References
- Ai et al. 2018. Technical efficiency analysis of major agriculture production provinces in China: A stochastic frontier model with entropy. Journal Of Physics: Conference Series 1053:12101.
- Caves, D. W., L. R. Christensen, and W. E. Diewert. 1982. Multilateral comparisons of output, input, and productivity using superlative index numbers. Economic Journal 92 (365):73–86. doi:10.2307/2232257.
- Charnes, A. C. W. W. 1978. Measuring the efficiency of decision making units. European Journal Of Operational Research 6 (2):429–44. doi:10.1016/0377-2217(78)90138-8.
- Chen, L., and G. Jia. 2017. Environmental efficiency analysis of China’s regional industry: A data envelopment analysis (DEA) based approach. Journal Of Cleaner Production 142:846–53. doi:10.1016/j.jclepro.2016.01.045.
- Cooper, W. W. 1984. Some models of estimating technical and scale inefficiencies in data envelopment analysis.
- D’ Inverno, G., L. Carosi, G. Romano, and A. Guerrini. 2018. Water pollution in wastewater treatment plants: An efficiency analysis with undesirable output. European Journal Of Operational Research 269 (1):24–34. doi:10.1016/j.ejor.2017.08.028.
- Emrouznejad, A., and G. Yang. 2016. A framework for measuring global Malmquist–Luenberger productivity index with CO 2 emissions on Chinese manufacturing industries. Energy 115:840–56. doi:10.1016/j.energy.2016.09.032.
- Fan, M., S. Shao, and L. Yang. 2015. Combining global Malmquist–Luenberger index and generalized method of moments to investigate industrial total factor CO2 emission performance: A case of Shanghai (China). Energy Policy 79:189–201. doi:10.1016/j.enpol.2014.12.027.
- Färe, R., S. Grosskopf, and M. Norris. 1997. Productivity growth, technical progress, and efficiency change in industrialized countries: Reply. American Economic Review 87 (5):1040–44.
- Fei, R., and B. Lin. 2016. Energy efficiency and production technology heterogeneity in China’s agricultural sector: A meta-frontier approach. Technological Forecasting And Social Change 109:25–34. doi:10.1016/j.techfore.2016.05.012.
- Fei, R., and B. Lin. 2017. The integrated efficiency of inputs–Outputs and energy – CO2 emissions performance of China’s agricultural sector. Renewable And Sustainable Energy Reviews 75:668–76. doi:10.1016/j.rser.2016.11.040.
- Fujii, H., and S. Managi. 2015. Optimal production resource reallocation for CO 2 emissions reduction in manufacturing sectors. Global Environmental Change 35:505–13. doi:10.1016/j.gloenvcha.2015.06.005.
- Gökgöz, F., and E. Erkul. 2019. Investigating the energy efficiencies of European countries with super efficiency model and super SBM approaches. Energy Efficiency 12 (3):601–18. doi:10.1007/s12053-018-9652-6.
- Government, C.C. 2016. The 13th five-year plan for national economic and social development of the people’s republic of china. Chinese Nursing Research.
- Guo, X., Q. Zhu, L. Lv, J. Chu, and J. Wu. 2017. Efficiency evaluation of regional energy saving and emission reduction in China: A modified slacks-based measure approach. Journal Of Cleaner Production 140:1313–21. doi:10.1016/j.jclepro.2016.10.021.
- Guo, X. M., and Z. Y. Zhang. 2011. China’s energy price shocks on its tertiary industry energy efficiency: Avector-error-correction model based empirical study. Journal Of Chongqing University 10 (1):1–13.
- Lin, B., and X. Wang. 2014. Exploring energy efficiency in China׳s iron and steel industry: A stochastic frontier approach. Energy Policy 72:87–96. doi:10.1016/j.enpol.2014.04.043.
- Lin, W., B. Chen, L. Xie, and H. Pan. 2015. Estimating energy consumption of transport modes in china using DEA. Sustainability 7 (4):4225–39. doi:10.3390/su7044225.
- Malmquist, S. 1953. Index numbers and indifference surfaces. Trabajos De Estadistica 4 (2):209–42. doi:10.1007/BF03006863.
- Olatubi, W. O., and D. E. Dismukes. 2000. A data envelopment analysis of the levels and determinants of coal-fired electric power generation performance. Utilities Policy 9 (2):47–59. doi:10.1016/S0957-1787(01)00004-2.
- Qin, Q., X. Li, L. Li, W. Zhen, and Y.-M. Wei. 2017. Air emissions perspective on energy efficiency: An empirical analysis of China’s coastal areas. Applied Energy 185:604–14. doi:10.1016/j.apenergy.2016.10.127.
- Ren, L. 2009. Productivity evaluation to chinese agriculture based on sbm model. IEEE 505–08.
- Rodríguez, C. M., C. F. Rengifo Rodas, J. C. Corrales Muñoz, and A. F. Casas. 2019. A multi-criteria approach for comparison of environmental assessment methods in the analysis of the energy efficiency in agricultural production systems. Journal Of Cleaner Production 228:1464–71. doi:10.1016/j.jclepro.2019.04.388.
- Sueyoshi, T., and Y. Yuan. 2017. Social sustainability measured by intermediate approach for DEA environmental assessment: Chinese regional planning for economic development and pollution prevention. Energy Economics 66:154–66. doi:10.1016/j.eneco.2017.06.008.
- Tone, K. 2001. A slacks-based measure of e ciency in data envelopment analysis. European Journal Of Operational Research 130:498–509. doi:10.1016/S0377-2217(99)00407-5.
- Tone, K. 2002. A slacks-based measure of super-efficiency in data envelopment analysis. European Journal Of Operational Research 143 (1):32–41. doi:10.1016/S0377-2217(01)00324-1.
- Vlontzos, G., S. Niavis, and B. Manos. 2014. A DEA approach for estimating the agricultural energy and environmental efficiency of EU countries. Renewable And Sustainable Energy Reviews 40:91–96. doi:10.1016/j.rser.2014.07.153.
- Wang, K., Y. Wei, and Z. Huang. 2018. Environmental efficiency and abatement efficiency measurements of China’s thermal power industry: A data envelopment analysis based materials balance approach. European Journal Of Operational Research 269 (1):35–50. doi:10.1016/j.ejor.2017.04.053.
- Wang, P., B. Zhu, X. Tao, and R. Xie. 2017. Measuring regional energy efficiencies in China: A meta-frontier SBM-undesirable approach. Natural Hazards 85 (2):793–809. doi:10.1007/s11069-016-2605-5.
- Wang, S., and Y. Ma. 2018. Influencing factors and regional discrepancies of the efficiency of carbon dioxide emissions in Jiangsu, China. Ecological Indicators 90:460–68. doi:10.1016/j.ecolind.2018.03.033.
- 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.
- Yang, Z., D. Wang, T. Du, A. Zhang, and Y. Zhou. 2018. Total-factor energy efficiency in China’s agricultural sector: Trends, disparities and potentials. Energies 11 (4):853. doi:10.3390/en11040853.
- Zhang, N., P. Zhou, and C.-C. Kung. 2015. Total-factor carbon emission performance of the Chinese transportation industry: A bootstrapped non-radial Malmquist index analysis. Renewable And Sustainable Energy Reviews 41:584–93. doi:10.1016/j.rser.2014.08.076.
- Zhang, P., J. Lv, and X. Yang. 2014. Evaluating the operating efficiency of chinese bonded zone based on super-sbm model. IEEE 1–5.
- Zhao, R., and D. Wang. 2014. Evaluation on efficiency of agricultural circular economy in Hebei based on DEA. Journal of Agricultural Mechanization Research.
- Zhou, C., C. Shi, S. Wang, and G. Zhang. 2018. Estimation of eco-efficiency and its influencing factors in Guangdong province based on Super-SBM and panel regression models. Ecological Indicators 86:67–80. doi:10.1016/j.ecolind.2017.12.011.