How do distinct firm characteristics affect behavioural additionalities of public R&D subsidies? Empirical evidence from a binary regression analysis
AbstractIn 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 Ã¢â‚¬â€œ project additionality, scale additionality and cooperation additionality Ã¢â‚¬â€œ 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.
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Bibliographic InfoPaper provided by European Regional Science Association in its series ERSA conference papers with number ersa11p297.
Date of creation: Sep 2011
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This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-11-14 (All new papers)
- NEP-INO-2011-11-14 (Innovation)
- NEP-IPR-2011-11-14 (Intellectual Property Rights)
- NEP-SBM-2011-11-14 (Small Business Management)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Manfred Paier & Thomas Scherngell, 2011. "Determinants of Collaboration in European R&D Networks: Empirical Evidence from a Discrete Choice Model," Industry & Innovation, Taylor and Francis Journals, vol. 18(1), pages 89-104.
- 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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