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How do distinct firm characteristics affect behavioural additionalities of public R&D subsidies? Empirical evidence from a binary regression analysis

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  • Iris Wanzenböck
  • Thomas Scherngell

    ()

  • Fischer Manfred

Abstract

In the recent past, interest of Science, Technology, and Innovation (STI) policies to influence the innovation behaviour of firms has been increased considerably. This gives rise to the notion of behavioural additionality, broadening traditional evaluation concepts of input and output additionality. Though there is empirical work measuring behavioural additionalities, we know little about what role distinct firm characteristics play for their occurrence. The objective is to estimate how distinct firm characteristics influence the realisation of behavioural additionalities. We use survey data on 155 firms, considering the behavioural additionalities stimulated by the Austrian R&D funding scheme in the field of intelligent transport systems in 2006. We focus on three different forms of behavioural additionality "" project additionality, scale additionality and cooperation additionality "" and employ binary regression models to address this question. Results indicate that R&D related firm characteristics significantly affect the realisation of behavioural additionality. Firms with a high level of R&D resources are less likely to substantiate behavioural additionalities, while small, young and technologically specialised firms more likely realise behavioural additionalities. From a policy perspective, this indicates that direct R&D promotion of firms with high R&D resources may be misallocated, while attention of public support should be shifted to smaller, technologically specialised firms with lower R&D experience.

Suggested Citation

  • Iris Wanzenböck & Thomas Scherngell & Fischer Manfred, 2011. "How do distinct firm characteristics affect behavioural additionalities of public R&D subsidies? Empirical evidence from a binary regression analysis," ERSA conference papers ersa11p297, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa11p297
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    1. Manfred Paier & Thomas Scherngell, 2011. "Determinants of Collaboration in European R&D Networks: Empirical Evidence from a Discrete Choice Model," Industry and Innovation, Taylor & Francis Journals, vol. 18(1), pages 89-104.
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    Cited by:

    1. Dezhina, I. & Simachev, Yu., 2013. "Matching Grants for Stimulating Partnerships between Companies and Universities in Innovation Area: Initial Effects in Russia," Journal of the New Economic Association, New Economic Association, vol. 19(3), pages 99-122.
    2. repec:kap:iaecre:v:21:y:2015:i:1:p:13-31 is not listed on IDEAS
    3. Dezhina, Irina & Simachev, Yuri, 2012. "Partnering universities and companies in Russia: effects of new government initiative," MPRA Paper 43622, University Library of Munich, Germany.

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