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Time Of Technology Adoption And Learning By Using

Author

Listed:
  • Bruce Mcwilliams
  • David Zilbermanfr

Abstract

Learning by using is introduced into an adoption model to explain why larger and more educated firms adopt earlier. Dynamic economies of scale arise in learning by using that speed up adoption. The empirical estimation of time of adoption using Tobit analysis integrates the concepts of adoption and diffusion, allowing the diffusion of the technology to be derived from the time of adoption analysis. In addition, by introducing heterogeneity among the adopters, Tobit analysis is shown to provide superior results to the traditional logit and probit analysis of the dichotomous adopt/not adopt variable.

Suggested Citation

  • Bruce Mcwilliams & David Zilbermanfr, 1996. "Time Of Technology Adoption And Learning By Using," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 4(2), pages 139-154.
    • Handle: RePEc:taf:ecinnt:v:4:y:1996:i:2:p:139-154
    DOI: 10.1080/10438599600000005
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    References listed on IDEAS

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    Cited by:

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    2. 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.
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    5. Park, Timothy A. & Lohr, Luanne, 2001. "Management Strategies And Human Capital Investments By Organic Producers," 2001 Annual meeting, August 5-8, Chicago, IL 20708, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    6. Torben Schubert, 2024. "Captive Offshoring, Innovation and Market Diffusion: Evidence from the Swedish Community Innovation Survey," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 5650-5678, June.
    7. Zein Kallas & Teresa Serra & José Maria Gil, 2010. "Farmers’ objectives as determinants of organic farming adoption: the case of Catalonian vineyard production," Agricultural Economics, International Association of Agricultural Economists, vol. 41(5), pages 409-423, September.
    8. Sauer, Johannes & Zilberman, David D., 2009. "Innovation behaviour at micro level - selection and identification," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt6t49r0fh, Department of Agricultural & Resource Economics, UC Berkeley.
    9. David Zilberman & Amir Heiman, 1997. "The Value of Economic Research," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(5), pages 1539-1544.
    10. Love, James H. & Roper, Stephen & Vahter, Priit, 2023. "The dynamics of abandoned innovation activities: Learning from failure or learning to prevent failure?," Research Policy, Elsevier, vol. 52(8).
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    13. Roper, Stephen & Love, James H. & Bonner, Karen, 2017. "Firms’ knowledge search and local knowledge externalities in innovation performance," Research Policy, Elsevier, vol. 46(1), pages 43-56.
    14. Vu Linh Toan Le & Tien Hoang Nguyen & Khanh Duy Pham, 2023. "What Drives Industry 4.0 Technologies Adoption? Evidence from a SEM-Neural Network Approach in the Context of Vietnamese Firms," Sustainability, MDPI, vol. 15(7), pages 1-32, March.
    15. Jane Bourke & Stephen Roper, 2012. "In with the new: the determinants of prescribing innovation by general practitioners in Ireland," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 13(4), pages 393-407, August.
    16. Bourke, Jane & Roper, Stephen, 2014. "The influence of experiential learning on medical equipment adoption in general practices," Health Policy, Elsevier, vol. 118(1), pages 37-47.
    17. Bourke, Jane & Roper, Stephen, 2016. "AMT adoption and innovation: An investigation of dynamic and complementary effects," Technovation, Elsevier, vol. 55, pages 42-55.
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    19. Nadia A. Streletskaya & Samuel D. Bell & Maik Kecinski & Tongzhe Li & Simanti Banerjee & Leah H. Palm‐Forster & David Pannell, 2020. "Agricultural Adoption and Behavioral Economics: Bridging the Gap," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 42(1), pages 54-66, March.

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    More about this item

    Keywords

    Time of adoption; learning-by-using; tobit; diffusion J.E.L. Codes: 033; C24;
    All these keywords.

    JEL classification:

    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models

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