IDEAS home Printed from https://ideas.repec.org/p/wiw/wiwrsa/ersa11p297.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www-sre.wu.ac.at/ersa/ersaconfs/ersa11/e110830aFinal00297.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cilem Selin Hazir & Corinne Autant-Bernard, 2012. "Using Affiliation Networks to Study the Determinants of Multilateral Research Cooperation Some empirical evidence from EU Framework Programs in biotechnology," Working Papers 1212, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    2. Sara Amoroso & Alex Coad & Nicola Grassano, 2017. "European R&D networks: A snapshot from the 7th EU Framework Programme," JRC Working Papers on Corporate R&D and Innovation JRC107546, Joint Research Centre (Seville site).
    3. Ernest Miguélez & Rosina Moreno, 2013. "Do Labour Mobility and Technological Collaborations Foster Geographical Knowledge Diffusion? The Case of European Regions," Growth and Change, Wiley Blackwell, vol. 44(2), pages 321-354, June.
    4. Romeo-Victor IONESCU, 2015. "European Economy Vs The Trap Of The Europe 2020 Strategy," EURINT, Centre for European Studies, Alexandru Ioan Cuza University, vol. 2, pages 215-233.
    5. Simen G. Enger & Fulvio Castellacci, 2016. "Who gets Horizon 2020 research grants? Propensity to apply and probability to succeed in a two-step analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1611-1638, December.
    6. Aurélien Fichet de Clairfontaine & Manfred Fischer & Rafael Lata & Manfred Paier, 2015. "Barriers to cross-region research and development collaborations in Europe: evidence from the fifth European Framework Programme," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 54(2), pages 577-590, March.
    7. Biggiero, Lucio & Angelini, Pier Paolo, 2015. "Hunting scale-free properties in R&D collaboration networks: Self-organization, power-law and policy issues in the European aerospace research area," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 21-43.
    8. Ernest Miguelez, 2013. "How does geographical mobility of inventors influence network formation?," WIPO Economic Research Working Papers 07, World Intellectual Property Organization - Economics and Statistics Division, revised Apr 2013.
    9. Iris Wanzenböck & Thomas Scherngell & Thomas Brenner, 2013. "What determines the position of regions in European knowledge networks? A comparative perspective on R&D collaboration, co-patent and co-publication networks," ERSA conference papers ersa13p332, European Regional Science Association.
    10. Iris Wanzenböck & Thomas Scherngell & Thomas Brenner, 2014. "Embeddedness of regions in European knowledge networks: a comparative analysis of inter-regional R&D collaborations, co-patents and co-publications," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 53(2), pages 337-368, September.
    11. Crescenzi, Riccardo & Nathan, Max & Rodríguez-Pose, Andrés, 2016. "Do inventors talk to strangers? On proximity and collaborative knowledge creation," Research Policy, Elsevier, vol. 45(1), pages 177-194.
    12. Ana Fernández & Esther Ferrándiz & M. Dolores León, 2021. "Are organizational and economic proximity driving factors of scientific collaboration? Evidence from Spanish universities, 2001–2010," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 579-602, January.
    13. Sara Amoroso & Simone Vannuccini, 2019. "Teaming up with Large R&D Investors: Good or Bad for Knowledge Production and Diffusion?," SPRU Working Paper Series 2019-20, SPRU - Science Policy Research Unit, University of Sussex Business School.
    14. Lorenzo Cassi & Andrea Morrison & Roberta Rabellotti, 2015. "Proximity and Scientific Collaboration: Evidence from the Global Wine Industry," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 106(2), pages 205-219, April.
    15. Tom Broekel & Marcel Bednarz, 2018. "Disentangling link formation and dissolution in spatial networks: An Application of a Two-Mode STERGM to a Project-Based R&D Network in the German Biotechnology Industry," Networks and Spatial Economics, Springer, vol. 18(3), pages 677-704, September.
    16. Pier Paolo Angelini, "undated". "The role of inter-organizational proximity on the evolution of the European Aerospace R&D collaboration network," CERIS Working Paper 201402, Institute for Economic Research on Firms and Growth - Moncalieri (TO) ITALY -NOW- Research Institute on Sustainable Economic Growth - Moncalieri (TO) ITALY.
    17. Luigi Aldieri & Gennaro Guida & Maxim Kotsemir & Concetto Paolo Vinci, 2019. "An investigation of impact of research collaboration on academic performance in Italy," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(4), pages 2003-2040, July.
    18. Li, Ruimeng & Yang, Naiding & Zhang, Yanlu & Liu, Hui & Zhang, Mingzhen, 2021. "Impacts of module–module aligned patterns on risk cascading propagation in complex product development (CPD) interdependent networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 564(C).
    19. Mafini Dosso & Antonio Vezzani, 2020. "Firm market valuation and intellectual property assets," Industry and Innovation, Taylor & Francis Journals, vol. 27(7), pages 705-729, August.
    20. Otello Ardovino & Maria Rosaria Carillo & Luca Pennacchio, 2016. "R&D cooperation within Italian technological districts: A microeconometric analysis," Discussion Papers 2_2016, CRISEI, University of Naples "Parthenope", Italy.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wiw:wiwrsa:ersa11p297. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Gunther Maier). General contact details of provider: http://www.ersa.org .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.