IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i12p5587-d1681317.html
   My bibliography  Save this article

Technology Spillovers, Collaborative Innovation and High-Quality Development—A Comparative Analysis Based on the Yangtze River Delta and Beijing-Tianjin-Hebei City Clusters

Author

Listed:
  • Yan Qi

    (School of Economics, Inner Mongolia University of Finance and Economics, Hohhot 010070, China
    School of Economics, Central University of Finance and Economics, Beijing 102206, China
    These authors contributed equally to this work.)

  • Yiwei Liu

    (School of Economics, Central University of Finance and Economics, Beijing 102206, China
    These authors contributed equally to this work.)

Abstract

Exploring the mechanism of science and technology innovation spillover effect and collaborative innovation on the high-quality development of urban agglomerations is of great practical significance for implementing the innovation-driven development strategy. Based on the panel data of prefecture-level cities from 2012 to 2020, this study uses web crawler technology to obtain cooperative invention patent data, combines the social network analysis method to construct collaborative innovation networks, constructs a high-quality development indicator system from six dimensions such as the degree of marketization and the industrial system, and adopts the spatial Durbin model to reveal the regional innovation spillover effect. The comparative study based on the Yangtze River Delta (YRD) and Beijing-Tianjin-Hebei (BTH) urban agglomerations found the following: (1) There is significant spatial heterogeneity in science and technology innovation, with the YRD showing a positive spillover trend and BTH showing a significant negative spillover trend; (2) The collaborative innovation network shows differentiated characteristics, with the YRD having a higher density of the network and forming a multi-centered structure, and BTH maintaining the pattern of single-core radiation; (3) There is a horse-tracing effect in high-quality development, with the average score of YRD The average score of YRD is significantly higher than that of Beijing-Tianjin-Hebei, and the indicators of several dimensions are better. Based on these conclusions, city clusters should further strengthen the construction of collaborative innovation networks among cities and enhance the capacity of neighboring cities to undertake innovation, to give full play to the spillover effect and driving effect of innovation on high-quality development.

Suggested Citation

  • Yan Qi & Yiwei Liu, 2025. "Technology Spillovers, Collaborative Innovation and High-Quality Development—A Comparative Analysis Based on the Yangtze River Delta and Beijing-Tianjin-Hebei City Clusters," Sustainability, MDPI, vol. 17(12), pages 1-28, June.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:12:p:5587-:d:1681317
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/12/5587/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/12/5587/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Guan, Jiancheng & Liu, Na, 2016. "Exploitative and exploratory innovations in knowledge network and collaboration network: A patent analysis in the technological field of nano-energy," Research Policy, Elsevier, vol. 45(1), pages 97-112.
    2. Rosina Moreno & Raffaele Paci & Stefano Usai, 2005. "Spatial Spillovers and Innovation Activity in European Regions," Environment and Planning A, , vol. 37(10), pages 1793-1812, October.
    3. Bruno Cassiman & Reinhilde Veugelers, 2002. "R&D Cooperation and Spillovers: Some Empirical Evidence from Belgium," American Economic Review, American Economic Association, vol. 92(4), pages 1169-1184, September.
    4. Fei Fan & Huan Lian & Song Wang, 2020. "Can regional collaborative innovation improve innovation efficiency? An empirical study of Chinese cities," Growth and Change, Wiley Blackwell, vol. 51(1), pages 440-463, March.
    5. Yongming Zhu & Xiaoyu Zhou & Junjie Li & Fan Wang, 2022. "Technological Innovation, Fiscal Decentralization, Green Development Efficiency: Based on Spatial Effect and Moderating Effect," Sustainability, MDPI, vol. 14(7), pages 1-16, April.
    6. Masahisa Fujita & Jacques‐François Thisse, 2003. "Does Geographical Agglomeration Foster Economic Growth? And Who Gains and Loses from It?," The Japanese Economic Review, Japanese Economic Association, vol. 54(2), pages 121-145, June.
    7. Romer, Paul M, 1990. "Endogenous Technological Change," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 71-102, October.
    8. Funke, Michael & Niebuhr, Annekatrin, 2000. "Spatial R&D spillovers and economic growth: Evidence from West Germany," HWWA Discussion Papers 98, Hamburg Institute of International Economics (HWWA).
    9. Dixit, Avinash K & Stiglitz, Joseph E, 1977. "Monopolistic Competition and Optimum Product Diversity," American Economic Review, American Economic Association, vol. 67(3), pages 297-308, June.
    10. Barro, Robert J & Sala-i-Martin, Xavier, 1997. "Technological Diffusion, Convergence, and Growth," Journal of Economic Growth, Springer, vol. 2(1), pages 1-26, March.
    11. Xia Gao & Jiancheng Guan & Ronald Rousseau, 2011. "Mapping collaborative knowledge production in China using patent co-inventorships," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(2), pages 343-362, August.
    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. Hongwei Dai & Yiwei Liu & Heyang Li & Aochen Cao, 2024. "Depth and Width of Collaborative Innovation Networks and High-Quality Development," Sustainability, MDPI, vol. 16(14), pages 1-30, July.
    2. Gancia, Gino & Zilibotti, Fabrizio, 2005. "Horizontal Innovation in the Theory of Growth and Development," Handbook of Economic Growth, in: Philippe Aghion & Steven Durlauf (ed.), Handbook of Economic Growth, edition 1, volume 1, chapter 3, pages 111-170, Elsevier.
    3. Fabio Cerina & Francesco Pigliaru, 2007. "Agglomeration and Growth in the NEG: A Critical Assessment," Chapters, in: Bernard Fingleton (ed.), New Directions in Economic Geography, chapter 5, Edward Elgar Publishing.
    4. Serrano, Guadalupe & Cabrer, Bernardí, 2000. "Technological "Catch-Up" And Trade Flows. A Panel Data Approach," ERSA conference papers ersa00p152, European Regional Science Association.
    5. Cerina, Fabio & Mureddu, Francesco, 2014. "Is agglomeration really good for growth? Global efficiency, interregional equity and uneven growth," Journal of Urban Economics, Elsevier, vol. 84(C), pages 9-22.
    6. Michael Peneder & Karl Aiginger & Gernot Hutschenreiter & Markus Marterbauer, 2001. "Structural Change and Economic Growth," WIFO Studies, WIFO, number 20668.
    7. Thomas Doring & Jan Schnellenbach, 2006. "What do we know about geographical knowledge spillovers and regional growth?: A survey of the literature," Regional Studies, Taylor & Francis Journals, vol. 40(3), pages 375-395.
    8. Ugo Fratesi, 2003. "Innovation Diffusion and the Evolution of Regional Disparities," ERSA conference papers ersa03p327, European Regional Science Association.
    9. Kyoko Hirose & Kazuhiro Yamamoto, 2007. "Knowledge spillovers, location of industry, and endogenous growth," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 41(1), pages 17-30, March.
    10. Yan Yan & Jiancheng Guan, 2018. "How multiple networks help in creating knowledge: evidence from alternative energy patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 51-77, April.
    11. Mateo Hoyos, 2025. "North–South trade, technology diffusion, and uneven development," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 34(4), pages 613-633, May.
    12. Antonescu, Daniela, 2013. "The Regional Development Policy of Romania in the Post-Accession Period," Working Papers of National Institute for Economic Research 131209, Institutul National de Cercetari Economice (INCE).
    13. Matthias Siller & Christoph Hauser & Janette Walde & Gottfried Tappeiner, 2014. "The Multiple Facets of Regional Innovation," Working Papers 2014-19, Faculty of Economics and Statistics, Universität Innsbruck.
    14. Wei Yang & Xiang Yu & Dian Wang & Jinrui Yang & Ben Zhang, 2021. "Spatio-temporal evolution of technology flows in China: patent licensing networks 2000–2017," The Journal of Technology Transfer, Springer, vol. 46(5), pages 1674-1703, October.
    15. Bettina Becker, 2013. "The Determinants of R&D Investment: A Survey of the Empirical Research," Discussion Paper Series 2013_09, Department of Economics, Loughborough University, revised Sep 2013.
    16. William Darity & Lewis S. Davis, 2005. "Growth, trade and uneven development," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 29(1), pages 141-170, January.
    17. Alejandro Diaz-Bautista, 2005. "Convergence and Economic Growth considering Human Capital and R&D Spillovers Convergencia y Crecimiento Economico en Mexico considerando al Capital Humano y derrames en Investigacion y Desarrollo," Urban/Regional 0506012, University Library of Munich, Germany.
    18. Spyros Arvanitis & Florian Seliger, 2014. "Imitation versus innovation," KOF Working papers 14-367, KOF Swiss Economic Institute, ETH Zurich.
    19. Abida Hafeez & Karim Bux Shah Syed & Fiza Qureshi, 2019. "Exploring the Relationship between Government R & D Expenditures and Economic Growth in a Global Perspective: A PMG Estimation Approach," International Business Research, Canadian Center of Science and Education, vol. 12(4), pages 163-174, April.
    20. Croce, M.M. & Nguyen, Thien T. & Raymond, S. & Schmid, L., 2019. "Government debt and the returns to innovation," Journal of Financial Economics, Elsevier, vol. 132(3), pages 205-225.

    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:gam:jsusta:v:17:y:2025:i:12:p:5587-:d:1681317. 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.