IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0286096.html
   My bibliography  Save this article

Innovation network structure, government R&D investment and regional innovation efficiency: Evidence from China

Author

Listed:
  • Xiao-Yan Cao
  • Xiang-Li Wu
  • Li-Min Wang

Abstract

Based on the panel data of 30 provinces in China from 2011 to 2019, this paper uses a two-stage DEA model to measure regional innovation efficiency, then non-parametric test is used to examine the impact of innovation network structure and government R&D investment on regional innovation efficiency. The results show that, at the provincial level, innovation efficiency of regional R&D is not necessarily in direct proportion to the innovation efficiency in the commercialization stage. Commercialization efficiency is not necessarily high in provinces with high technical R&D efficiency. At the national level, the innovation efficiency gap between our country’s R&D and commercialization stage is small, indicating that the development of the national innovation efficiency is more and more balanced. Innovation network structure can promote the R&D efficiency, but has no significant effect on the commercialization efficiency. Government R&D investment helps to improve the R&D efficiency, but it is not conducive to the improvement of commercialization efficiency. The interaction between innovation network structure and government R&D investment will have compound effects on regional innovation efficiency; the region with underdeveloped innovation network structure can increase the government R&D investment to make it have a higher level of R&D. This paper provides insights into how to improve innovation efficiency in different social networks and policy environments.

Suggested Citation

  • Xiao-Yan Cao & Xiang-Li Wu & Li-Min Wang, 2023. "Innovation network structure, government R&D investment and regional innovation efficiency: Evidence from China," PLOS ONE, Public Library of Science, vol. 18(5), pages 1-20, May.
    • Handle: RePEc:plo:pone00:0286096
    DOI: 10.1371/journal.pone.0286096
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0286096
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0286096&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0286096?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
    ---><---

    References listed on IDEAS

    as
    1. Kaihua Chen & Jiancheng Guan, 2012. "Measuring the Efficiency of China's Regional Innovation Systems: Application of Network Data Envelopment Analysis (DEA)," Regional Studies, Taylor & Francis Journals, vol. 46(3), pages 355-377, April.
    2. Eisingerich, Andreas B. & Bell, Simon J. & Tracey, Paul, 2010. "How can clusters sustain performance? The role of network strength, network openness, and environmental uncertainty," Research Policy, Elsevier, vol. 39(2), pages 239-253, March.
    3. Melissa A. Schilling & Corey C. Phelps, 2007. "Interfirm Collaboration Networks: The Impact of Large-Scale Network Structure on Firm Innovation," Management Science, INFORMS, vol. 53(7), pages 1113-1126, July.
    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. Sun, Yutao, 2016. "The structure and dynamics of intra- and inter-regional research collaborative networks: The case of China (1985–2008)," Technological Forecasting and Social Change, Elsevier, vol. 108(C), pages 70-82.
    2. Jiancheng Guan & Yan Yan & Jingjing Zhang, 2015. "How do collaborative features affect scientific output? Evidences from wind power field," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 333-355, January.
    3. Viacheslav Iurkov & Gabriel R G Benito, 2020. "Change in domestic network centrality, uncertainty, and the foreign divestment decisions of firms," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 51(5), pages 788-812, July.
    4. Joan Crespo & Frédéric Amblard & Jérôme Vicente, 2015. "Simulating micro behaviours and structural properties of knowledge networks: toward a “one size fits one” cluster policy," Papers in Evolutionary Economic Geography (PEEG) 1503, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Feb 2015.
    5. Guan, Jiancheng & Zhang, Jingjing & Yan, Yan, 2015. "The impact of multilevel networks on innovation," Research Policy, Elsevier, vol. 44(3), pages 545-559.
    6. Mingting Kou & Yi Zhang & Yu Zhang & Kaihua Chen & Jiancheng Guan & Senmao Xia, 2020. "Does gender structure influence R&D efficiency? A regional perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 477-501, January.
    7. Joan Crespo & Jérôme Vicente & Frédéric Amblard, 2016. "Micro-behaviors and structural properties of knowledge networks: toward a ‘one size fits one’ cluster policy," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 25(6), pages 533-552, September.
    8. Li, Fengshu & Andries, Petra & Pellens, Maikel & Xu, Jianzhong, 2021. "The importance of large firms for generating economic value from subsidized technological innovation: A regional perspective," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    9. Avimanyu Datta, 2016. "Antecedents To Radical Innovations: A Longitudinal Look At Firms In The Information Technology Industry By Aggregation Of Patents," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 20(07), pages 1-31, October.
    10. Chen, Ping-Chuan & Hung, Shiu-Wan, 2016. "An actor-network perspective on evaluating the R&D linking efficiency of innovation ecosystems," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 303-312.
    11. Duk Hee Lee & Il Won Seo & Ho Chull Choe & Hee Dae Kim, 2012. "Collaboration network patterns and research performance: the case of Korean public research institutions," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(3), pages 925-942, June.
    12. Schilling, Melissa A. & Green, Elad, 2011. "Recombinant search and breakthrough idea generation: An analysis of high impact papers in the social sciences," Research Policy, Elsevier, vol. 40(10), pages 1321-1331.
    13. Dzikowski Piotr, 2016. "The Importance of Vertical Linkages for the Innovation Activity of Medium-High and High Technology Industries in Poland," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 51(1), pages 90-103, September.
    14. Muhamed Kudic & Wilfried Ehrenfeld & Toralf Pusch, 2015. "On the trail of core–periphery patterns in innovation networks: measurements and new empirical findings from the German laser industry," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 55(1), pages 187-220, October.
    15. Cho, Chanho & Halford, Joseph T. & Hsu, Scott & Ng, Lilian, 2016. "Do managers matter for corporate innovation?," Journal of Corporate Finance, Elsevier, vol. 36(C), pages 206-229.
    16. Amalesh Sharma & V. Kumar & Jun Yan & Sourav Bikash Borah & Anirban Adhikary, 2019. "Understanding the structural characteristics of a firm’s whole buyer–supplier network and its impact on international business performance," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 50(3), pages 365-392, April.
    17. Mueller, Matthias & Bogner, Kristina & Buchmann, Tobias & Kudic, Muhamed, 2015. "Simulating knowledge diffusion in four structurally distinct networks: An agent-based simulation model," Hohenheim Discussion Papers in Business, Economics and Social Sciences 05-2015, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    18. Mammadaliyev, Farid & Gilsing, Victor & Knoben, J., 2024. "How do firms adapt their portfolios of external collaborations to changing internal organizational attributes? The moderating role of firm age," Other publications TiSEM 56c854b7-ed86-4830-843e-c, Tilburg University, School of Economics and Management.
    19. Xaver Neumeyer & Susana C. Santos & Michael H. Morris, 2019. "Who is left out: exploring social boundaries in entrepreneurial ecosystems," The Journal of Technology Transfer, Springer, vol. 44(2), pages 462-484, April.
    20. Gabriela Citlalli López-Torres & Gonzalo Maldonado Guzmán & Sandra Yesenia Pinzón Castro & Ricardo García Ramírez, 2016. "Collaboration and innovation activities in SMEs," Contaduría y Administración, Accounting and Management, vol. 61(3), pages 568-581, Julio-Sep.

    More about this item

    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:plo:pone00:0286096. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.