IDEAS home Printed from https://ideas.repec.org/a/spr/endesu/v26y2024i11d10.1007_s10668-023-03757-1.html
   My bibliography  Save this article

Spatial correlation network structure of green innovation efficiency and its driving factors in the Bohai Rim region

Author

Listed:
  • Kaixuan Di

    (Shandong Normal University)

  • Zuankuo Liu

    (Shandong Normal University)

  • Shanglei Chai

    (Shandong Normal University)

  • Kanyong Li

    (Shandong Jiaotong University)

  • Yu Li

    (Shandong Normal University)

Abstract

As the integration point of green development and innovation-driven, green innovation has become the key to promote high-quality and sustainable development in the Bohai Rim region. This study calculates the green innovation efficiency (GIE) of 43 cities in the Bohai Rim region based on the super slacks-based measure (super-SBM) model, further using the social network analysis and quadratic assignment procedure analysis methods to explore the GIE spatial correlation network structure and its driving factors. The findings show that (1) the GIE between cities in the Bohai Rim region exhibits complex and stable network characteristics; (2) Beijing and Tianjin exert an important influence on the green innovation development of other cities; (3) each city is divided into four functional blocks, with strong spatial spillover effects between the blocks; and (4) the closer the geographical distance is, the more similar the environmental regulations are, and the easier it is for spatial associations to occur. The differences in the level of urban economic development, openness, human capital, and infrastructure are conducive to promoting the establishment of spatial associations. Finally, based on the conclusions, the study provides a theoretical basis and policy recommendations for improving the quality and efficiency of green innovation and collaborative development in the Bohai Rim region.

Suggested Citation

  • Kaixuan Di & Zuankuo Liu & Shanglei Chai & Kanyong Li & Yu Li, 2024. "Spatial correlation network structure of green innovation efficiency and its driving factors in the Bohai Rim region," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(11), pages 27227-27247, November.
    • Handle: RePEc:spr:endesu:v:26:y:2024:i:11:d:10.1007_s10668-023-03757-1
    DOI: 10.1007/s10668-023-03757-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10668-023-03757-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10668-023-03757-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Liang, Zhiying & Chen, Jian & Jiang, Dayang & Sun, Yunpeng, 2022. "Assessment of the spatial association network of green innovation: Role of energy resources in green recovery," Resources Policy, Elsevier, vol. 79(C).
    2. Jiang, Yufan & Wang, Hongyan & Liu, Zuankuo, 2021. "The impact of the free trade zone on green total factor productivity ——evidence from the shanghai pilot free trade zone," Energy Policy, Elsevier, vol. 148(PB).
    3. Lu Wang & Wenzhong Ye & Lingming Chen, 2021. "Research on Green Innovation of the Great Changsha-Zhuzhou-Xiangtan City Group Based on Network," Land, MDPI, vol. 10(11), pages 1-15, November.
    4. Sun, Huaping & Edziah, Bless Kofi & Sun, Chuanwang & Kporsu, Anthony Kwaku, 2019. "Institutional quality, green innovation and energy efficiency," Energy Policy, Elsevier, vol. 135(C).
    5. Piao, Zhefan & Miao, Binbin & Zheng, Zihan & Xu, Feng, 2022. "Technological innovation efficiency and its impact factors: An investigation of China's listed energy companies," Energy Economics, Elsevier, vol. 112(C).
    6. Wang, Jiating & Cai, Siyuan, 2020. "The construction of high-speed railway and urban innovation capacity: Based on the perspective of knowledge Spillover," China Economic Review, Elsevier, vol. 63(C).
    7. Zeng, Juying & Škare, Marinko & Lafont, Juan, 2021. "The co-integration identification of green innovation efficiency in Yangtze River Delta region," Journal of Business Research, Elsevier, vol. 134(C), pages 252-262.
    8. Long, Xingle & Zhao, Xicang & Cheng, Faxin, 2015. "The comparison analysis of total factor productivity and eco-efficiency in China's cement manufactures," Energy Policy, Elsevier, vol. 81(C), pages 61-66.
    9. Liu, Gengyuan & Yang, Zhifeng & Fath, Brian D. & Shi, Lei & Ulgiati, Sergio, 2017. "Time and space model of urban pollution migration: Economy-energy-environment nexus network," Applied Energy, Elsevier, vol. 186(P2), pages 96-114.
    10. Edziah, Bless Kofi & Sun, Huaping & Adom, Philip Kofi & Wang, Feng & Agyemang, Andrew Osei, 2022. "The role of exogenous technological factors and renewable energy in carbon dioxide emission reduction in Sub-Saharan Africa," Renewable Energy, Elsevier, vol. 196(C), pages 1418-1428.
    11. Liu, S. & Xiao, Q., 2021. "An empirical analysis on spatial correlation investigation of industrial carbon emissions using SNA-ICE model," Energy, Elsevier, vol. 224(C).
    12. Luo, Yusen & Lu, Zhengnan & Long, Xingle, 2020. "Heterogeneous effects of endogenous and foreign innovation on CO2 emissions stochastic convergence across China," Energy Economics, Elsevier, vol. 91(C).
    13. Biao Hu & Kai Yuan & Tingyun Niu & Liang Zhang & Yuqiong Guan, 2022. "Study on the Spatial and Temporal Evolution Patterns of Green Innovation Efficiency and Driving Factors in Three Major Urban Agglomerations in China—Based on the Perspective of Economic Geography," Sustainability, MDPI, vol. 14(15), pages 1-28, July.
    14. Liu, Fengqin & Sim, Jae-yeon & Sun, Huaping & Edziah, Bless Kofi & Adom, Philip Kofi & Song, Shunfeng, 2023. "Assessing the role of economic globalization on energy efficiency: Evidence from a global perspective," China Economic Review, Elsevier, vol. 77(C).
    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. Napolitano, Oreste & Foresti, Pasquale & Kounetas, Konstantinos & Spagnolo, Nicola, 2023. "The impact of energy, renewable and CO2 emissions efficiency on countries’ productivity," Energy Economics, Elsevier, vol. 125(C).
    2. Liwen Sun & Ying Han, 2022. "Spatial Correlation Network Structure and Influencing Factors of Two-Stage Green Innovation Efficiency: Evidence from China," Sustainability, MDPI, vol. 14(18), pages 1-22, September.
    3. Nakaishi, Tomoaki & Nagashima, Fumiya & Kagawa, Shigemi & Nansai, Keisuke & Chatani, Satoru, 2023. "Quantifying the health benefits of improving environmental efficiency: A case study from coal power plants in China," Energy Economics, Elsevier, vol. 121(C).
    4. D’Errico, Maria Chiara, 2024. "Sustainable economic growth and energy security nexus: A stochastic frontier analysis across OECD countries," Energy Economics, Elsevier, vol. 132(C).
    5. Xie, Ronghui & Teo, Thompson S.H., 2022. "Green technology innovation, environmental externality, and the cleaner upgrading of industrial structure in China — Considering the moderating effect of environmental regulation," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    6. Eleftherios Spyromitros, 2023. "Determinants of Green Innovation: The Role of Monetary Policy and Central Bank Characteristics," Sustainability, MDPI, vol. 15(10), pages 1-23, May.
    7. Shaoyan Yang & Duodong Ding & Churen Sun, 2022. "Does Innovative City Policy Improve Green Total Factor Energy Efficiency? Evidence from China," Sustainability, MDPI, vol. 14(19), pages 1-30, October.
    8. Luo, Yusen & Lu, Zhengnan & Wu, Chao, 2023. "Can internet development accelerate the green innovation efficiency convergence: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    9. Weisong Mi & Kaixu Zhao & Pei Zhang, 2022. "Spatio-Temporal Evolution and Driving Mechanism of Green Innovation in China," Sustainability, MDPI, vol. 14(9), pages 1-27, April.
    10. Biao Hu & Kai Yuan & Tingyun Niu & Liang Zhang & Yuqiong Guan, 2022. "Study on the Spatial and Temporal Evolution Patterns of Green Innovation Efficiency and Driving Factors in Three Major Urban Agglomerations in China—Based on the Perspective of Economic Geography," Sustainability, MDPI, vol. 14(15), pages 1-28, July.
    11. Sun, Yunpeng & Gao, Pengpeng & Tian, Wenjuan & Guan, Weimin, 2023. "Green innovation for resource efficiency and sustainability: Empirical analysis and policy," Resources Policy, Elsevier, vol. 81(C).
    12. Edziah, Bless Kofi & Opoku, Eric Evans Osei, 2024. "Enhancing energy efficiency in Asia-Pacific: Comprehensive energy policy analysis," Energy Economics, Elsevier, vol. 138(C).
    13. Ningning Cui & Emmanuel Nketiah & Xiaoyu Ma, 2023. "Do Green Energy and Information Technology Influence Greenhouse Gas Emitting Countries to Attain Sustainable Development?," Sustainability, MDPI, vol. 15(18), pages 1-19, September.
    14. Djula Borozan, 2023. "Institutions and Environmentally Adjusted Efficiency," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 14(4), pages 4489-4510, December.
    15. Fu, Tong & Jian, Ze, 2020. "A developmental state: How to allocate electricity efficiently in a developing country," Energy Policy, Elsevier, vol. 138(C).
    16. Chen, Zhenling & Zhang, Xiaoling & Ni, Guohua, 2020. "Decomposing capacity utilization under carbon dioxide emissions reduction constraints in data envelopment analysis: An application to Chinese regions," Energy Policy, Elsevier, vol. 139(C).
    17. Rongrong Xu & Yongxiang Wu & Ming Chen & Xuan Zhang & Wei Wu & Long Tan & Gaoxu Wang & Yi Xu & Bing Yan & Yuedong Xia, 2019. "Calculation of the contribution rate of China’s hydraulic science and technology based on a feedforward neural network," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-22, September.
    18. Liu, Yue & Sun, Huaping & Zhang, Jijian & Taghizadeh-Hesary, Farhad, 2020. "Detection of volatility regime-switching for crude oil price modeling and forecasting," Resources Policy, Elsevier, vol. 69(C).
    19. Agostino, Mariarosaria, 2024. "Extreme weather events and firms’ energy practices. The role of country governance," Energy Policy, Elsevier, vol. 192(C).
    20. Xiao, Huijuan & Wang, Daoping & Qi, Yu & Shao, Shuai & Zhou, Ya & Shan, Yuli, 2021. "The governance-production nexus of eco-efficiency in Chinese resource-based cities: A two-stage network DEA approach," Energy Economics, Elsevier, vol. 101(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:spr:endesu:v:26:y:2024:i:11:d:10.1007_s10668-023-03757-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.