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Technology-sharing strategy and incentive mechanism for R&D teams of manufacturing enterprises

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  • Zhang, Hao
  • Wang, Mingyue
  • Cheng, Zhixuan
  • Wan, Ling

Abstract

Technology innovation is a necessary condition for manufacturing enterprises to maintain competitiveness. As the central part of the national innovation system, enterprises must avoid redundant research and development (R&D) input and blind competition; therefore, it is crucial to guide technology-sharing of R&D teams in enterprises. An evolutionary game model for the analysis of agents’ strategy choice between upstream and downstream R&D teams is established. It shows that the technology-sharing strategy chosen by the R&D teams is closely related to the sharable coefficient of technology, and also closely related to the benefits obtained through free-riding. As the sharable coefficient of technology of upstream and downstream R&D teams A and B is continuously changing, four evolutionary stable equilibrium strategies appear in turn. The coefficient of synergy benefits, the capacity of technology absorption, and the sharable coefficient of technology have a positive correlation with the sum of direct benefits and synergy benefits; the technology transfer costs, the capability difference costs, risk factors, and the relative amount of technology-sharing are the critical factors negatively affecting the technology-sharing of the upstream and downstream R&D teams. A specific compensation mechanism can reduce the cost of sharing and increase the willingness to share technology. At the same time, as the internal incentive factors changes, the technology-sharing system tends to converge to {technology-sharing, technology-sharing}, thus providing decision support for the formulation and effective evaluation of manufacturing innovation policies.

Suggested Citation

  • Zhang, Hao & Wang, Mingyue & Cheng, Zhixuan & Wan, Ling, 2020. "Technology-sharing strategy and incentive mechanism for R&D teams of manufacturing enterprises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).
  • Handle: RePEc:eee:phsmap:v:555:y:2020:i:c:s0378437120302521
    DOI: 10.1016/j.physa.2020.124546
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    Cited by:

    1. Na Yu & Chunfeng Zhao, 2021. "Chain Innovation Mechanism of the Manufacturing Industry in the Yangtze River Delta of China Based on Evolutionary Game," Sustainability, MDPI, vol. 13(17), pages 1-20, August.
    2. Wang, Ding & Guo, Peng & Kilgour, D. Marc & Ponnambalam, Kumaraswamy & Hipel, Keith W., 2022. "The evolution of R&D collaboration in inter-organizational project networks: Effects of reference points for competitive preference," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 591(C).
    3. Qiang Mu & Peng Guo & Ding Wang, 2022. "Optimal Subsidy Support for the Provision of Elderly Care Services in China Based on the Evolutionary Game Analysis," IJERPH, MDPI, vol. 19(5), pages 1-20, February.

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