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Time of adoption and intensity of technology transfer: an institutional analysis of offices of technology transfer in the United States

Author

Listed:
  • Federico Castillo

    (University of California, Berkeley)

  • J. Keith Gilless

    (University of California, Berkeley)

  • Amir Heiman

    (Hebrew University of Jerusalem)

  • David Zilberman

    (University of California, Berkeley)

Abstract

This paper considers the adoption of institutional innovations by not for profit organizations, an issue that can be considered in the context of the extensive literature on the adoption of technological innovation by firms. The specific institutional innovation considered is the offices of technology transfer (OTT)—the organization that assemble and disclose university innovations and negotiate and enforce licenses with users of these innovations. We propose a theoretical framework that depart from previous studies by focusing on the timing decision of institutions rather than on the percentage of institutions that adopt at each point in time. Our theoretical framework also incorporates organization theory via imitation effects on the timing of adoption. We find that number of adopters has an S-shape function of time, which may indicate a strong element of imitation led universities to create OTTs. We also find that universities with higher research incomes and rankings were earlier adopters of the OTT model and that universities with medical schools were generally late adopters. Finally, we find that the number of universities who have already adopted the OTT model increases the speed by which other non-adopters make their OTT adoption decisions and that the number of invention disclosures, a primary indicator of output of OTTs, increases with the size of research budget, is smaller for those with medical schools, and larger for those that were earlier adopters of OTT. Section 1 of the paper discusses the recent trends in technology transfer while Section 2 reviews the advent of OTTs as facilitators of technology transfer activities. Section 3 reviews the relevant technology and institutional innovation literature. Section 4 develops a conceptual framework that links Sections 2 and 3 to analyze the advent and timing of the establishment of OTTs. Section 5 estimates the time of adoption of the OTT working model on the part of major research universities in the US, and analyzes the impact of time of adoption of the OTT model on the intensity of the technology transfer process. Section 6 presents empirical results while the conclusions and policy implications are discussed in Section 7.

Suggested Citation

  • Federico Castillo & J. Keith Gilless & Amir Heiman & David Zilberman, 2018. "Time of adoption and intensity of technology transfer: an institutional analysis of offices of technology transfer in the United States," The Journal of Technology Transfer, Springer, vol. 43(1), pages 120-138, February.
  • Handle: RePEc:kap:jtecht:v:43:y:2018:i:1:d:10.1007_s10961-016-9468-5
    DOI: 10.1007/s10961-016-9468-5
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    References listed on IDEAS

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    2. David J. Jefferson & Magali Maida & Alexander Farkas & Monica Alandete-Saez & Alan B. Bennett, 2017. "Technology transfer in the Americas: common and divergent practices among major research universities and public sector institutions," The Journal of Technology Transfer, Springer, vol. 42(6), pages 1307-1333, December.
    3. Eva María de la Torre & Fernando Casani & Carmen Pérez Esparrells, 2021. "Measuring universities’ engagement: a revision of the European research projects and the actual use of the so-called ‘third mission’ indicators," Revista de Estudios Regionales, Universidades Públicas de Andalucía, vol. 1, pages 97-128.
    4. Arkadiusz Świadek & Jadwiga Gorączkowska & Karolina Godzisz, 2022. "Conditions Driving Eco-Innovation in a Catching-Up Country—ICT vs. Industry in Poland," Energies, MDPI, vol. 15(15), pages 1-21, July.
    5. Robert Huggins & Daniel Prokop & Piers Thompson, 2020. "Universities and open innovation: the determinants of network centrality," The Journal of Technology Transfer, Springer, vol. 45(3), pages 718-757, June.
    6. Hua Cheng & Shiqian Huang & Yinhong Yu & Zhiying Zhang & Meifen Jiang, 2023. "The 2011 Collaborative Innovation Plan, University-Industry Collaboration and Achievement Transformation of Universities: Evidence from China," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 14(2), pages 1249-1274, June.
    7. Jadwiga Goraczkowska & Marek Tomaszewski, 2019. "Support of innovation activity in small and medium-sized enterprises in the Greater Poland Voivodeship," Ekonomia i Prawo, Uniwersytet Mikolaja Kopernika, vol. 18(2), pages 183-195, June.

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    More about this item

    Keywords

    Adoption; Institutional innovation; Heterogeneity; Mimetic isomorphism;
    All these keywords.

    JEL classification:

    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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