IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i8p3613-d1636245.html
   My bibliography  Save this article

Spatial and Temporal Differentiation of Carbon Emission Efficiency and the Impact of Green Technology Innovation in Hubei Province

Author

Listed:
  • Shan Duan

    (Hubei Key Laboratory of Regional Development and Environmental Response, Hubei University, Wuhan 430062, China)

  • Bingying Shang

    (Hubei Key Laboratory of Regional Development and Environmental Response, Hubei University, Wuhan 430062, China)

  • Yan Nie

    (Hubei Key Laboratory of Geographic Process Analysis and Simulation, Central China Normal University, Wuhan 430079, China)

  • Junkai Wang

    (Hubei Key Laboratory of Regional Development and Environmental Response, Hubei University, Wuhan 430062, China)

  • Ming Li

    (Hubei Key Laboratory of Regional Development and Environmental Response, Hubei University, Wuhan 430062, China)

  • Jing Yu

    (Hubei Key Laboratory of Regional Development and Environmental Response, Hubei University, Wuhan 430062, China)

Abstract

Green technological innovation is pivotal in advancing the ‘dual carbon’ target and promoting sustainable and low-carbon development. This research examines 17 prefecture-level cities in Hubei Province, employing the Super-SBM model for assessing emissions of carbon efficiency from 2010 to 2020. The kernel density estimation and the Dagum coefficient of Gini are also used to examine the spatio-temporal differentiation and the evolution of these efficiencies. A data panel regression model is utilized to evaluate how green technological innovation impacts carbon emission efficiency in Hubei Province. The research revealed that (1) Hubei Province’s carbon emission efficiency first fluctuated and then increased rapidly, and (2) the overall regional difference in carbon emission efficiency in Hubei Province shows a trend of first decreasing and then gradually increasing. The Wuhan metropolitan area and the Xiang-yang-Shiyan-Suizhou-Shennongjia urban area are quite different; the differentiation within the Yichang-Jingzhou-Jing-Enshi urban agglomeration shows a narrowing trend. (3) The innovation elements of green technology are positively correlated with the effectiveness of carbon emissions; the relationship between economic expansion and population density among the control variables also shows a positive correlation, while the industrial structure and government environmental regulations are negatively correlated. (4) In Hubei Province, there is a temporal lag between green technological innovation and its impact on carbon emission efficiency. Capital investment and technical achievement currently enhance carbon emission efficiency, while human capital positively affects carbon emission efficiency during a second lag period. This article proposes countermeasures and recommendations for R&D capital spending, innovative talent cultivation, and regional differentiation, providing specific references to advance the coordinated growth of the whole Hubei Province and green sustainable development.

Suggested Citation

  • Shan Duan & Bingying Shang & Yan Nie & Junkai Wang & Ming Li & Jing Yu, 2025. "Spatial and Temporal Differentiation of Carbon Emission Efficiency and the Impact of Green Technology Innovation in Hubei Province," Sustainability, MDPI, vol. 17(8), pages 1-22, April.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:8:p:3613-:d:1636245
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/8/3613/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/8/3613/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhenxing Jin & Chengxin Wang & Shangkun Yu & Shuai Zhang & Xiaoming Ding, 2022. "Spatiotemporal evolution and influencing factors of urban shrinkage in the Yellow River Basin, China," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-19, March.
    2. Chaomei Chen, 2003. "Patents, citations & innovations: A window on the knowledge economy," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 54(8), pages 802-803, June.
    3. Fang, Zhen, 2023. "Assessing the impact of renewable energy investment, green technology innovation, and industrialization on sustainable development: A case study of China," Renewable Energy, Elsevier, vol. 205(C), pages 772-782.
    4. R. Ramanathan, 2002. "Combining indicators of energy consumption and CO 2 emissions: a cross-country comparison," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 17(3), pages 214-227.
    5. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    Full references (including those not matched with items on IDEAS)

    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. Bo Li & Jing Liu & Qian Liu & Muhammad Mohiuddin, 2022. "The Effects of Broadband Infrastructure on Carbon Emission Efficiency of Resource-Based Cities in China: A Quasi-Natural Experiment from the “Broadband China” Pilot Policy," IJERPH, MDPI, vol. 19(11), pages 1-27, May.
    2. Zhang, Wei & Liu, Xuemeng & Zhao, Shikuan & Tang, Tian, 2024. "Does green finance agglomeration improve carbon emission performance in China? A perspective of spatial spillover," Applied Energy, Elsevier, vol. 358(C).
    3. Zhou, Di & Huang, Qing & Chong, Zhaohui, 2022. "Analysis on the effect and mechanism of land misallocation on carbon emissions efficiency: Evidence from China," Land Use Policy, Elsevier, vol. 121(C).
    4. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    5. Cenjie Liu & Zhongbao Zhou & Qing Liu & Rui Xie & Ximei Zeng, 2020. "Can a low-carbon development path achieve win-win development: evidence from China’s low-carbon pilot policy," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 25(7), pages 1199-1219, October.
    6. Ji, Youmeng & Wu, Xiangli & Wang, Limin, 2024. "Spatial correlation network and influencing factors analysis of supply efficiency of basic public service (SEBPS) in rust belt regions of China: An empirical study from Northeast China," Socio-Economic Planning Sciences, Elsevier, vol. 96(C).
    7. Zhang, Wei & Liu, Xuemeng & Wang, Die & Zhou, Jianping, 2022. "Digital economy and carbon emission performance: Evidence at China's city level," Energy Policy, Elsevier, vol. 165(C).
    8. Halkos, George & Petrou, Kleoniki Natalia, 2017. "Regional environmental efficiency in waste generation," MPRA Paper 81237, University Library of Munich, Germany.
    9. Zhou, P. & Ang, B.W. & Poh, K.L., 2006. "Slacks-based efficiency measures for modeling environmental performance," Ecological Economics, Elsevier, vol. 60(1), pages 111-118, November.
    10. Ying Sun & Fengqin Liu & Huaping Sun, 2022. "Does Standardization Improve Carbon Emission Efficiency as Soft Infrastructure? Evidence from China," Energies, MDPI, vol. 15(6), pages 1-17, March.
    11. Tianyi Zeng & Hong Jin & Zhifei Geng & Zihang Kang & Zichen Zhang, 2022. "The Effect of Urban Shrinkage on Carbon Dioxide Emissions Efficiency in Northeast China," IJERPH, MDPI, vol. 19(9), pages 1-18, May.
    12. Liu, Biao & Wang, Jinman & Feng, Yu & Yang, Man & Mu, Jiayin, 2024. "Mitigating the disparities in carbon emission efficiency enhancement in China's coal resource-based cities," Energy, Elsevier, vol. 307(C).
    13. Wang, Qunwei & Chiu, Yung-Ho & Chiu, Ching-Ren, 2017. "Non-radial metafrontier approach to identify carbon emission performance and intensity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 664-672.
    14. Qunwei Wang & Peng Zhou & Zengyao Zhao & Neng Shen, 2014. "Energy Efficiency and Energy Saving Potential in China: A Directional Meta-Frontier DEA Approach," Sustainability, MDPI, vol. 6(8), pages 1-17, August.
    15. Chenxu Liu & Ruien Tang & Yaqi Guo & Yuhan Sun & Xinyi Liu, 2022. "Research on the Structure of Carbon Emission Efficiency and Influencing Factors in the Yangtze River Delta Urban Agglomeration," Sustainability, MDPI, vol. 14(10), pages 1-22, May.
    16. Minyoung Yang & Jinsoo Kim, 2022. "A Critical Review of the Definition and Estimation of Carbon Efficiency," Sustainability, MDPI, vol. 14(16), pages 1-18, August.
    17. Wen-Min Lu & Qian Long Kweh & Chung-Wei Wang, 2021. "Integration and application of rough sets and data envelopment analysis for assessments of the investment trusts industry," Annals of Operations Research, Springer, vol. 296(1), pages 163-194, January.
    18. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499.
    19. Alperovych, Yan & Hübner, Georges & Lobet, Fabrice, 2015. "How does governmental versus private venture capital backing affect a firm's efficiency? Evidence from Belgium," Journal of Business Venturing, Elsevier, vol. 30(4), pages 508-525.
    20. Chen, Ya & Pan, Yongbin & Liu, Haoxiang & Wu, Huaqing & Deng, Guangwei, 2023. "Efficiency analysis of Chinese universities with shared inputs: An aggregated two-stage network DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 90(C).

    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:17:y:2025:i:8:p:3613-:d:1636245. 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.