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The role of firm and national level factors in fostering R&D cooperation: a cross country comparison

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Abstract

This paper explores the factors that affect firms’ propensity to engage in R&D cooperation using a CIS-3 sample of innovative firms located in seven European countries. It performs the analysis separately for the manufacturing and the service sectors in order to examine whether there are specific features that shape the service firms’ R&D cooperative behaviour in particular ways. Differences between the manufacturing and the service sectors in the cooperative behaviour of firms become much more evident once an appropriate structure of endogeneity is determined. We compare different countries because, so far, the empirical evidence produced comes from single countries or countries that are all quite homogeneous in terms of industrial structure. Instead, we consider also countries, such as transition economies, that have not been analyzed so far. We find that public subsidies positively affect firms’ propensity to engage in R&D cooperation in all countries, but they seem particularly important to enhance firms’ cooperativeness in the service sector. Implications for innovation policy are examined.

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Notes

  1. Oxley and Sampson (2004) highlighted many other opportunities deriving from R&D cooperations, such as hints about partner strategies and directions of technological search, the awareness of competitive benchmarking data, the identification of key personnel or the absorption of codified and tacit knowledge.

  2. These early theoretical models have been later extended to account for the fact that firms may try to influence spillovers by increasing their R&D endowments:in particular, firms attempt to minimize outgoing spillovers and maximize incoming spillovers. The literature usually converges in asserting a positive impact of this variable on the firms’ propensity to cooperate. Furthermore, while most studies explore only a linear relationship between R&D intensity and the firms’ propensity to cooperate in R&D, Belderbos et al. (2004) and Fritsch and Franke (2004) show a non-linear concave effect of R&D intensity on firms’ propensity to engage in R&D cooperation, justifying this result with the decreasing returns of absorptive capacity.

  3. The investigation of the role of incoming and outgoing spillovers has recently extended beyond European Countries: Chun and Mun (2012) examine the Korean case using a survey carried out in the 2002. They find that incoming spillovers play a significant role in enhancing R&D cooperation likelihood and this effect is much larger for smaller firms.

  4. These alliances include joint development agreements, Research Joint Ventures, technology transfer and technology sharing agreements.

  5. The CIS is a compulsory survey for firms that takes place every four years in European countries to shed light on firms innovation activities. Only firms with more than 10 employees can be part of the sample. The CIS is characterized by a harmonized questionnaire and methodology on which countries of the European Union agree.

  6. It is worth underlining that, as Abramosky et al. (2009) and Bodas Freitas et al. (2011) consider, the very broad definition of innovative firms which is used in the sample should not cause any serious selection problem.

  7. See: Caloghirou et al. (2003) for details on EU’s Framework Programmes.

  8. The distinction between lack of external and internal sources of finance is available only for Italy, the other countries’ questionnaire generally speaks about the lack of sources of finance.

  9. See: Veugelers 1997; Fritsch and Lukas 2001; Bayona et al. 2001; Angel 2002; Cassiman and Veugelers 2002; Hernan et al. 2003; Becker and Dietz 2004; Belderbos et al. 2004.

  10. Regressions with sectorial dummies are available upon request.

  11. Lopez (2008, p. 134) showed a similar regression of the generalized residuals on the exclusion restrictions reporting a very low R 2 (0.002). He did not include the constant term in the regression, but Greene (2003, p. 36) has shown that “ The proof that 0 ≤ R 2 ≤ 1 requires X to contain a column of 1s. If not [\(\ldots\)] when we compute R 2 the result is unpredictable”. This is the reason of the presence of α in equation 7.

  12. The function used for the marginal effects computation in the case of endogeneity correction in Tables 9, 10 and 12 is unsuitable for robust standard errors calculation therefore they have not been reported. Significance of coefficients has been previously checked.

  13. Equality of coefficients of the manufacturing and service sector overall cooperation has not been tested, however we computed marginal effects which are reasonably comparable.

  14. See also Czarnitzki and Fier (2002).

  15. See: The “ Country report 2009 for Germany" at http://www.proinno-europe.eu

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Correspondence to Chiara Franco.

Appendix

Appendix

See Tables 6, 7, 8, 9, 10, 11, 12.

Table 6 Italy: results of the probit estimation for the manufacturing and service sector
Table 7 Spain: results of the probit estimation for the manufacturing and service sector
Table 8 Germany: results of the probit estimation for the manufacturing and service sector
Table 9 Norway: results of the probit estimation for the manufacturing and service sector
Table 10 Belgium: results of the probit estimation for the manufacturing and service sector
Table 11 Romania: results of the probit estimation for the manufacturing and service sector
Table 12 Czech Republic: results of the probit estimation for the manufacturing and service sector

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Franco, C., Gussoni, M. The role of firm and national level factors in fostering R&D cooperation: a cross country comparison. J Technol Transf 39, 945–976 (2014). https://doi.org/10.1007/s10961-013-9306-y

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