Knowledge Transfer Performance of China's Industry-University-Research Institute Collaboration: History
Please note this is an old version of this entry, which may differ significantly from the current revision.
Subjects: Management

Knowledge transfer performance is a key consideration in the process of R&D collaboration between companies and research institutes; how to improve the performance of knowledge transfer depends on the matching between the partners of IUR collaboration. The goal difference of industry-university-research institute collaboration partners has a negative moderating effect on the relationship between learning willingness, absorptive capacity, and knowledge transfer performance. The greater the degree of goal difference, the lower the role of the enterprise’s learning willingness and absorptive capacity to promote knowledge transfer performance. Technical knowledge difference has a significant inverted U-shaped effect on the relationship between absorptive capacity and knowledge transfer performance: a high degree of technical knowledge difference weakens the effects of absorptive capacity on knowledge transfer performance, while a low degree of technical knowledge difference will also negatively moderate the effects of absorptive capacity on knowledge transfer performance.

  • industry-university-research institute collaboration
  • knowledge transfer performance

1. Theoretical Implications

First, the technical knowledge difference of collaboration participants has a significant inverted U–shaped moderating effect on the relationship between absorptive capacity and knowledge transfer performance. As Chen et al. [1] pointed out, if the technical knowledge difference among the partner difference of IUR collaborations is too large, even if the enterprises have strong absorption capacity, they will eventually be unable to digest and use the valuable knowledge from the other side effectively because of the huge knowledge gap, leading to a poor knowledge transfer effect [2][3]. Similarly, if the technical knowledge differences are too small, this indicates that the knowledge depth and knowledge structure of universities and research institutes lack complementarity for enterprises [4][5]. Even if the enterprises have a strong absorption capacity, the absorbed knowledge will have little value to the enterprise, and the knowledge transfer effect will be poor [6][7]. The effect of the absorptive capacity on knowledge transfer depends on the technical knowledge difference between the two collaboration participants [8][9]. Although no specific discussion on the mechanism of effects of technical knowledge difference on knowledge transfer performance can be found in the literature [10][11][12][13], the conclusion of this study can be regarded as an extension of similar studies.
Second, the goal difference of collaboration participants has a significant moderating effect on the relationship between learning willingness, absorptive capacity, and knowledge transfer performance. Cooperative theory points out that differences must exist between different participants, and the basis of collaboration is the common goal [14][15]. Relevant studies on enterprise technology alliance collaboration have pointed out that only with common collaboration goals can both parties invest resources actively and make joint efforts to achieve collaboration goals [16][17]. Similarly, as the collaboration between organizations with different attributes, IUR has huge differences in organizational goals between the participants, and such differences have been referred to as the possibility of resource complementarity between them [18][19]. Enterprises reduce R&D costs and improve R&D efficiency and their technology system through IUR, while universities and research institutes also obtain benefits from the productization and marketization of technologies through IUR, train scientific research personnel, and refine scientific problems in practice. In other words, a basis for collaboration between enterprises, universities, and research institutes exists, but there may be differences between them in terms of specific collaboration goals, and such differences have an important influence on the effect of knowledge transfer performance [20][21]. Enterprises at different stages have different demand types (including product technology, applied generic technology, and basic generic technology) for collaborative R&D. In other words, differences in the types of technologies to be solved in R&D collaboration can be observed, and the degree of such differences in goals will have a negative effect on the effect of knowledge transfer by affecting the learning willingness and absorptive capacity of enterprises.

2. Practical Implications

The 13th Five-Year Plan of China places an emphasis on the concepts of innovation, coordination, green, opening, and sharing. IUR collaboration innovation has become an important method for improving the independent innovation capability of Chinese enterprises, and is also the main starting point in the promotion of the transformation of Chinese industry from manufacturing to innovation. The key to achieving the above goals lies in how the accurate and smooth flow of knowledge from universities and research institutes to enterprises can be promoted. On the one hand, the government must carry on scientific research system reform and promote universities and research institutes for the implementation of the service function of the social economy. On the other hand, as an important subject of the economic system, enterprises need to improve their technology system, improve their independent innovation capability, and realize the sustainable growth of core competitiveness through “self-cultivation” with the help of IUR. How can enterprises choose the right IUR partners to achieve the purpose of technological breakthrough in a better and more rapid way? This study on the influence mechanism of the difference between collaboration participants on knowledge transfer performance in this paper provides the following enlightenment for the above problems of enterprise management practice.
First, learning willingness and absorptive capacity can directly promote knowledge transfer in IUR collaboration. These results indicate that the enterprise that needs to promote knowledge transfer effect first needs to promote internal absorptive capacity and knowledge absorptive capacity, which includes, mainly, the ability to knowledge recognition, digestion, and utilization, focus on the construction of internal R&D capacity, improve the structure of the R&D team by introducing talents, and lay a solid foundation for the absorption capacity of enterprises. If enterprises lack a strong learning willingness and good absorptive capacity, they will have no intention and no ability to acquire knowledge from universities and research institutes, and the knowledge transfer in IUR collaboration will become a fool’s paradise. Chinese enterprises choose to cooperate with universities for short term interests, and lack the long term goal of improving their independent innovation capability through IUR collaboration, fundamentally leading to the poor effect of the knowledge transfer performance. Enterprises should internalize the knowledge of universities and research institutes into their knowledge reserve and prepare sufficient redundant resources for knowledge transfer from a long term strategic goal. However, learning willingness alone is not sufficient for enterprises. If they lack sufficient absorptive capacity, they may be willing, but lack the power in the face of knowledge from scientific research institutions. Therefore, enterprises should build and cultivate their internal absorptive capacity before carrying out IUR collaboration, for example, increase R&D investment; improve R&D systems, institutions and technical personnel training mechanisms; and introduce excellent external talents.
Second, to re-understand the difference in the collaboration participants and focus on the important influence on knowledge transfer performance of IUR. The IUR collaboration of China has had certain achievements and a number of failure cases, enterprises lack technical or unable to break through technical bottlenecks, need to seek the help of universities and research institutes. However, most enterprises ignore the difference between them and their partners. Due to the significant influence of the differences of the collaboration participants in knowledge transfer, ignoring the differences of the collaboration participants can ultimately reduce the collaboration between the two participants to a low probability event. Enterprises can realize the desire for technological breakthrough through the IUR under the normal coincidence of the differences between the collaboration participants.
Finally, in the selection of IUR collaboration partners, we should adhere to the actual situation of the enterprise itself as the basis, and not blindly choose high level research universities. The realization of IUR knowledge transfer performance depends on the enterprise’s strong learning willingness and its absorptive capacity, but these are only the necessary conditions for knowledge transfer performance. We need to solve the problem from the source and find partners that match with the development of the enterprise and its technical strength, to improve the efficiency of the knowledge transfer of IUR collaboration. That is, we should choose the universities with strong complementary effects in knowledge depth and knowledge structure. However, universities with little difference in collaboration goals and concepts are not cooperating blindly with the universities with strong research comprehensive strength, because this type of university has a large depth of knowledge, and their knowledge structure and system are relatively complete. Most of these cooperation efforts focus on basic and applied generic technology and, thus, have higher requirements on the absorptive capacity of enterprises.

This entry is adapted from the peer-reviewed paper 10.3390/su132313202


  1. Chen, K.; Zhang, Y.; Zhu, G.; Mu, R. Do research institutes benefit from their network positions in research collaboration networks with industries or/and universities? Technovation 2020, 94–95, 102002.
  2. Mehreen, H.; Rammal, H.G.; Pereira, V.; Del Giudice, M. Investigating the influence of absorptive capacity of recipients within cross-border transfer of knowledge: Evidence from emerging markets. Int. Mark. Rev. 2021. ahead of print.
  3. Un, C.A.; Asakawa, K. Types of R&D Collaborations and Process Innovation: The Benefit of Collaborating Upstream in the Knowledge Chain. J. Prod. Innov. Manag. 2014, 32, 138–153.
  4. Lhuillery, S.; Pfister, E. R&D cooperation and failures in innovation projects: Empirical evidence from French CIS data. Res. Policy 2009, 38, 45–57.
  5. Todo, Y.; Matous, P.; Inoue, H. The strength of long ties and the weakness of strong ties: Knowledge diffusion through supply chain networks. Res. Policy 2016, 45, 1890–1906.
  6. Wang, Q.; Zhao, L.; Chang-Richards, A.; Zhang, Y.; Li, H. Understanding the Impact of Social Capital on the Innovation Performance of Construction Enterprises: Based on the Mediating Effect of Knowledge Transfer. Sustainability 2021, 13, 5099.
  7. Cao, X.; Xing, Z.; Sun, K. Collaboration network, technology network and technological development: A patent analysis in the Chinese green technological field of energy saving. Foresight 2021, 23, 33–49.
  8. Gorman, M.E. Types of Knowledge and Their Roles in Technology Transfer. J. Technol. Transf. 2002, 27, 219–231.
  9. Karnani, F. The university’s unknown knowledge: Tacit knowledge, technology transfer and university spin-offs findings from an empirical study based on the theory of knowledge. J. Technol. Transf. 2013, 38, 235–250.
  10. Nambisan, S. Industry technical committees, technological distance, and innovation performance. Res. Policy 2013, 42, 928–940.
  11. Quintana-García, C.; Velasco, C.; Ángel, B. Innovative competence, exploration and exploitation: The influence of technological diversification. Res. Policy 2008, 37, 492–507.
  12. Schulze, A.; Brojerdi, G.J.C. The Effect of the Distance between Partners’ Knowledge Components on Collaborative Innovation. Eur. Manag. Rev. 2012, 9, 85–98.
  13. Belderbos, R.; Cassiman, B.; Faems, D.; Leten, B.; Van Looy, B. Co-ownership of intellectual property: Exploring the value-appropriation and value-creation implications of co-patenting with different partners. Res. Policy 2014, 43, 841–852.
  14. Tomlinson, P.R. Co-operative ties and innovation: Some new evidence for UK manufacturing. Res. Policy 2010, 39, 762–775.
  15. Wu, Y.; Gu, F.; Ji, Y.; Guo, J.; Fan, Y. Technological capability, eco-innovation performance, and cooperative R&D strategy in new energy vehicle industry: Evidence from listed companies in China. J. Clean. Prod. 2020, 261, 121157.
  16. Van Beers, C.; Zand, F. R&D Cooperation, Partner Diversity, and Innovation Performance: An Empirical Analysis. J. Prod. Innov. Manag. 2013, 31, 292–312.
  17. Barge-Gil, A. Cooperation-based innovators and peripheral cooperators: An empirical analysis of their characteristics and behavior. Technovation 2010, 30, 195–206.
  18. Zhou, K.Z.; Gao, G.Y.; Zhao, H. State Ownership and Firm Innovation in China: An Integrated View of Institutional and Efficiency Logics. Adm. Sci. Q. 2016, 62, 375–404.
  19. Huang, K.G.-L.; Geng, X.; Wang, H. Institutional Regime Shift in Intellectual Property Rights and Innovation Strategies of Firms in China. Organ. Sci. 2017, 28, 355–377.
  20. Walter, J.; Lechner, C.; Kellermanns, F.W. Knowledge transfer between and within alliance partners: Private versus collective benefits of social capital. J. Bus. Res. 2007, 60, 698–710.
  21. Xu, D.; Lu, J.W.; Gu, Q. Organizational Forms and Multi-population Dynamics: Economic Transition in China. Adm. Sci. Q. 2014, 59, 517–547.
This entry is offline, you can click here to edit this entry!
Video Production Service