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How composite indicators of innovation can influence technology policy decision?

Author

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  • Nuno Boavida

    () (IET, Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia)

Abstract

This working paper is based on the development of the Thesis Plan presented for the Units Project II and Project III at the 1st Winter School of PhD programme on Technology Assessment at FCT/UNL. It focuses the methodology analysis and includes empirical information elements, in order to understand how composite indicators of innovation can influence technology policy decisions. In order to test the hypotheses raised in the Thesis Plan, two separate phases were designed. On the first part, the work tests hypotheses 1 and partially 2, identifying the quality, depth and limitations of three famous complex indicator-based systems, namely the Science, Technology and Industry Scoreboard, the European Innovation Scoreboard 2008 and Innovation Union Scoreboard 2010. On the second phase, the remaining hypotheses are tested adding media databases analysis, which will provide complementary information to a set of interviews to policy makers, in order to understand the role of the composite indicators on technology decisions.

Suggested Citation

  • Nuno Boavida, 2011. "How composite indicators of innovation can influence technology policy decision?," IET Working Papers Series 03/2011, Universidade Nova de Lisboa, IET/CICS.NOVA-Interdisciplinary Centre on Social Sciences, Faculty of Science and Technology.
  • Handle: RePEc:ieu:wpaper:34
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    File URL: http://run.unl.pt/handle/10362/6142
    File Function: First version, 2011
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    References listed on IDEAS

    as
    1. Grupp, Hariolf & Schubert, Torben, 2010. "Review and new evidence on composite innovation indicators for evaluating national performance," Research Policy, Elsevier, vol. 39(1), pages 67-78, February.
    2. Michela Nardo & Michaela Saisana & Andrea Saltelli & Stefano Tarantola & Anders Hoffman & Enrico Giovannini, 2005. "Handbook on Constructing Composite Indicators: Methodology and User Guide," OECD Statistics Working Papers 2005/3, OECD Publishing.
    3. Kuhlmann, Stefan & Boekholt, Patries & Georghiou, Luke & Guy, Ken & Heraud, Jean-Alain & Laredo, Philippe & Lemola, Tarmo & Loveridge, Denis & Luukkonen, Terttu & Moniz, António & Polt, Wolfgang & Rip, 1999. "Improving Distributed Intelligence in Complex Innovation Systems," MPRA Paper 6426, University Library of Munich, Germany, revised May 1999.
    4. Charles I. Jones, 2002. "Sources of U.S. Economic Growth in a World of Ideas," American Economic Review, American Economic Association, vol. 92(1), pages 220-239, March.
    5. M. Saisana & A. Saltelli & S. Tarantola, 2005. "Uncertainty and sensitivity analysis techniques as tools for the quality assessment of composite indicators," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(2), pages 307-323.
    6. Geels, Frank W. & Schot, Johan, 2007. "Typology of sociotechnical transition pathways," Research Policy, Elsevier, vol. 36(3), pages 399-417, April.
    7. Gomez-Limon, Jose Antonio & Riesgo, Laura, 2008. "Alternative Approaches On Constructing A Composite Indicator To Measure Agricultural Sustainability," 107th Seminar, January 30-February 1, 2008, Sevilla, Spain 6489, European Association of Agricultural Economists.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Abdurrahman M. Yazan, 2016. "Methods Used in Future Technology Analysis and its Selection: an application to VTOL transportation system," IET Working Papers Series 03/2016, Universidade Nova de Lisboa, IET/CICS.NOVA-Interdisciplinary Centre on Social Sciences, Faculty of Science and Technology.

    More about this item

    Keywords

    composite indicators; innovation; technology policy decisions; European Innovation Scoreboard; Innovation Union Scoreboard;

    JEL classification:

    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E61 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Policy Objectives; Policy Designs and Consistency; Policy Coordination
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives

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