IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i1p111-d125569.html
   My bibliography  Save this article

Analysis of Total Factor Energy Efficiency and Its Influencing Factors on Key Energy-Intensive Industries in the Beijing-Tianjin-Hebei Region

Author

Listed:
  • Jinchao Li

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Beijing 102206, China)

  • Yuwei Xiang

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Huanyu Jia

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Lin Chen

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

Abstract

In order to realize the synergistic optimization management of energy efficiency in the key energy-intensive industries of the Beijing-Tianjin-Hebei (Jing-Jin-Ji) region, this paper calculates the total factor energy efficiency (TFEE) of 27 industries in the Jing-Jin-Ji region. We discover that the manufacturing of raw chemical materials and chemical products, the smelting and processing of ferrous metals, and the production and supply of electric power and heat power are key industries, considering their economic output ratio, energy consumption ratio, and energy efficiency. Then, the Malmquist index is used to decompose the TFEE of key energy-intensive industries. The results show that the TFEE changes in the three major industries in the Jing-Jin-Ji region are caused by technological progress. Hebei has the highest total factor average energy efficiency in the production and supply of electric power and heat power industry, the main reason for this being the spillover effect from Beijing enterprises that have led to significant technological changes in Hebei. Due to similar technological advancements, Tianjin has the highest total factor average energy efficiency in the manufacturing of raw chemical materials and chemical products and the smelting and processing of ferrous metals. Therefore, the Jing-Jin-Ji region should work to increase its technological innovation and enhance its core competitiveness. We should optimize the allocation of resources in specific industries to improve the scale efficiency.

Suggested Citation

  • Jinchao Li & Yuwei Xiang & Huanyu Jia & Lin Chen, 2018. "Analysis of Total Factor Energy Efficiency and Its Influencing Factors on Key Energy-Intensive Industries in the Beijing-Tianjin-Hebei Region," Sustainability, MDPI, vol. 10(1), pages 1-17, January.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:1:p:111-:d:125569
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/1/111/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/10/1/111/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wu, Li-Ming & Chen, Bai-Sheng & Bor, Yun-Chang & Wu, Yin-Chin, 2007. "Structure model of energy efficiency indicators and applications," Energy Policy, Elsevier, vol. 35(7), pages 3768-3777, July.
    2. Wang, Ke & Lu, Bin & Wei, Yi-Ming, 2013. "China’s regional energy and environmental efficiency: A Range-Adjusted Measure based analysis," Applied Energy, Elsevier, vol. 112(C), pages 1403-1415.
    3. Sueyoshi, Toshiyuki & Yuan, Yan, 2017. "Social sustainability measured by intermediate approach for DEA environmental assessment: Chinese regional planning for economic development and pollution prevention," Energy Economics, Elsevier, vol. 66(C), pages 154-166.
    4. Fare, Rolf & Grosskopf, Shawna & Noh, Dong-Woon & Weber, William, 2005. "Characteristics of a polluting technology: theory and practice," Journal of Econometrics, Elsevier, vol. 126(2), pages 469-492, June.
    5. Kumar Mandal, Sabuj & Madheswaran, S., 2010. "Environmental efficiency of the Indian cement industry: An interstate analysis," Energy Policy, Elsevier, vol. 38(2), pages 1108-1118, February.
    6. Zhou, P. & Ang, B.W., 2008. "Linear programming models for measuring economy-wide energy efficiency performance," Energy Policy, Elsevier, vol. 36(8), pages 2901-2906, August.
    7. 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.
    8. Apergis, Nicholas & Aye, Goodness C. & Barros, Carlos Pestana & Gupta, Rangan & Wanke, Peter, 2015. "Energy efficiency of selected OECD countries: A slacks based model with undesirable outputs," Energy Economics, Elsevier, vol. 51(C), pages 45-53.
    9. Hu, Jin-Li & Wang, Shih-Chuan, 2006. "Total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 34(17), pages 3206-3217, November.
    10. Wang, Ke & Wei, Yi-Ming, 2014. "China’s regional industrial energy efficiency and carbon emissions abatement costs," Applied Energy, Elsevier, vol. 130(C), pages 617-631.
    11. Saygin, D. & Worrell, E. & Tam, C. & Trudeau, N. & Gielen, D.J. & Weiss, M. & Patel, M.K., 2012. "Long-term energy efficiency analysis requires solid energy statistics: The case of the German basic chemical industry," Energy, Elsevier, vol. 44(1), pages 1094-1106.
    12. Rohdin, Patrik & Thollander, Patrik & Solding, Petter, 2007. "Barriers to and drivers for energy efficiency in the Swedish foundry industry," Energy Policy, Elsevier, vol. 35(1), pages 672-677, January.
    13. Zhou, P. & Ang, B.W. & Zhou, D.Q., 2012. "Measuring economy-wide energy efficiency performance: A parametric frontier approach," Applied Energy, Elsevier, vol. 90(1), pages 196-200.
    14. Zhou, P. & Ang, B.W. & Han, J.Y., 2010. "Total factor carbon emission performance: A Malmquist index analysis," Energy Economics, Elsevier, vol. 32(1), pages 194-201, January.
    15. Sueyoshi, Toshiyuki & Goto, Mika & Wang, Derek, 2017. "Malmquist index measurement for sustainability enhancement in Chinese municipalities and provinces," Energy Economics, Elsevier, vol. 67(C), pages 554-571.
    16. Honma, Satoshi & Hu, Jin-Li, 2014. "Industry-level total-factor energy efficiency in developed countries: A Japan-centered analysis," Applied Energy, Elsevier, vol. 119(C), pages 67-78.
    17. Fan, Meiting & Shao, Shuai & Yang, Lili, 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, Elsevier, vol. 79(C), pages 189-201.
    18. Zhang, Ning & Zhou, Peng & Kung, Chih-Chun, 2015. "Total-factor carbon emission performance of the Chinese transportation industry: A bootstrapped non-radial Malmquist index analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 584-593.
    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. Xintao Li & Dong Feng & Jian Li & Zaisheng Zhang, 2019. "Research on the Spatial Network Characteristics and Synergetic Abatement Effect of the Carbon Emissions in Beijing–Tianjin–Hebei Urban Agglomeration," Sustainability, MDPI, vol. 11(5), pages 1-15, March.
    2. Zheming Yan & Rui Shi & Zhiming Yang, 2018. "ICT Development and Sustainable Energy Consumption: A Perspective of Energy Productivity," Sustainability, MDPI, vol. 10(7), pages 1-15, July.
    3. Jianguo Zhou & Baoling Jin & Shijuan Du & Ping Zhang, 2018. "Scenario Analysis of Carbon Emissions of Beijing-Tianjin-Hebei," Energies, MDPI, vol. 11(6), pages 1-17, June.
    4. Cong Hu & Biliang Hu & Xunpeng Shi & Yan Wu, 2020. "The Roles of Beijing-Tianjin-Hebei Coordinated Development Strategy in Industrial Energy and Related Pollutant Emission Intensities," Sustainability, MDPI, vol. 12(19), pages 1-17, September.
    5. Yongrok Choi, 2018. "Regional Cooperation for the Sustainable Development and Management in Northeast Asia," Sustainability, MDPI, vol. 10(2), pages 1-8, February.
    6. Chen, Ya & Pan, Yongbin & Wang, Mengyuan & Ding, Tao & Zhou, Zhixiang & Wang, Ke, 2023. "How do industrial sectors contribute to carbon peaking and carbon neutrality goals? A heterogeneous energy efficiency analysis for Beijing," Structural Change and Economic Dynamics, Elsevier, vol. 66(C), pages 67-80.
    7. Gregory N. Sixt & Claudia Strambo & Jingjing Zhang & Nicholas Chow & Jie Liu & Guoyi Han, 2020. "Assessing the Level of Inter-Sectoral Policy Integration for Governance in the Water–Energy Nexus: A Comparative Study of Los Angeles and Beijing," Sustainability, MDPI, vol. 12(17), pages 1-19, September.
    8. Ruyin Long & Qin Zhang & Hong Chen & Meifen Wu & Qianwen Li, 2020. "Measurement of the Energy Intensity of Human Well-Being and Spatial Econometric Analysis of Its Influencing Factors," IJERPH, MDPI, vol. 17(1), pages 1-21, January.
    9. Chuai, Xiaowei & Gao, Runyi & Huang, Xianjin & Lu, Qinli & Zhao, Rongqin, 2021. "The embodied flow of built-up land in China's interregional trade and its implications for regional carbon balance," Ecological Economics, Elsevier, vol. 184(C).
    10. Dong Feng & Jian Li & Xintao Li & Zaisheng Zhang, 2019. "The Effects of Urban Sprawl and Industrial Agglomeration on Environmental Efficiency: Evidence from the Beijing–Tianjin–Hebei Urban Agglomeration," Sustainability, MDPI, vol. 11(11), pages 1-12, May.

    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. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    2. Song, Chenxi & Li, Mingjia & Wen, Zhexi & He, Ya-Ling & Tao, Wen-Quan & Li, Yangzhe & Wei, Xiangyang & Yin, Xiaolan & Huang, Xing, 2014. "Research on energy efficiency evaluation based on indicators for industry sectors in China," Applied Energy, Elsevier, vol. 134(C), pages 550-562.
    3. Mardani, Abbas & Zavadskas, Edmundas Kazimieras & Streimikiene, Dalia & Jusoh, Ahmad & Khoshnoudi, Masoumeh, 2017. "A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1298-1322.
    4. Qin, Quande & Li, Xin & Li, Li & Zhen, Wei & Wei, Yi-Ming, 2017. "Air emissions perspective on energy efficiency: An empirical analysis of China’s coastal areas," Applied Energy, Elsevier, vol. 185(P1), pages 604-614.
    5. Zhou, D.Q. & Wu, F. & Zhou, X. & Zhou, P., 2016. "Output-specific energy efficiency assessment: A data envelopment analysis approach," Applied Energy, Elsevier, vol. 177(C), pages 117-126.
    6. Ke Wang & Yujiao Xian & Yi-Ming Wei & Zhimin Huang, 2016. "Sources of carbon productivity change: A decomposition and disaggregation analysis based on global Luenberger productivity indicator and endogenous directional distance function," CEEP-BIT Working Papers 91, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    7. Zhou, D.Q. & Wang, Qunwei & Su, B. & Zhou, P. & Yao, L.X., 2016. "Industrial energy conservation and emission reduction performance in China: A city-level nonparametric analysis," Applied Energy, Elsevier, vol. 166(C), pages 201-209.
    8. Zhang, Yue-Jun & Sun, Ya-Fang & Huang, Junling, 2018. "Energy efficiency, carbon emission performance, and technology gaps: Evidence from CDM project investment," Energy Policy, Elsevier, vol. 115(C), pages 119-130.
    9. Shuangjie Li & Hongyu Diao & Liming Wang & Chunqi Li, 2021. "Energy Efficiency Measurement: A VO TFEE Approach and Its Application," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    10. Zhou, Haibo & Yang, Yi & Chen, Yao & Zhu, Joe, 2018. "Data envelopment analysis application in sustainability: The origins, development and future directions," European Journal of Operational Research, Elsevier, vol. 264(1), pages 1-16.
    11. Ying Li & Yung-Ho Chiu & Liang Chun Lu, 2018. "Regional Energy, CO 2 , and Economic and Air Quality Index Performances in China: A Meta-Frontier Approach," Energies, MDPI, vol. 11(8), pages 1-20, August.
    12. Wang, Qunwei & Su, Bin & Sun, Jiasen & Zhou, Peng & Zhou, Dequn, 2015. "Measurement and decomposition of energy-saving and emissions reduction performance in Chinese cities," Applied Energy, Elsevier, vol. 151(C), pages 85-92.
    13. Nelson Amowine & Zhiqiang Ma & Mingxing Li & Zhixiang Zhou & Benjamin Azembila Asunka & James Amowine, 2019. "Energy Efficiency Improvement Assessment in Africa: An Integrated Dynamic DEA Approach," Energies, MDPI, vol. 12(20), pages 1-17, October.
    14. Lin, Boqiang & Du, Kerui, 2015. "Energy and CO2 emissions performance in China's regional economies: Do market-oriented reforms matter?," Energy Policy, Elsevier, vol. 78(C), pages 113-124.
    15. Yu, Dejian & He, Xiaorong, 2020. "A bibliometric study for DEA applied to energy efficiency: Trends and future challenges," Applied Energy, Elsevier, vol. 268(C).
    16. 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.
    17. Feng, Chao & Zhang, Hua & Huang, Jian-Bai, 2017. "The approach to realizing the potential of emissions reduction in China: An implication from data envelopment analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 859-872.
    18. P. Zhou & F. Wu & D. Q. Zhou, 2017. "Total-factor energy efficiency with congestion," Annals of Operations Research, Springer, vol. 255(1), pages 241-256, August.
    19. Hang, Ye & Sun, Jiasen & Wang, Qunwei & Zhao, Zengyao & Wang, Yizhong, 2015. "Measuring energy inefficiency with undesirable outputs and technology heterogeneity in Chinese cities," Economic Modelling, Elsevier, vol. 49(C), pages 46-52.
    20. Wang, Q.W. & Zhou, P. & Shen, N. & Wang, S.S., 2013. "Measuring carbon dioxide emission performance in Chinese provinces: A parametric approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 324-330.

    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:10:y:2018:i:1:p:111-:d:125569. 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.