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Impact assessment of a support programme of science-based emerging technologies

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Abstract

The impact assessment of support programmes of science-based emerging technologies requires the analysis of several dimensions of performance, as these programmes refer to used-inspired basic research which is linked to basic research as well as to technological application. Bibliometric analysis proves to be a useful tool for capturing different aspects of performance. In the specific programme “future emerging technologies”, interdisciplinarity turns out to be crucial for achieving excellent and creative outcomes. Furthermore, the orientation on risky projects yields some excellent results, but few failures.

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Source: Web of science, own compilations

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Notes

  1. There is a close link between evaluation and impact assessment, but evaluation and assessment are not identical concepts (Airaghi et al. 1999:8).

  2. FET Flagships were not part of our impact assessment.

  3. TF Idf (Term frequency Inverse document frequency, see https://janav.wordpress.com/2013/10/27/tf-idf-and-cosine-similarity/).

  4. The survey was conducted online by the programme Questback offered by Enterprise Feedback Suite (EFS).

  5. Because the excellent performance of the project—based on the bibliometric analysis—was the criterion to select these projects.

References

  • Airaghi, A., Busch, N. E., Georghiou, L., Stefan Kuhlmann, S., Ledoux, M. J., et al. (1999). Options and limits for assessing the socio-economic impact of european RTD programmes, report to the European Commission. Brussels: European Commission.

    Google Scholar 

  • Amabile, T. M. (1996). Creativity in context: Update to the social psychology of creativity. New York: Springer.

    Google Scholar 

  • Arts, S., & Veugelers, R. (2014). Technology familiarity, recombinant novelty, and breakthrough invention. Industrial and Corporate Change, 24(6), 1215–1246.

    Article  Google Scholar 

  • Bonnín Roca, J., Vaishnava, P., Morgan, M. G., Joana Mendonça, J., & Fuchs, E. (2017). When risks cannot be seen: Regulating uncertainty in emerging technologies. Research Policy, 46, 1215–1233.

    Article  Google Scholar 

  • Cochrane, J. H. (2005). The risk and return of venture capital. Journal of Financial Economics, 75(1), 3–52.

    Article  Google Scholar 

  • De Touzalin, A. (2013). Future and emerging technologies (FET) work programme 2014–2015 in H2020, DG CONNECT. Paris: European Commission.

    Google Scholar 

  • Georghiou, L., & Roessner, D. (2000). Evaluating technology programs: Tools and methods. Research Policy, 29, 657–678.

    Article  Google Scholar 

  • Glänzel, W., & Czerwon, H. J. (1996). A new methodological approach to bibliographic coupling and its application to the national, regional and institutional level. Scientometrics, 37, 195–221.

    Article  Google Scholar 

  • Lai, P. C. (2017). The literature review of technology adoption models and theories for the novelty technology. JISTEM Journal of Information Systems and Technology Management, 14(1), 1.

    Google Scholar 

  • Mamykina, L., Candy, L., & Ernest Edmonds, E. (2002). Collaborative creativity. Communications of the ACM, 45(10), 96–99.

    Article  Google Scholar 

  • Mason, C. M., & Harrison, R. T. (2002). Is it worth it? The rates of return from informal venture capital investments. Journal of Business Venturing, 17(3), 211–236.

    Article  Google Scholar 

  • Rhoten, D., & Andrew Parker, A. (2004). Risks and rewards of an interdisciplinary research path. Science, 17(306/5704), 2046.

    Article  Google Scholar 

  • Rotolo, D., Hicks, D., & Martin, B. R. (2016). What is an emerging technology? Research Policy, 44(10), 1827–1843.

    Article  Google Scholar 

  • Sahlmann, W. (1990). The structure and governance of venture capital organizations. Journal of Financial Economics, 27, 473–521.

    Article  Google Scholar 

  • Sawyer, R. K. (2011). Explaining creativity: The science of human innovation. Oxford: Oxford University Press.

    Google Scholar 

  • Schmoch, U. (2007). Double-boom cycles and the comeback of science-push and market-pull. Research Policy, 36(7), 1000–1015.

    Article  Google Scholar 

  • Schmoch, U., Breiner, S., Cuhls, K., Hinze, S., & Münt, G. (1996). The organisation of interdisciplinarity—Research structures in the areas of medical lasers and neural networks. In G. Reger & U. Schmoch (Eds.), Organisation of science and technology at the watershed (pp. 267–372). Heidelberg: Physica-Verlag.

    Chapter  Google Scholar 

  • Shapira, P., & Kuhlmann, S. (2003). Learning from science and technology policy evaluation: Experiences from the United States and Europe. Cheltenham: Edward Elgar Publishing.

    Google Scholar 

  • Stacey, R. D. (1996). Complexity and creativity in organizations. San Francisco: Berrett-Koehler Publishers.

    Google Scholar 

  • Sternberg, R. J. (Ed.). (1999). Handbook of creativity. Cambridge: Cambridge University Press.

    Google Scholar 

  • Stokes, D. E. (1997). Pasteur’s quadrant—Basic science and technological innovation. Washington, D.C.: Brookings Institution Press.

    Google Scholar 

  • Struening, E. L., & Guttentag, M. (1975). Handbook of evaluation research. Beverly Hills: Sage Publications.

    Google Scholar 

  • Tatikonda, M. V., & Rosenthal, S. R. (2000). Technology novelty, project complexity, and product development project execution success: A deeper look at task uncertainty in product innovation. IEEE Transactions on Engineering Management, 47(1), 74–87.

    Article  Google Scholar 

  • Van Raan, A. J. F. (2005). Measurement of central aspects of scientific research: Performance. Interdisciplinarity, Structure, Measurement, 3(1), 1–19.

    Google Scholar 

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Acknowledgements

Certain data included in this paper are derived from the Science Citation Index Expanded (SCIE), the Social Science Citation Index (SSCI), the Arts and Humanities Citation Index (AHCI), and the Index to Social Sciences and Humanities Proceedings (ISSHP) (all updated June 2010) prepared by Thomson Reuters (Scientific) Inc. (TR®), Philadelphia, Pennsylvania, USA, USA: ©Copyright Thomson Reuters (Scientific) 2010. All rights reserved.

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Funding was provided by European Commission (Grant No. i665083)

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Schmoch, U., Beckert, B. & Schaper-Rinkel, P. Impact assessment of a support programme of science-based emerging technologies. Scientometrics 118, 1141–1161 (2019). https://doi.org/10.1007/s11192-018-03002-x

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