhodes. 1978. Measuring the efficiency of decision making units. European Journal of Operational Research 2 (6):429–44. doi:10.1016/0377-2217(78)90138-8.
  • Charnes, V. 1994. Data Envelopment Analysis. 1sted. ed. USA: Kluwer Academic Publishers.
  • yh-Min Chiang, Marko J. Spasojevic, Helene C. Muller-Landau, I-Fang Sun, Yiching Lin, Sheng-Hsin Su, Zueng-Sang Chen, Chien-Teh Chen, Nathan G. Swenson & Ryan W. McEwan  2016. Functional composition drives ecosystem function through multiple mechanisms in a broadleaved subtropical forest. Oecologia 182 (3):829–40. doi:10.1007/s00442-016-3717-z.
  • Chien, T., and J.-L. Hu. 2007. Renewable energy and macroeconomic efficiency of OECD and non-OECD economies. Energy Policy 35 (7):3606–15. doi:10.1016/j.enpol.2006.12.033.
  • Cîrstea, Ş. D., C. S. Martiş, A. Cîrstea, A. Constantinescu-Dobra, and M. T. Fülöp. 2018. Current situation and future perspectives of the Romanian renewable energy. Energies 11 (12):3289. doi:10.3390/en11123289.
  • Coelli, T. J. 1995. Recent developments in frontier modelling and efficiency measurement. Australian Journal of Agricultural Economics 39 (3):219–46. doi:10.1111/j.1467-8489.1995.tb00552.x.
  • Cooper, W. W., L. M. Seiford, and J. Zhu. 2011. Handbook on data envelopment analysis. 2nded. ed. USA: Springer Science & Business Media.
  • Dagdeviren, M. 2008. Decision making in equipment selection: An integrated approach with AHP and PROMETHEE. Journal of Intelligent Manufacturing 19 (4):397–406. doi:10.1007/s10845-008-0091-7.
  • Demirbag, M., E. Tatoglu, and K. W. Glaister. 2009. Equity-based entry modes of emerging country multinationals: Lessons from Turkey. Journal of World Business 44 (4):445–62. doi:10.1016/j.jwb.2008.11.009.
  • Dutta, P., A. Jain, and A. Gupta. 2020. Performance analysis of non-banking finance companies using two-stage data envelopment analysis. Annals of Operations Research 1–26. doi:10.1007/s10479-020-03705-6.
  • Edenhofer, O., R. Pichs-Madruga, Y. Sokona, K. Seyboth, S. Kadner, T. Zwickel, and P. Matschoss. 2011. Renewable energy sources and climate change mitigation: Special report of the intergovernmental panel on climate change. 1sted. ed. USA: Cambridge University Press.
  • Ekiz, M., and C. Tuncer Sakar. 2020. A new approach to rank all alternatives in data envelopment analysis: ASES. Journal of the Faculty of Engineering and Architecture of Gazi University 35 (2):683–95. doi:10.17341/gazimmfd.506640.
  • Emrouznejad, A., and M. Tavana. 2014. Performance measurement with fuzzy data envelopment analysis. 1sted. ed. USA: Springer.
  • Ervural, B. C., S. Zaim, and D. Delen. 2018. A two-stage analytical approach to assess sustainable energy efficiency. Energy 164:822–36. doi:10.1016/j.energy.2018.08.213.
  • Fancello, G., M. Carta, and P. Serra. 2020. Data envelopment analysis for the assessment of road safety in urban road networks: A comparative study using CCR and BCC models. Case Studies on Transport Policy 8 (3):736–44. doi:10.1016/j.cstp.2020.07.007.
  • Farrell, M. J. 1957. The measurement of productive efficiency. Journal of the Royal Statistical Society: Series A (General) 120 (3):253–81. doi:10.2307/2343100.
  • Gervásio, H., and L. S. Da Silva. 2012. A probabilistic decision-making approach for the sustainable assessment of infrastructures. Expert Systems with Applications 39 (8):7121–31. doi:10.1016/j.eswa.2012.01.032.
  • Gokgoz, F., and M. T. Guvercin. 2018. Energy security and renewable energy efficiency in EU. Renewable and Sustainable Energy Reviews 96:226–39. doi:10.1016/j.rser.2018.07.046.
  • Guler, E., S. Kandemir Yerel, and E. Acikkalp. 2020. Türkiye’deki enerji dağıtım şirketlerinin etkinliklerinin veri zarflama analizi ile değerlendirilmesi. Bilecik Seyh Edebali University Journal of Science 7 (1):66–79. doi:10.35193/bseufbd.683652.
  • Hinkle, D. E., W. Wiersma, and S. G. Jurs. 2003. Applied statistics for the behavioral sciences (Vol. 663). Houghton Mifflin College Division.
  • Hong, J. D., and K. Y. Jeong. 2020. Cross-evaluation based super efficiency DEA approach to designing disaster recovery center location-allocation-routing network schemes. Journal of Humanitarian Logistics and Supply Chain Management 10 (4):485–508. doi:10.1108/JHLSCM-03-2020-0019.
  • Honma, S., and J.-L. Hu. 2008. Total-factor energy efficiency of regions in Japan. Energy Policy 36 (2):821–33. doi:10.1016/j.enpol.2007.10.026.
  • Hu, J. L., and S. C. Wang. 2006. Total-factor energy efficiency of regions in China. Energy Policy 34 (17):3206–17. doi:10.1016/j.enpol.2005.06.015.
  • Ibrahim, M. D., and A. A. Alola. 2020. Integrated analysis of energy-economic development-environmental sustainability nexus: Case study of MENA countries. Science of the Total Environment 737:139768. doi:10.1016/j.scitotenv.2020.139768.
  • Internet Adress: https://databank.worldbank.org/source/sustainable-energy-for-all# ( Access date: 23.JULY.2020)
  • J.P. Brans. L’ingénièrie de la décision; Elaboration d’instruments d’aide à la décision. La méthode PROMETHEE. In R. Nadeau and M. Landry, editors, L’aide à la décision: Nature, Instruments et Perspectives d’Avenir, pages 183–213, Québec, Canada, 1982. Presses de l’Université Laval
  • Khare, R., V. G. K. Villuri, and D. Chaurasia. 2020. Urban sustainability assessment: The evaluation of coordinated relationship between BRTS and land use in transit-oriented development mode using DEA model. Ain Shams Engineering Journal: 1–11. doi:10.1016/j.asej.2020.08.012.
  • Kou, G., Y. Peng, and G. Wang. 2014. Evaluation of clustering algorithms for financial risk analysis using MCDM methods. Information Sciences 275 (1–12):1–12. doi:10.1016/j.ins.2014.02.137.
  • Kumar, S., and R. Gulati. 2014. Deregulation and efficiency of Indian banks.
  • Lepchak, A., and S. B. Voese. 2020. Evaluation of the efficiency of logistics activities using Data Envelopment Analysis (DEA). Gestão & Produção 27 (1):1–20. doi:10.1590/0104-530X3371-20.
  • Li, T., A. Li, and X. Guo. 2020. The sustainable development-oriented development and utilization of renewable energy industry-A comprehensive analysis of MCDM methods. Energy 212:118694. doi:10.1016/j.energy.2020.118694.
  • Li, Y. 2020. Analyzing efficiencies of city commercial banks in China: An application of the bootstrapped DEA approach. Pacific-Basin Finance Journal: 62:101372. doi:10.1016/j.pacfin.2020.101372.
  • Liu, D., S. Y. Cho, D. M. Sun, and Z. D. Qiu. 2010. A Spearman correlation coefficient ranking for matching-score fusion on speaker recognition. TENCON 2010–2010 IEEE Region 10 Conference, IEEE. Fukuoka, Japan. doi: 10.1109/TENCON.2010.5686608.
  • Luptáčik, M. 2010. Data Envelopment Analysis. In Mathematical Optimization and Economic Analysis, 135–86. New York: Springer.
  • Mahlknecht, J., and R. González-Bravo. 2018. Measuring the water-energy-food nexus: The case of Latin America and the Caribbean region. Energy Procedia 153:169–73. doi:10.1016/j.egypro.2018.10.065.
  • Mastrocinque, E., F. J. Ramírez, A. Honrubia-Escribano, and D. T. Pham. 2020. An AHP-based multi-criteria model for sustainable supply chain development in the renewable energy sector. Expert Systems with Applications 150:113321. doi:10.1016/j.eswa.2020.113321.
  • Mello, J. C. C. S., L. A. Meza, J. Q. Da Silveira, and E. G. Gomes. 2013. About negative efficiencies in cross evaluation BCC input oriented models. European Journal of Operational Research 229 (3):732–37. doi:10.1016/j.ejor.2013.02.020.
  • Mousavi-Nasab, S. H., and A. Sotoudeh-Anvari. 2017. A comprehensive MCDM-based approach using TOPSIS, COPRAS and DEA as an auxiliary tool for material selection problems. Materials & Design 121:237–53. doi:10.1016/j.matdes.2017.02.041.
  • Mukaka, M. M. 2012. A guide to appropriate use of correlation coefficient in medical research. Malawi Medical Journal 24 (3):69–71.
  • Neofytou, H., A. Nikas, and H. Doukas. 2020. Sustainable energy transition readiness: A multicriteria assessment index. Renewable and Sustainable Energy Reviews 131:109988. doi:10.1016/j.rser.2020.109988.
  • Neofytou, H., Y. Sarafidis, N. Gkonis, S. Mirasgedis, and D. Askounis. 2020. Energy efficiency contribution to sustainable development: A multi-criteria approach in greece. Energy Sources, Part B: Economics, Planning, and Policy 1–33. doi:10.1080/15567249.2020.1849449.
  • Ozcan, Y. A. 2014. Health care benchmarking and performance evaluation, 210. Int. Ser. Oper. Res. Manage. Sci. Springer Science, Business Media, New York.
  • Ozden, U. H. 2008. Veri zarflama analizi (VZA) ile Türkiye’deki vakıf üniversitelerinin etkinliğinin ölçülmesi. Istanbul University Journal of the School of Business Administration 37 (2):167–85.
  • Ozkale, C., C. Celik, A. C. Turkmen, and E. S. Cakmaz. 2017. Decision analysis application intended for selection of a power plant running on renewable energy sources. Renewable and Sustainable Energy Reviews 70:1011–21. doi:10.1016/j.rser.2016.12.006.
  • Ozveri, O., and M. Kabak. 2018. İşletmelerin ürün kalitesi etkinliğinin analiz edilmesi için bulanik veri zarflama analizi yönteminin kullanilmasi. Anadolu University Journal of Social Sciences 18 (3):145–58.
  • Phillis, A., E. Grigoroudis, and V. S. Kouikoglou. 2020. Assessing national energy sustainability using multiple criteria decision analysis. International Journal of Sustainable Development & World Ecology 1–18. doi:10.1080/13504509.2020.1780646.
  • Pohekar, S. D., and M. Ramachandran. 2004. Application of multi-criteria decision making to sustainable energy planning—A review. Renewable and Sustainable Energy Reviews 8 (4):365–81. doi:10.1016/j.rser.2003.12.007.
  • Polatidis, H., and D. A. Haralambopoulos. 2007. Decomposition analysis and design of sustainable renewable energy systems: A new approach. Energy Sources, Part B: Economics, Planning, and Policy 2 (4):371–80. doi:10.1080/15567240600705235.
  • Puth, M. T., M. Neuhäuser, and G. D. Ruxton. 2015. Effective use of spearman’s and kendall’s correlation coefficients for association between two measured traits. Animal Behaviour 102:77–84. doi:10.1016/j.anbehav.2015.01.010.
  • Ren, J., D. Xu, H. Cao, S. A. Wei, L. Dong, and M. E. Goodsite. 2016. Sustainability decision support framework for industrial system prioritization. AIChE Journal 62 (1):108–30. doi:10.1002/aic.15039.
  • Sadorsky, P. 2009. Renewable energy consumption and income in emerging economies. Energy Policy 37 (10):4021–28. doi:10.1016/j.enpol.2009.05.003.
  • Sarkis, J. 2000. A comparative analysis of DEA as a discrete alternative multiple criteria decision tool. European Journal of Operational Research 123 (3):543–57. doi:10.1016/S0377-2217(99)00099-5.
  • Selam, A. A., S. Ozel, and M. O. A. Akan. 2014. Yenilenebilir enerji kullanımı açısından Türkiye’nin OECD ülkeleri arasındaki yeri. Dumlupinar University Journal of Social Science 317–34.
  • Sharma, D., A. Pandey, C. Kumar, and R. K. Ranjan. 2019. Assessment & anthology of sustainable sources of energy using an approach of PROMETHEE. IOP Conference Series: Materials Science and Engineering, IOP Publishing, Greater Noida, India.
  • Shuai, S., and Z. Fan. 2020. Modeling the role of environmental regulations in regional green economy efficiency of china: Empirical evidence from super efficiency DEA-Tobit model. Journal of Environmental Management 261:110227. doi:10.1016/j.jenvman.2020.110227.
  • Solangi, Y. A., Q. Tan, N. H. Mirjat, and S. Ali. 2019. Evaluating the strategies for sustainable energy planning in Pakistan: An integrated SWOT-AHP and Fuzzy-TOPSIS approach. Journal of Cleaner Production 236:117655. doi:10.1016/j.jclepro.2019.117655.
  • Soylemez, A. 2015. Graphical representation of data envelopment analysis by Robust CoPlot. Master’s Thesis. Hacettepe University Institute of Science, Turkey.
  • Sozen, A., and F. Karik. 2017. Comparison of Turkey’s renewable energy performance with OECD and BRICS countries by multiple criteria. Energy Sources, Part B: Economics, Planning, and Policy 12 (5):487–94. doi:10.1080/15567249.2016.1200163.
  • Taskopru, V. 2014. Classic data envelopment analysis with categorical data envelopment analysis models a comparative examination of energy productivity. Master thesis, Mimar Sinan University Institute of Science, Turkey
  • Tipi, T., N. Yildiz, M. Nargelecekenler, and B. Cetin. 2009. Measuring the technical efficiency and determinants of efficiency of rice (Oryza sativa) farms in Marmara region, Turkey. New Zealand Journal of Crop and Horticultural Science 37 (2):121–29. doi:10.1080/01140670909510257.
  • Uludag, A. S., and H. Dogan. 2018. Sürdürülebilir enerji odakli bir etkinlik ve performans analizi: AB üyesi ülkeler ile Türkiye karşılaştırması. In IV. International Caucasus-Central Asia Foreign Trade and Logistics Congress, 7-8 September, Didim- Aydin, Turkey, 335–48.
  • Vavrek, R., and J. Chovancová. 2019. Assessment of economic and environmental energy performance of EU countries using CV-TOPSIS technique. Ecological Indicators 106:105519. doi:10.1016/j.ecolind.2019.105519.
  • Visani, F., and F. Boccali. 2020. Purchasing price assessment of leverage items: A data envelopment analysis approach. International Journal of Production Economics 223:107521. doi:10.1016/j.ijpe.2019.107521.
  • Wang, H. 2015. A generalized MCDA–DEA (multi-criterion decision analysis–data envelopment analysis) approach to construct slacks-based composite indicator. Energy 80:114–22. doi:10.1016/j.energy.2014.11.051.
  • Wang, P., Z. Zhu, and Y. Wang. 2016. A novel hybrid MCDM model combining the SAW, TOPSIS and GRA methods based on experimental design. Information Sciences 345:27–45. doi:10.1016/j.ins.2016.01.076.
  • Wang, Y., L. Xu, and Y. A. Solangi. 2020. Strategic renewable energy resources selection for Pakistan: Based on SWOT-Fuzzy AHP approach. Sustainable Cities and Society 52:101861. doi:10.1016/j.scs.2019.101861.
  • Woo, C., Y. Chung, D. Chun, H. Seo, and S. Hong. 2015. The static and dynamic environmental efficiency of renewable energy: A Malmquist index analysis of OECD countries. Renewable and Sustainable Energy Reviews 47:367–76. doi:10.1016/j.rser.2015.03.070.
  • Yang, L., H. Ouyang, K. Fang, L. Ye, and J. Zhang. 2015. Evaluation of regional environmental efficiencies in China based on super-efficiency-DEA. Ecological Indicators 51:13–19. doi:10.1016/j.ecolind.2014.08.040.
  • Yenioglu, Z. A., and V. Ates. 2019. Yenilenebilir enerji kullanımındaki göreceli etkinliklerin veri zarflama analizi ile değerlendirilmesi: Türkiye ve bazı Avrupa ülkeleri örneği. Journal of Polytechnic 22 (4):863–69. doi:10.2339/politeknik.446110.
  • Yulek, M. Â. 2018. Industrial Policy and Sustainable Growth. 1sted. ed. USA: Springer.
  • Zhu, J., and W. D. Cook. 2007. Modeling data irregularities and structural complexities in data envelopment analysis. 1sted. ed. USA: Springer Science & Business Media.
  • Zurano-Cervelló, P., C. Pozo, J. M. Mateo-Sanz, L. Jiménez, and G. Guillén-Gosálbez. 2019. Sustainability efficiency assessment of the electricity mix of the 28 EU member countries combining data envelopment analysis and optimized projections. Energy Policy 134:110921. doi:10.1016/j.enpol.2019.110921.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.