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Estimating the innovation effects of university–industry–government linkages: The case of Taiwan

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  • Hu, Mei-Chih
  • Mathews, John A

Abstract

This study focuses on university—industry—government (UIG) linkages and their influence on innovation in Taiwan. The innovation effects are estimated using a quartet of measures — technology transfers, technology licensing, firms incubated and patents granted — while the UIG influence is estimated via its differential impact according to the size of the firms involved, the type of innovation (process or product-oriented), the stage of the technology cycle, and the role of government. Using a Structural Equation Model (SEM) method to examine these interactions, the study reveals that UIG linkage effects vary with the size of company, in that the major incentive for UIG linkages for large companies is an attempt to acquire a skilled and qualified workforce, while SMEs (small and medium enterprises) tend to use them to gain marketing advantage, particularly for those SMEs or start-ups in emerging industries. The study concludes that Taiwan's innovation capacity is heavily reliant on building the capability of SMEs and continues to depend greatly on government leadership through technology-capability-enhancing institutions such as ITRI.

Suggested Citation

  • Hu, Mei-Chih & Mathews, John A, 2009. "Estimating the innovation effects of university–industry–government linkages: The case of Taiwan," Journal of Management & Organization, Cambridge University Press, vol. 15(2), pages 138-154, May.
    • Handle: RePEc:cup:jomorg:v:15:y:2009:i:02:p:138-154_00
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    Cited by:

    1. Ssu-Han Chen & Mu-Hsuan Huang & Dar-Zen Chen, 2013. "Driving factors of external funding and funding effects on academic innovation performance in university–industry–government linkages," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 1077-1098, March.
    2. Huang, Mu-Hsuan & Chen, Dar-Zen, 2017. "How can academic innovation performance in university–industry collaboration be improved?," Technological Forecasting and Social Change, Elsevier, vol. 123(C), pages 210-215.
    3. Dulcineia Catarina Moura & Maria José Madeira & Filipe A. P. Duarte, 2019. "Cooperation In The Field Of Innovation, Absorptive Capacity, Public Financial Support And Determinants Of The Innovative Performance Of Enterprise," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 24(04), pages 1-28, July.
    4. Zeng, Tian & Botella-Carrubi, Dolores, 2023. "Improving societal benefit through transformative consumer research: A descriptive review," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    5. Matthew A. Shapiro, 2012. "Receiving information at Korean and Taiwanese universities, industry, and GRIs," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(1), pages 289-309, January.
    6. Fan-Chuan Tseng & Mu-Hsuan Huang & Dar-Zen Chen, 2020. "Factors of university–industry collaboration affecting university innovation performance," The Journal of Technology Transfer, Springer, vol. 45(2), pages 560-577, April.
    7. Zhiyang Zhong & Gaoming Zheng & Yan Wang, 2022. "Impact of Transnational Research Collaboration on Universities’ Innovation Performance: Panel Data Research of 64 Chinese Universities from 2009 to 2019," Sustainability, MDPI, vol. 15(1), pages 1-16, December.

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