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Input–Output Efficiency of Chinese Power Generation Enterprises and Its Improvement Direction-Based on Three-Stage DEA Model

Author

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  • Wenhui Zhao

    (College of Economics and Management, Shanghai University of Electric Power, Shanghai 200090, China
    These authors contributed equally to this work.)

  • Ye Qiu

    (College of Economics and Management, Shanghai University of Electric Power, Shanghai 200090, China
    These authors contributed equally to this work.)

  • Wei Lu

    (Academic Affairs Office, Shanghai University of Political Science and Law, Shanghai 201701, China
    These authors contributed equally to this work.)

  • Puyu Yuan

    (College of Science, Shenyang Ligong University, Shenyang 110159, China
    These authors contributed equally to this work.)

Abstract

This paper uses the three-stage DEA method to measure the input–output efficiency of China’s 23 listed power generation companies (mainly thermal power generation) in 2019, and uses the SFA regression model to eliminate environmental elements and random disturbances. The results show that in a non-homogeneous environment, the scale efficiencies of most power generation companies are greater than or equal to their pure technical efficiencies. These companies should first improve management and technical levels, and then optimize the scale of investment. Furthermore, after removing environmental variables, half of the companies should turn to increasing economies of scale instead of diminishing economies of scale. It can be seen that environmental factors, such as the degree of regional development and IPO time, have reduced the economies of scale of enterprises, so they should strengthen the communication between different regions, and the government should provide assistance to companies that are listed late.

Suggested Citation

  • Wenhui Zhao & Ye Qiu & Wei Lu & Puyu Yuan, 2022. "Input–Output Efficiency of Chinese Power Generation Enterprises and Its Improvement Direction-Based on Three-Stage DEA Model," Sustainability, MDPI, vol. 14(12), pages 1-14, June.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:12:p:7421-:d:841193
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    as
    1. Sueyoshi, Toshiyuki & Yuan, Yan, 2016. "Returns to damage under undesirable congestion and damages to return under desirable congestion measured by DEA environmental assessment with multiplier restriction: Economic and energy planning for s," Energy Economics, Elsevier, vol. 56(C), pages 288-309.
    2. Abbott, Malcolm, 2006. "The productivity and efficiency of the Australian electricity supply industry," Energy Economics, Elsevier, vol. 28(4), pages 444-454, July.
    3. Zheng Xiang & Xiaohong Chen & Yanqing Lian, 2016. "Quantifying the Vulnerability of Surface Water Environment in Humid Areas Base on DEA Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(14), pages 5101-5112, November.
    4. Jingqi Sun & Nuermaimaiti Ruze & Jianjun Zhang & Haoran Zhao & Boyang Shen, 2019. "Evaluating the Investment Efficiency of China’s Provincial Power Grid Enterprises under New Electricity Market Reform: Empirical Evidence Based on Three-Stage DEA Model," Energies, MDPI, vol. 12(18), pages 1-17, September.
    5. Andrew N. Kleit & Dek Terrell, 2001. "Measuring Potential Efficiency Gains From Deregulation Of Electricity Generation: A Bayesian Approach," The Review of Economics and Statistics, MIT Press, vol. 83(3), pages 523-530, August.
    6. Pombo, Carlos & Taborda, Rodrigo, 2006. "Performance and efficiency in Colombia's power distribution system: Effects of the 1994 reform," Energy Economics, Elsevier, vol. 28(3), pages 339-369, May.
    7. Jie Wu & Panpan Xia & Qingyuan Zhu & Junfei Chu, 2019. "Measuring environmental efficiency of thermoelectric power plants: a common equilibrium efficient frontier DEA approach with fixed-sum undesirable output," Annals of Operations Research, Springer, vol. 275(2), pages 731-749, April.
    8. Hattori, Toru & Tsutsui, Miki, 2004. "Economic impact of regulatory reforms in the electricity supply industry: a panel data analysis for OECD countries," Energy Policy, Elsevier, vol. 32(6), pages 823-832, April.
    9. Daniel O. COTE, 1989. "Firm Efficiency And Ownership Structure," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 60(4), pages 431-450, October.
    10. IGNATIUS, Joshua & GHASEMI, M.-R. & ZHANG, Feng & EMROUZNEJAD, Ali & HATAMI-MARBINI, Adel, 2016. "Carbon Efficiency Evaluation: An Analytical Framework Using Fuzzy DEA," LIDAM Reprints CORE 2735, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. Charles, Vincent & Aparicio, Juan & Zhu, Joe, 2019. "The curse of dimensionality of decision-making units: A simple approach to increase the discriminatory power of data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 279(3), pages 929-940.
    12. Goto, Mika & Tsutsui, Miki, 1998. "Comparison of Productive and Cost Efficiencies Among Japanese and US Electric Utilities," Omega, Elsevier, vol. 26(2), pages 177-194, April.
    13. Shin, Kong Joo & Managi, Shunsuke, 2017. "Liberalization of a retail electricity market: Consumer satisfaction and household switching behavior in Japan," Energy Policy, Elsevier, vol. 110(C), pages 675-685.
    14. Khodadadipour, M. & Hadi-Vencheh, A. & Behzadi, M.H. & Rostamy-malkhalifeh, M., 2021. "Undesirable factors in stochastic DEA cross-efficiency evaluation: An application to thermal power plant energy efficiency," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 613-628.
    15. Toru Hattori, 2002. "Relative Performance of U.S. and Japanese Electricity Distribution: An Application of Stochastic Frontier Analysis," Journal of Productivity Analysis, Springer, vol. 18(3), pages 269-284, November.
    16. Korhonen, Pekka J. & Luptacik, Mikulas, 2004. "Eco-efficiency analysis of power plants: An extension of data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 154(2), pages 437-446, April.
    17. Du, Minzhe & Liu, Yunxiao & Wang, Bing & Lee, Myunghun & Zhang, Ning, 2021. "The sources of regulated productivity in Chinese power plants: An estimation of the restricted cost function combined with DEA approach," Energy Economics, Elsevier, vol. 100(C).
    18. Jing Yang & Changhui Yang & Xiaojia Wang & Manli Cheng & Jingjing Shang, 2020. "Efficiency Measurement and Factor Analysis of China’s Solar Photovoltaic Power Generation Considering Regional Differences Based on a FAHP–DEA Model," Energies, MDPI, vol. 13(8), pages 1-26, April.
    19. Ignatius, Joshua & Ghasemi, M.-R. & Zhang, Feng & Emrouznejad, Ali & Hatami-Marbini, Adel, 2016. "Carbon efficiency evaluation: An analytical framework using fuzzy DEA," European Journal of Operational Research, Elsevier, vol. 253(2), pages 428-440.
    20. Kottas, Angelos T. & Bozoudis, Michail N. & Madas, Michael A., 2020. "Turbofan aero-engine efficiency evaluation: An integrated approach using VSBM two-stage network DEA," Omega, Elsevier, vol. 92(C).
    21. Palacios M., Sebastián & Saavedra P., Eduardo, 2017. "Alternative policies for the liberalization of retail electricity markets in Chile," Utilities Policy, Elsevier, vol. 49(C), pages 72-92.
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