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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
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    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. 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.
    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. Wang, Jian, 2016. "Knowledge creation in collaboration networks: Effects of tie configuration," Research Policy, Elsevier, vol. 45(1), pages 68-80.
    5. 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.
    6. Armen A. Alchian, 1950. "Uncertainty, Evolution, and Economic Theory," Journal of Political Economy, University of Chicago Press, vol. 58(3), pages 211-211.
    7. 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.
    8. Corey C. Phelps & Ralph Heidl & Anu Wadhwa, 2012. "Networks, knowledge, and knowledge networks: A critical review and research agenda," Post-Print hal-00715591, HAL.
    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. 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.
    11. Jasjit Singh, 2005. "Collaborative Networks as Determinants of Knowledge Diffusion Patterns," Management Science, INFORMS, vol. 51(5), pages 756-770, May.
    12. 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).
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. Xia Gao & Jiancheng Guan, 2012. "Network model of knowledge diffusion," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(3), pages 749-762, March.
    18. 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.
    Full references (including those not matched with items on IDEAS)

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