IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v9y2017i2p210-d89366.html
   My bibliography  Save this article

DEA Efficiency of Energy Consumption in China’s Manufacturing Sectors with Environmental Regulation Policy Constraints

Author

Listed:
  • Xiaoqing Chen

    (School of Economics and Management, Nanjing University of Information Science and Technology, Nanjing 210044, China
    Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China)

  • Zaiwu Gong

    (School of Economics and Management, Nanjing University of Information Science and Technology, Nanjing 210044, China
    Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China)

Abstract

Because overall energy consumption intensity in China’s manufacturing industry is extremely high, the study of energy efficiency in that industry, with an analysis of the policy impacts of energy intensity reduction and other key factors, will no doubt improve energy utilization in the industry and stimulate sustainable development within it. This paper uses 2004–2014 panel data of 28 manufacturing industries and a piecewise linear utility function to construct a data envelopment analysis (DEA) model of energy consumption with environmental regulations constraints. We also examine the DEA evaluation of energy efficiency in manufacturing industries. We integrate environmental regulations as qualitative variables into the energy consumption evaluation model to research the coupling effects on energy consumption intensity of energy consumption structure, opening up, environmental regulations, technological progress, and competition within industries. The research shows that energy efficiency policy intensity is not the major effect on the development of low or moderate energy-consumption industries, whereas low-energy-efficiency policy is very favorable for the development of high energy-consumption industries.

Suggested Citation

  • Xiaoqing Chen & Zaiwu Gong, 2017. "DEA Efficiency of Energy Consumption in China’s Manufacturing Sectors with Environmental Regulation Policy Constraints," Sustainability, MDPI, vol. 9(2), pages 1-19, February.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:2:p:210-:d:89366
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/9/2/210/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/9/2/210/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fujii, Hidemichi & Cao, Jing & Managi, Shunsuke, 2016. "Firm-level environmentally sensitive productivity and innovation in China," Applied Energy, Elsevier, vol. 184(C), pages 915-925.
    2. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    3. Guo, Chuanyin & Abbasi Shureshjani, Roohollah & Foroughi, Ali Asghar & Zhu, Joe, 2017. "Decomposition weights and overall efficiency in two-stage additive network DEA," European Journal of Operational Research, Elsevier, vol. 257(3), pages 896-906.
    4. Kenneth Arrow, 1962. "Economic Welfare and the Allocation of Resources for Invention," NBER Chapters, in: The Rate and Direction of Inventive Activity: Economic and Social Factors, pages 609-626, National Bureau of Economic Research, Inc.
    5. Cook, Wade D. & Ruiz, José L. & Sirvent, Inmaculada & Zhu, Joe, 2017. "Within-group common benchmarking using DEA," European Journal of Operational Research, Elsevier, vol. 256(3), pages 901-910.
    6. Ryo Fujikura & Shinji Kaneko & Hirofumi Nakayama & Naoya Sawazu, 2006. "Coverage and reliability of Chinese statistics regarding sulfur dioxide emissions during the late 1990s," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 7(4), pages 415-434, December.
    7. Yin, Pengzhen & Sun, Jiasen & Chu, Junfei & Liang, Liang, 2016. "Evaluating the environmental efficiency of a two-stage system with undesired outputs by a DEA approach: An interest preference perspectiveAuthor-Name: Wu, Jie," European Journal of Operational Research, Elsevier, vol. 254(3), pages 1047-1062.
    8. Lim, Sungmook & Zhu, Joe, 2016. "A note on two-stage network DEA model: Frontier projection and duality," European Journal of Operational Research, Elsevier, vol. 248(1), pages 342-346.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yutao Lei & Xuan Zhang & Wenxiang Peng, 2022. "Can China’s Policy of Carbon Emissions Trading Optimize Manufacturing Structure? Evidence from Guangdong Based on a Synthetic Control Approach," Sustainability, MDPI, vol. 14(6), pages 1-23, March.
    2. Jianlong Wu & Zhongji Yang & Xiaobo Hu & Hongqi Wang & Jing Huang, 2018. "Exploring Driving Forces of Sustainable Development of China’s New Energy Vehicle Industry: An Analysis from the Perspective of an Innovation Ecosystem," Sustainability, MDPI, vol. 10(12), pages 1-24, December.
    3. Shuo Han & Weijun Cui & Jin Chen & Yu Fu, 2019. "Female CEOs and Corporate Innovation Behaviors—Research on the Regulating Effect of Gender Culture," Sustainability, MDPI, vol. 11(3), pages 1-22, January.
    4. Abbas Mardani & Dalia Streimikiene & Tomas Balezentis & Muhamad Zameri Mat Saman & Khalil Md Nor & Seyed Meysam Khoshnava, 2018. "Data Envelopment Analysis in Energy and Environmental Economics: An Overview of the State-of-the-Art and Recent Development Trends," Energies, MDPI, vol. 11(8), pages 1-21, August.
    5. Yi Zhou & Lianshui Li & Ruiling Sun & Zaiwu Gong & Mingguo Bai & Guo Wei, 2019. "Haze Influencing Factors: A Data Envelopment Analysis Approach," IJERPH, MDPI, vol. 16(6), pages 1-16, March.
    6. Zhijun Feng & Wen Zhou & Qian Ming, 2019. "Embodied Energy Flow Patterns of the Internal and External Industries of Manufacturing in China," Sustainability, MDPI, vol. 11(2), pages 1-24, January.
    7. Hui Li & Kangyin Dong & Renjin Sun & Jintao Yu & Jinhong Xu, 2017. "Sustainability Assessment of Refining Enterprises Using a DEA-Based Model," Sustainability, MDPI, vol. 9(4), pages 1-15, April.
    8. Zaiwu Gong & Xiaoqing Chen, 2017. "Analysis of Interval Data Envelopment Efficiency Model Considering Different Distribution Characteristics—Based on Environmental Performance Evaluation of the Manufacturing Industry," Sustainability, MDPI, vol. 9(12), pages 1-25, November.
    9. Bo Zeng & Meng Zhou & Jun Zhang, 2017. "Forecasting the Energy Consumption of China’s Manufacturing Using a Homologous Grey Prediction Model," Sustainability, MDPI, vol. 9(11), pages 1-16, October.
    10. Xiaobing Yu & Xianrui Yu & Yiqun Lu & Jichuan Sheng, 2018. "Economic and Emission Dispatch Using Ensemble Multi-Objective Differential Evolution Algorithm," Sustainability, MDPI, vol. 10(2), pages 1-17, February.
    11. Shakila Aziz & Sheikh Morshed Jahan, 2023. "Eco-efficiency analysis of industrial sectors in Bangladesh using data envelopment analysis and malmquist productivity index," SN Business & Economics, Springer, vol. 3(2), pages 1-23, February.
    12. Zhiyu Fang & Ling Jiang & Zhong Fang, 2021. "Does Economic Policy Intervention Inhibit the Efficiency of China’s Green Energy Economy?," Sustainability, MDPI, vol. 13(23), pages 1-20, December.
    13. Filip Fidanoski & Kiril Simeonovski & Violeta Cvetkoska, 2021. "Energy Efficiency in OECD Countries: A DEA Approach," Energies, MDPI, vol. 14(4), pages 1-21, February.
    14. Xiaoyang Zhou & Hao Chen & Hao Wang & Benjamin Lev & Lifang Quan, 2019. "Natural and Managerial Disposability Based DEA Model for China’s Regional Environmental Efficiency Assessment," Energies, MDPI, vol. 12(18), pages 1-20, September.
    15. Yue Liu & Pierre Failler & Zhiying Liu, 2022. "Impact of Environmental Regulations on Energy Efficiency: A Case Study of China’s Air Pollution Prevention and Control Action Plan," Sustainability, MDPI, vol. 14(6), pages 1-21, March.
    16. Wei Sun & Yufei Hou & Lanjiang Guo, 2018. "Analyzing and Forecasting Energy Consumption in China’s Manufacturing Industry and Its Subindustries," Sustainability, MDPI, vol. 11(1), pages 1-26, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kaffash, Sepideh & Azizi, Roza & Huang, Ying & Zhu, Joe, 2020. "A survey of data envelopment analysis applications in the insurance industry 1993–2018," European Journal of Operational Research, Elsevier, vol. 284(3), pages 801-813.
    2. Kao, Chiang, 2018. "Multiplicative aggregation of division efficiencies in network data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 270(1), pages 328-336.
    3. Kao, Chiang, 2017. "Efficiency measurement and frontier projection identification for general two-stage systems in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 261(2), pages 679-689.
    4. Zhang, Linyan & Chen, Kun, 2019. "Hierarchical network systems: An application to high-technology industry in China," Omega, Elsevier, vol. 82(C), pages 118-131.
    5. Chu, Junfei & Zhu, Joe, 2021. "Production scale-based two-stage network data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 294(1), pages 283-294.
    6. Dariush Akbarian, 2021. "Network DEA based on DEA-ratio," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-26, December.
    7. Ramin Gharizadeh Beiragh & Reza Alizadeh & Saeid Shafiei Kaleibari & Fausto Cavallaro & Sarfaraz Hashemkhani Zolfani & Romualdas Bausys & Abbas Mardani, 2020. "An integrated Multi-Criteria Decision Making Model for Sustainability Performance Assessment for Insurance Companies," Sustainability, MDPI, vol. 12(3), pages 1, January.
    8. Atwood, Joseph & Shaik, Saleem, 2020. "Theory and statistical properties of Quantile Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 286(2), pages 649-661.
    9. Aghayi, Nazila & Maleki, Bentolhoda, 2016. "Efficiency measurement of DMUs with undesirable outputs under uncertainty based on the directional distance function: Application on bank industry," Energy, Elsevier, vol. 112(C), pages 376-387.
    10. Afsharian, Mohsen & Ahn, Heinz & Harms, Sören Guntram, 2019. "Performance comparison of management groups under centralised management," European Journal of Operational Research, Elsevier, vol. 278(3), pages 845-854.
    11. Nykamp, Stefan & Andor, Mark & Hurink, Johann L., 2012. "‘Standard’ incentive regulation hinders the integration of renewable energy generation," Energy Policy, Elsevier, vol. 47(C), pages 222-237.
    12. Nestor Duch-Brown & Jose Garcia-Quevedo & Daniel Montolio, 2008. "Assessing the assignation of public subsidies: Do the experts choose the most efficient R&D projects?," Working Papers in Economics 207, Universitat de Barcelona. Espai de Recerca en Economia.
    13. Ding, Tao & Zhang, Yun & Zhang, Danlu & Li, Feng, 2023. "Performance evaluation of Chinese research universities: A parallel interactive network DEA approach with shared and fixed sum inputs," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    14. Yaliu Yang & Yuan Wang & Cui Wang & Yingyan Zhang & Cuixia Zhang, 2022. "Temporal and Spatial Evolution of the Science and Technology Innovative Efficiency of Regional Industrial Enterprises: A Data-Driven Perspective," Sustainability, MDPI, vol. 14(17), pages 1-21, August.
    15. Zaiwu Gong & Xiaoqing Chen, 2017. "Analysis of Interval Data Envelopment Efficiency Model Considering Different Distribution Characteristics—Based on Environmental Performance Evaluation of the Manufacturing Industry," Sustainability, MDPI, vol. 9(12), pages 1-25, November.
    16. Zhang, Ning & Zhao, Yu & Wang, Na, 2022. "Is China's energy policy effective for power plants? Evidence from the 12th Five-Year Plan energy saving targets," Energy Economics, Elsevier, vol. 112(C).
    17. Kremantzis, Marios Dominikos & Beullens, Patrick & Kyrgiakos, Leonidas Sotirios & Klein, Jonathan, 2022. "Measurement and evaluation of multi-function parallel network hierarchical DEA systems," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    18. V. Murale & Dr. Clement Sudhahar & Dr. Ashrafali, 2010. "Impact of Intellectual Capital on Firm Value (A Panel Data Analysis of Indian IT Firms)," Journal of Commerce and Trade, Society for Advanced Management Studies, vol. 5(1), pages 99-106, April.
    19. Liu, Bingsheng & Sheu, Jiuh-Biing & Zhao, Xue & Chen, Yuan & Zhang, Wei, 2020. "Decision making on post-disaster rescue routing problems from the rescue efficiency perspective," European Journal of Operational Research, Elsevier, vol. 286(1), pages 321-335.
    20. Antonio Peyrache & Maria C. A. Silva, 2022. "Efficiency and Productivity Analysis from a System Perspective: Historical Overview," Springer Books, in: Duangkamon Chotikapanich & Alicia N. Rambaldi & Nicholas Rohde (ed.), Advances in Economic Measurement, chapter 0, pages 173-230, Springer.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:9:y:2017:i:2:p:210-:d:89366. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.