IDEAS home Printed from https://ideas.repec.org/a/spr/endesu/v27y2025i8d10.1007_s10668-024-04768-2.html
   My bibliography  Save this article

Does technological innovation promote green development in the Yangtze River Economic Belt? Based on the spatial econometric analysis

Author

Listed:
  • Rui Ding

    (Chongqing University of Science and Technology)

  • Fangcheng Sun

    (Chongqing Technology and Business University)

  • Tingyong Zhong

    (Chongqing Technology and Business University)

Abstract

The Yangtze River Economic Belt (YREB) is a prominent strategic region in China, and technological innovation, being a core development driver, playing critical support role to facilitate YREB’s green development. This article evaluates green development level of YREB according to Driver-Pressure-State-Impact-Response (DPSIR) framework, and explores influences of technological innovation on the regional green development employing spatial econometric model. Research results manifest that green development reveals a continuous rising tendency, and it is generally better in lower reaches. Meanwhile, local green development plays positive spatial spillover effects on neighboring areas. Secondly, technological innovation plays an obvious driving function on local green development in the whole YREB, while only upper and middle reaches witness significantly positive spatial spillover effects. Thirdly, mechanism analysis result implies that the technological innovation could facilitate the regional green development through three paths: improving technological efficiency, decreasing pollution emission, and upgrading industrial structure. Furthermore, discussions with panel threshold models show that different impacts of technological innovation on green development depend on economic and technological factors. An increased level of technological and economic level will multiply influence that technological innovation on green development.

Suggested Citation

  • Rui Ding & Fangcheng Sun & Tingyong Zhong, 2025. "Does technological innovation promote green development in the Yangtze River Economic Belt? Based on the spatial econometric analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(8), pages 19319-19353, August.
  • Handle: RePEc:spr:endesu:v:27:y:2025:i:8:d:10.1007_s10668-024-04768-2
    DOI: 10.1007/s10668-024-04768-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10668-024-04768-2
    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/s10668-024-04768-2?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    2. Ben Youssef, Adel & Boubaker, Sabri & Omri, Anis, 2018. "Entrepreneurship and sustainability: The need for innovative and institutional solutions," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 232-241.
    3. Wang, Yujie & Chen, Hong & Long, Ruyin & Liu, Bei & Jiang, Shiyan & Yang, Xingxing & Yang, Menghua, 2021. "Evaluating green development level of mineral resource-listed companies: Based on a “dark green” assessment framework," Resources Policy, Elsevier, vol. 71(C).
    4. Jin, Peizhen & Peng, Chong & Song, Malin, 2019. "Macroeconomic uncertainty, high-level innovation, and urban green development performance in China," China Economic Review, Elsevier, vol. 55(C), pages 1-18.
    5. Shahab, Yasir & Hussain, Tanveer & Wang, Peng & Zhong, Ma & Kumar, Satish, 2023. "Business groups and environmental violations: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 85(C).
    6. Lee, Chi-Chuan & Lee, Chien-Chiang, 2022. "How does green finance affect green total factor productivity? Evidence from China," Energy Economics, Elsevier, vol. 107(C).
    7. Ehara, Makoto & Hyakumura, Kimihiko & Sato, Ren'ya & Kurosawa, Kiyoshi & Araya, Kunio & Sokh, Heng & Kohsaka, Ryo, 2018. "Addressing Maladaptive Coping Strategies of Local Communities to Changes in Ecosystem Service Provisions Using the DPSIR Framework," Ecological Economics, Elsevier, vol. 149(C), pages 226-238.
    8. François Perroux, 1950. "Economic Space: Theory and Applications," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 64(1), pages 89-104.
    9. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
    10. Zhai, Xueqi & An, Yunfei, 2021. "The relationship between technological innovation and green transformation efficiency in China: An empirical analysis using spatial panel data," Technology in Society, Elsevier, vol. 64(C).
    11. Mark Crosby, 2000. "Patents, Innovation and Growth," The Economic Record, The Economic Society of Australia, vol. 76(234), pages 255-262, September.
    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. Wang, Jianda & Guo, Dongsheng, 2023. "Siphon and radiation effects of ICT agglomeration on green total factor productivity: Evidence from a spatial Durbin model," Energy Economics, Elsevier, vol. 126(C).
    2. Huiying Zhou, 2025. "Does FDI quality boost the city-level green total factor productivity in the Yangtze River Delta, China?," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 74(3), pages 1-25, September.
    3. Hu, Hui & Qi, Shaozhou & Chen, Yuanzhi, 2023. "Using green technology for a better tomorrow: How enterprises and government utilize the carbon trading system and incentive policies," China Economic Review, Elsevier, vol. 78(C).
    4. Zhang, Jinyue & Sun, Zhenglin, 2025. "Energy-environmental efficiency enhancement using green finance through spatio-temporal heterogeneity and dynamic regulatory mechanisms: Multiple perspectives study," Renewable Energy, Elsevier, vol. 240(C).
    5. Yunyan Jiang & Feng Deng, 2022. "Multi-Dimensional Threshold Effects of the Digital Economy on Green Economic Growth?—New Evidence from China," Sustainability, MDPI, vol. 14(19), pages 1-22, October.
    6. Yuxin Fang & Hongjun Cao & Jihui Sun, 2022. "Impact of Artificial Intelligence on Regional Green Development under China’s Environmental Decentralization System—Based on Spatial Durbin Model and Threshold Effect," IJERPH, MDPI, vol. 19(22), pages 1-27, November.
    7. Qi Cui & Xiaoyu Ma & Sisi Zhang, 2025. "The impact of green finance on energy saving and carbon reduction: evidence from Chinese cities," Economic Change and Restructuring, Springer, vol. 58(1), pages 1-33, February.
    8. Lin, Boqiang & Chen, Yu, 2020. "Transportation infrastructure and efficient energy services: A perspective of China's manufacturing industry," Energy Economics, Elsevier, vol. 89(C).
    9. Li, Lei & Zheng, Yifan & Ma, Shaojun & Ma, Xiaoyu & Zuo, Jian & Goodsite, Michael, 2025. "Unfavorable weather, favorable insights: Exploring the impact of extreme climate on green total factor productivity," Economic Analysis and Policy, Elsevier, vol. 85(C), pages 626-640.
    10. Zhu, Bei & Nakaishi, Tomoaki & Kagawa, Shigemi, 2024. "Neighbor's profit or Neighbor's beggar? Evidence from China's low carbon cities pilot scheme on green development," Energy Policy, Elsevier, vol. 195(C).
    11. Siyu Han & Mengcheng Wang & Qi Liu & Renyang Wang & Guoliang Ou & Lu Zhang, 2022. "The Influence of Land Disposition Derived from Land Finance on Urban Innovation in China: Mechanism Discussion and Empirical Evidence," IJERPH, MDPI, vol. 19(6), pages 1-23, March.
    12. Wenhui Luo & Gennian Tang & Peiling Yang & Chunxia Jia & Ruize Yang, 2024. "Examining Digital Economy’s Role in Urban Green Development: A Study of the Yangtze River Delta Region," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 11250-11285, September.
    13. Jin, Peizhen & Mangla, Sachin Kumar & Song, Malin, 2022. "The power of innovation diffusion: How patent transfer affects urban innovation quality," Journal of Business Research, Elsevier, vol. 145(C), pages 414-425.
    14. Yongna Zou & Qingping Cheng & Hanyu Jin & Xuefu Pu, 2023. "Evaluation of Green Agricultural Development and Its Influencing Factors under the Framework of Sustainable Development Goals: Case Study of Lincang City, an Underdeveloped Mountainous Region of China," Sustainability, MDPI, vol. 15(15), pages 1-22, August.
    15. Hongge Zhu & Zhenhuan Chen & Shaopeng Zhang & Wencheng Zhao, 2022. "The Role of Government Innovation Support in the Process of Urban Green Sustainable Development: A Spatial Difference-in-Difference Analysis Based on China’s Innovative City Pilot Policy," IJERPH, MDPI, vol. 19(13), pages 1-19, June.
    16. Guo, Pengwei & He, Yongda & Scrimgeour, Frank & Shao, Shuai & Yu, Yuting, 2024. "The impact of natural resource dependency on green economic growth: A business environment perspective," Technological Forecasting and Social Change, Elsevier, vol. 208(C).
    17. Zhen Zeng & Xianzhong Mu, 2024. "Can the Development of Renewable Energy Improve Total-Factor Carbon Emissions Efficiency? Evidence from 30 Provinces in China," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 14(6), pages 1-16.
    18. Tang, Xinmeng & Zhou, Xiaoguang, 2023. "Impact of green finance on renewable energy development: A spatiotemporal consistency perspective," Renewable Energy, Elsevier, vol. 204(C), pages 320-337.
    19. Jinlin Li & Litai Chen & Ying Chen & Jiawen He, 2022. "Digital economy, technological innovation, and green economic efficiency—Empirical evidence from 277 cities in China," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(3), pages 616-629, April.
    20. Li, Haichao & Su, Yuqi & Ding, Chante Jian & Tian, Gary Gang & Wu, Zhan, 2024. "Unveiling the green innovation paradox: Exploring the impact of carbon emission reduction on corporate green technology innovation," Technological Forecasting and Social Change, Elsevier, vol. 207(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:27:y:2025:i:8:d:10.1007_s10668-024-04768-2. 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.