IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v127y2022i3d10.1007_s11192-021-04244-y.html
   My bibliography  Save this article

System dynamic analysis on industry-university-research institute synergetic innovation process based on knowledge flow

Author

Listed:
  • Yue Wu

    (Sichuan University)

  • Xin Gu

    (Sichuan University
    Chengdu Soft Innovation and Intelligence Industry Research Association)

  • Zhenzhou Tu

    (Chengdu University of Information Engineering)

  • Zhaobohan Zhang

    (Sichuan University)

Abstract

The industry-university-research institute synergetic innovation (IUR-SI) is a contractual arrangement formed by the core subjects of enterprises, universities, and research institutes, with the cooperation and assistance of intermediary organizations and other auxiliary organizations. The purpose of knowledge appreciation, sharing, and creation, along with the collaborative interaction approach, can realize joint development of major scientific and technological innovations. By analyzing the key factors affecting knowledge flow in the IUR-SI process, this research explores how knowledge flow can be promoted more effectively and efficiently. First, the subjective, knowledge, and knowledge flow simulation factors which influence knowledge flow in the IUR-SI process are analyzed. Then the knowledge flow process is simulated using the system dynamics method. Finally, the corresponding system dynamics model is constructed, and its simulation is analyzed. The results show that in the IUR-SI process, knowledge sharing ability, knowledge hiding coefficient, knowledge failure rate, subject innovation willingness, trust relationship, and organizational distance have obvious influences on the overall knowledge stock of the system, meaning that the above factors have relatively high sensitivity. The continuous flow of knowledge will gradually strengthen their influence. Knowledge flow is more affected by internal driving mechanisms, such as knowledge transfer and knowledge sharing. Changes in the internal driving mechanism’s role will affect knowledge flow efficiency, while factors such as trust relationships and organizational distance will have a relatively small effect. These results indicate that improving knowledge flow efficiency, the internal environment, and strengthening knowledge transfer and sharing, should be of great importance.

Suggested Citation

  • Yue Wu & Xin Gu & Zhenzhou Tu & Zhaobohan Zhang, 2022. "System dynamic analysis on industry-university-research institute synergetic innovation process based on knowledge flow," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(3), pages 1317-1338, March.
    • Handle: RePEc:spr:scient:v:127:y:2022:i:3:d:10.1007_s11192-021-04244-y
    DOI: 10.1007/s11192-021-04244-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-021-04244-y
    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/s11192-021-04244-y?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. Devinder Grewal & Hilary Haugstetter, 2007. "Capturing and sharing knowledge in supply chains in the maritime transport sector: critical issues," Maritime Policy & Management, Taylor & Francis Journals, vol. 34(2), pages 169-183, April.
    2. Komanda Marcin, 2011. "Trust as a context for knowledge flows in co-opetition," Manager Journal, Faculty of Business and Administration, University of Bucharest, vol. 14(1), pages 139-151, December.
    3. Veugelers, Reinhilde & Cassiman, Bruno, 2005. "R&D cooperation between firms and universities. Some empirical evidence from Belgian manufacturing," International Journal of Industrial Organization, Elsevier, vol. 23(5-6), pages 355-379, June.
    4. Bernard L. Simonin, 1999. "Ambiguity and the process of knowledge transfer in strategic alliances," Strategic Management Journal, Wiley Blackwell, vol. 20(7), pages 595-623, July.
    5. Lee, Yong S, 2000. "The Sustainability of University-Industry Research Collaboration: An Empirical Assessment," The Journal of Technology Transfer, Springer, vol. 25(2), pages 111-133, June.
    6. Andrew C. Inkpen & Adva Dinur, 1998. "Knowledge Management Processes and International Joint Ventures," Organization Science, INFORMS, vol. 9(4), pages 454-468, August.
    7. Eom, Boo-Young & Lee, Keun, 2010. "Determinants of industry-academy linkages and, their impact on firm performance: The case of Korea as a latecomer in knowledge industrialization," Research Policy, Elsevier, vol. 39(5), pages 625-639, June.
    8. Szulanski, Gabriel, 2000. "The Process of Knowledge Transfer: A Diachronic Analysis of Stickiness," Organizational Behavior and Human Decision Processes, Elsevier, vol. 82(1), pages 9-27, May.
    9. Gabriel Szulanski & Rossella Cappetta & Robert J. Jensen, 2004. "When and How Trustworthiness Matters: Knowledge Transfer and the Moderating Effect of Causal Ambiguity," Organization Science, INFORMS, vol. 15(5), pages 600-613, October.
    10. Ming Yu Cheng & R. Ghulam, 2007. "Knowledge gap and earnings differential in the knowledge-based economy," Applied Economics Letters, Taylor & Francis Journals, vol. 14(3), pages 219-221.
    11. Satu Pekkarinen & Vesa Harmaakorpi, 2006. "Building regional innovation networks: The definition of an age business core process in a regional innovation system," Regional Studies, Taylor & Francis Journals, vol. 40(4), pages 401-413.
    12. Eric von Hippel, 1994. ""Sticky Information" and the Locus of Problem Solving: Implications for Innovation," Management Science, INFORMS, vol. 40(4), pages 429-439, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cui Zhang & Xiongjin Feng & Yanzhen Wang, 2022. "Technology Spillovers among Innovation Agents from the Perspective of Network Connectedness," Mathematics, MDPI, vol. 10(16), pages 1-17, August.
    2. Shui-Ying Jin & Hong Chai & Chien-Chiang Lee, 2024. "Knowledge Transfer of China’s HSR Standards “Going Global” Based on System Dynamics," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 6111-6150, June.
    3. Jiang, Man & Yang, Siluo & Gao, Qiang, 2024. "Multidimensional indicators to identify emerging technologies: Perspective of technological knowledge flow," Journal of Informetrics, Elsevier, vol. 18(1).

    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. Nicolai J. Foss & Kenneth Husted & Snejina Michailova, 2010. "Governing Knowledge Sharing in Organizations: Levels of Analysis, Governance Mechanisms, and Research Directions," Journal of Management Studies, Wiley Blackwell, vol. 47(3), pages 455-482, May.
    2. Xin Liu & Lin Zhang & Abhinav Gupta & Xiaoming Zheng & Changqi Wu, 2022. "Upper echelons and intra‐organizational learning: How executive narcissism affects knowledge transfer among business units," Strategic Management Journal, Wiley Blackwell, vol. 43(11), pages 2351-2381, November.
    3. Emilio Bellini & Giuseppe Piroli & Luca Pennacchio, 2019. "Collaborative know-how and trust in university–industry collaborations: empirical evidence from ICT firms," The Journal of Technology Transfer, Springer, vol. 44(6), pages 1939-1963, December.
    4. Arie Y. Lewin & Silvia Massini & Carine Peeters, 2011. "Microfoundations of Internal and External Absorptive Capacity Routines," Organization Science, INFORMS, vol. 22(1), pages 81-98, February.
    5. Christine Holmström Lind & Olivia H. Kang, 2017. "The Value-Adding Role of the Corporate Headquarters in Innovation Transfer Processes: The Issue of Headquarters Knowledge Situation," Management International Review, Springer, vol. 57(4), pages 571-602, August.
    6. Gabriel Szulanski & Dimo Ringov & Robert J. Jensen, 2016. "Overcoming Stickiness: How the Timing of Knowledge Transfer Methods Affects Transfer Difficulty," Organization Science, INFORMS, vol. 27(2), pages 304-322, April.
    7. Wang Juanru & Yang Jin, 2015. "An Empirical Study of Employees’ Tacit Knowledge Sharing Behavior," Journal of Systems Science and Information, De Gruyter, vol. 3(3), pages 264-278, June.
    8. Roud Vitaliy & Valeriya Vlasova, 2017. "Cooperating with Universities and R&D Organizations: Mainstream Practice or Peculiarity?," HSE Working papers WP BRP 75/STI/2017, National Research University Higher School of Economics.
    9. Bo Bernhard Nielsen & Sabina Nielsen, 2009. "Learning and Innovation in International Strategic Alliances: An Empirical Test of the Role of Trust and Tacitness," Journal of Management Studies, Wiley Blackwell, vol. 46(6), pages 1031-1056, September.
    10. Law, Kuok Kei, 2014. "The problem with knowledge ambiguity," European Management Journal, Elsevier, vol. 32(3), pages 444-450.
    11. João M. Lopes & Márcio Oliveira & Jorge Lopes & Umer Zaman, 2021. "Networks, Innovation and Knowledge Transfer in Tourism Industry: An Empirical Study of SMEs in Portugal," Social Sciences, MDPI, vol. 10(5), pages 1-17, April.
    12. Jun-You Lin, 2021. "Collaboration exploitation and exploration: does a proactive search strategy matter?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(10), pages 8295-8329, October.
    13. Balboni, Bernardo & Marchi, Gianluca & Vignola, Marina, 2017. "Knowledge transfer in the context of buyer–supplier relationship: An analysis of a supplier's customer portfolio," Journal of Business Research, Elsevier, vol. 80(C), pages 277-287.
    14. Vitaliy Roud & Valeriya Vlasova, 2020. "Strategies of industry-science cooperation in the Russian manufacturing sector," The Journal of Technology Transfer, Springer, vol. 45(3), pages 870-907, June.
    15. Li, Chia-Ying & Hsieh, Chang-Tseh, 2009. "The impact of knowledge stickiness on knowledge transfer implementation, internalization, and satisfaction for multinational corporations," International Journal of Information Management, Elsevier, vol. 29(6), pages 425-435.
    16. Albert Banal-Estañol & Inés Macho-Stadler & David Pérez-Castrillo, 2013. "Endogeneous matching in university-industry collaboration: Theory and empirical evidence from the UK," Economics Working Papers 1379, Department of Economics and Business, Universitat Pompeu Fabra.
    17. López-Sáez, Pedro & Cruz-González, Jorge & Navas-López, Jose Emilio & Perona-Alfageme, María del Mar, 2021. "Organizational integration mechanisms and knowledge transfer effectiveness in MNCs: The moderating role of cross-national distance," Journal of International Management, Elsevier, vol. 27(4).
    18. Martin M�ller & Allison Stewart, 2016. "Does Temporary Geographical Proximity Predict Learning? Knowledge Dynamics in the Olympic Games," Regional Studies, Taylor & Francis Journals, vol. 50(3), pages 377-390, March.
    19. Willy C. Shih, 2021. "Increasing the Level of Abstraction as a Strategy for Accelerating the Adoption of Complex Technologies," Strategy Science, INFORMS, vol. 6(1), pages 54-61, March.
    20. Szász, Levente & Rácz, Béla-Gergely & Scherrer, Maike & Deflorin, Patricia, 2019. "Disseminative capabilities and manufacturing plant roles in the knowledge network of MNCs," International Journal of Production Economics, Elsevier, vol. 208(C), pages 294-304.

    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:3:d:10.1007_s11192-021-04244-y. 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.