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Public funding in the academic field of nanotechnology: a multi-agent based model

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  • Nadine Hoser

    (Bamberg University
    DFG-Graduate College “Markets and Social Systems in Europe”)

Abstract

This paper simulates research networks in nanotechnology in Germany and the US. Agent-based modelling is used to analyse how public third-party funding influences the diffusion of a high technology by four different ways of funding. This diffusion is measured by the emerging number of nanoscientists. Next to the size of the national research systems and the number of scientists, the spread of nanotechnology is measured by interdisciplinarity and the probability of changing one’s disciplinary identity. The model is proper for the investigation of other high-technologies. Different ways of funding researchers can, according to the study results, influence the pattern of diffusion of a new technology in academia, in particular in the bigger research system of the US. While results are not significant for Germany, the way of funding researchers has significant effects in the US, with star scientists playing a crucial role for the distribution of public funding.

Suggested Citation

  • Nadine Hoser, 2013. "Public funding in the academic field of nanotechnology: a multi-agent based model," Computational and Mathematical Organization Theory, Springer, vol. 19(2), pages 253-281, June.
    • Handle: RePEc:spr:comaot:v:19:y:2013:i:2:d:10.1007_s10588-013-9158-x
    DOI: 10.1007/s10588-013-9158-x
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    References listed on IDEAS

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    3. Joachim Schummer, 2007. "The global institutionalization of nanotechnology research: A bibliometric approach to the assessment of science policy," Scientometrics, Springer;Akadémiai Kiadó, vol. 70(3), pages 669-692, March.
    4. Flaminio Squazzoni, 2010. "The impact of agent-based models in the social sciences after 15 years of incursions," History of Economic Ideas, Fabrizio Serra Editore, Pisa - Roma, vol. 18(2), pages 197-234.
    5. Thelen,Kathleen, 2004. "How Institutions Evolve," Cambridge Books, Cambridge University Press, number 9780521837682, October.
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    Cited by:

    1. Davide Secchi & Raffaello Seri, 2017. "Controlling for false negatives in agent-based models: a review of power analysis in organizational research," Computational and Mathematical Organization Theory, Springer, vol. 23(1), pages 94-121, March.
    2. Han, Xue & Niosi, Jorge, 2016. "Star scientists in PV technology and the limits of academic entrepreneurship," Journal of Business Research, Elsevier, vol. 69(5), pages 1707-1711.

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