IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v127y2022i7d10.1007_s11192-022-04416-4.html
   My bibliography  Save this article

Modeling and simulation of knowledge creation and diffusion in an industry-university-research cooperative innovation network: a case study of China’s new energy vehicles

Author

Listed:
  • Xia Cao

    (Harbin Engineering University)

  • Chuanyun Li

    (Harbin Engineering University)

  • Jinqiu Li

    (Harbin Engineering University)

  • Yunchang Li

    (Harbin Engineering University)

Abstract

Taking the industry-university-research cooperative innovation network in the field of new energy vehicles in China as the research object, a model of knowledge creation and diffusion is constructed based on the interaction between network structure and knowledge creation and diffusion. Complex network theory and simulation analysis methods are applied to analyze the evolution law of knowledge creation and diffusion in the industry-university-research cooperative innovation network. The results show that the industry-university-research cooperative innovation network in the field of new energy vehicles has the characteristics of a weighted scale-free network. The overall knowledge level of the network first shows a trend of slow growth and then one of rapid growth, while the growth rate of knowledge first shows a trend of gradually decreasing first and then stable. The greater the degree of the innovator and the higher its knowledge level, the more stable that innovator’s cooperative relationships are and the stronger its knowledge diffusion capacity. The knowledge diffusion model and network structure cause the emergence of sudden changes in the network. Knowledge diffusion constraints and network structure are the keys to knowledge creation and diffusion. With the passage of time, the differentiation among innovators in terms of knowledge level gradually increases, and the role of hub university-research institutions in knowledge creation and diffusion becomes increasingly prominent. Finally, we provide some countermeasures and suggestions to promote the development of the new energy vehicle industry.

Suggested Citation

  • Xia Cao & Chuanyun Li & Jinqiu Li & Yunchang Li, 2022. "Modeling and simulation of knowledge creation and diffusion in an industry-university-research cooperative innovation network: a case study of China’s new energy vehicles," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 3935-3957, July.
  • Handle: RePEc:spr:scient:v:127:y:2022:i:7:d:10.1007_s11192-022-04416-4
    DOI: 10.1007/s11192-022-04416-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-022-04416-4
    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/s11192-022-04416-4?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. Konno, Tomohiko, 2016. "Knowledge spillover processes as complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1207-1214.
    2. Wang, Jian, 2016. "Knowledge creation in collaboration networks: Effects of tie configuration," Research Policy, Elsevier, vol. 45(1), pages 68-80.
    3. Cowan, Robin & Jonard, Nicolas, 2004. "Network structure and the diffusion of knowledge," Journal of Economic Dynamics and Control, Elsevier, vol. 28(8), pages 1557-1575, June.
    4. Corey C. Phelps & Ralph Heidl & Anu Wadhwa, 2012. "Networks, knowledge, and knowledge networks: A critical review and research agenda," Post-Print hal-00715591, HAL.
    5. H. Kelejian, Harry & Prucha, Ingmar R., 2001. "On the asymptotic distribution of the Moran I test statistic with applications," Journal of Econometrics, Elsevier, vol. 104(2), pages 219-257, September.
    6. Xia Gao & Jiancheng Guan, 2012. "Network model of knowledge diffusion," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(3), pages 749-762, March.
    7. Xie, Xuemei & Fang, Liangxiu & Zeng, Saixing, 2016. "Collaborative innovation network and knowledge transfer performance: A fsQCA approach," Journal of Business Research, Elsevier, vol. 69(11), pages 5210-5215.
    8. Jian-Guo Liu & Guang-Yong Yang & Zhao-Long Hu, 2014. "A Knowledge Generation Model via the Hypernetwork," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-8, March.
    9. Olav Sorenson & Jan W. Rivkin & Lee Fleming, 2010. "Complexity, Networks and Knowledge Flows," Chapters, in: Ron Boschma & Ron Martin (ed.), The Handbook of Evolutionary Economic Geography, chapter 15, Edward Elgar Publishing.
    10. Xuan Liu & Shan Jiang & Hsinchun Chen & Catherine A. Larson & Mihail C. Roco, 2015. "Modeling knowledge diffusion in scientific innovation networks: an institutional comparison between China and US with illustration for nanotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1953-1984, December.
    11. Armen A. Alchian, 1950. "Uncertainty, Evolution, and Economic Theory," Journal of Political Economy, University of Chicago Press, vol. 58(3), pages 211-211.
    12. Liu, Mengmeng & Ma, Yinghong & Liu, Zhiyuan & You, Xuemei, 2017. "An IUR evolutionary game model on the patent cooperate of Shandong China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 475(C), pages 11-23.
    13. Michael Fritsch & Martina Kauffeld-Monz, 2010. "The impact of network structure on knowledge transfer: an application of social network analysis in the context of regional innovation networks," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 44(1), pages 21-38, February.
    14. Jasjit Singh, 2005. "Collaborative Networks as Determinants of Knowledge Diffusion Patterns," Management Science, INFORMS, vol. 51(5), pages 756-770, May.
    15. Linares, Ian Marques Porto & De Paulo, Alex Fabianne & Porto, Geciane Silveira, 2019. "Patent-based network analysis to understand technological innovation pathways and trends," Technology in Society, Elsevier, vol. 59(C).
    16. Niemann, Helen & Moehrle, Martin G. & Frischkorn, Jonas, 2017. "Use of a new patent text-mining and visualization method for identifying patenting patterns over time: Concept, method and test application," Technological Forecasting and Social Change, Elsevier, vol. 115(C), pages 210-220.
    17. Mei Hsiu-Ching Ho & Vincent H. Lin & John S. Liu, 2014. "Exploring knowledge diffusion among nations: a study of core technologies in fuel cells," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(1), pages 149-171, July.
    18. Tur, Elena M. & Azagra-Caro, Joaquín M., 2018. "The coevolution of endogenous knowledge networks and knowledge creation," Journal of Economic Behavior & Organization, Elsevier, vol. 145(C), pages 424-434.
    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. Mao, Chongfeng & Yu, Xianyun & Zhou, Qing & Harms, Rainer & Fang, Gang, 2020. "Knowledge growth in university-industry innovation networks – Results from a simulation study," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    2. Xia Cao & Chuanyun Li & Wei Chen & Jinqiu Li & Chaoran Lin, 2020. "Research on the invulnerability and optimization of the technical cooperation innovation network based on the patent perspective—A case study of new energy vehicles," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-19, September.
    3. Yue, Zenghui & Xu, Haiyun & Yuan, Guoting & Pang, Hongshen, 2019. "Modeling study of knowledge diffusion in scientific collaboration networks based on differential dynamics: A case study in graphene field," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 375-391.
    4. Jiang He & M. Hosein Fallah, 2014. "Dynamics of Inventor Networks and the Evolution of Technology Clusters," International Journal of Urban and Regional Research, Wiley Blackwell, vol. 38(6), pages 2174-2200, November.
    5. Abbasiharofteh, Milad & Kogler, Dieter F. & Lengyel, Balázs, 2023. "Atypical combinations of technologies in regional co-inventor networks," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 52(10), pages 1-1.
    6. Clayton, Paige & Lanahan, Lauren & Nelson, Andrew, 2022. "Dissecting diffusion: Tracing the plurality of factors that shape knowledge diffusion," Research Policy, Elsevier, vol. 51(1).
    7. Pablo Galaso & Jaromír Kovářík, 2021. "Collaboration networks, geography and innovation: Local and national embeddedness," Papers in Regional Science, Wiley Blackwell, vol. 100(2), pages 349-377, April.
    8. Uwe Cantner & Holger Graf, 2010. "Growth, Development and Structural Change of Innovator Networks: The Case of Jena," Chapters, in: Ron Boschma & Ron Martin (ed.), The Handbook of Evolutionary Economic Geography, chapter 17, Edward Elgar Publishing.
    9. Jason P. Davis & Vikas A. Aggarwal, 2020. "Knowledge mobilization in the face of imitation: Microfoundations of knowledge aggregation and firm‐level innovation," Strategic Management Journal, Wiley Blackwell, vol. 41(11), pages 1983-2014, November.
    10. Evangelos Ioannidis & Nikos Varsakelis & Ioannis Antoniou, 2021. "Intelligent Agents in Co-Evolving Knowledge Networks," Mathematics, MDPI, vol. 9(1), pages 1-17, January.
    11. Ioannidis, Evangelos & Varsakelis, Nikos & Antoniou, Ioannis, 2018. "Experts in Knowledge Networks: Central Positioning and Intelligent Selections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 890-905.
    12. Cantner, Uwe & Graf, Holger & Herrmann, Johannes & Kalthaus, Martin, 2016. "Inventor networks in renewable energies: The influence of the policy mix in Germany," Research Policy, Elsevier, vol. 45(6), pages 1165-1184.
    13. Lee Fleming & Charles King & Adam I. Juda, 2007. "Small Worlds and Regional Innovation," Organization Science, INFORMS, vol. 18(6), pages 938-954, December.
    14. Bulent Ozel, 2012. "Collaboration structure and knowledge diffusion in Turkish management academia," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(1), pages 183-206, October.
    15. Raisi, Hossein & Baggio, Rodolfo & Barratt-Pugh, Llandis & Willson, Gregory, 2020. "A network perspective of knowledge transfer in tourism," Annals of Tourism Research, Elsevier, vol. 80(C).
    16. Ioannidis, Evangelos & Varsakelis, Nikos & Antoniou, Ioannis, 2017. "False Beliefs in Unreliable Knowledge Networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 275-295.
    17. Liming Zhao & Haihong Zhang & Wenqing Wu, 2019. "Cooperative knowledge creation in an uncertain network environment based on a dynamic knowledge supernetwork," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 657-685, May.
    18. Wang, Haiying & Moore, Jack Murdoch & Wang, Jun & Small, Michael, 2021. "The distinct roles of initial transmission and retransmission in the persistence of knowledge in complex networks," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    19. Tubiana, Matteo & Miguelez, Ernest & Moreno, Rosina, 2022. "In knowledge we trust: Learning-by-interacting and the productivity of inventors," Research Policy, Elsevier, vol. 51(1).
    20. Giuseppe Calignano & Rune Dahl Fitjar, 2017. "Strengthening relationships in clusters: How effective is an indirect policy measure carried out in a peripheral technology district?," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 59(1), pages 139-169, July.

    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:scient:v:127:y:2022:i:7:d:10.1007_s11192-022-04416-4. 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.