Forms and Determinants of R&D Collaborations: Evidence Based on French Data

Abstract

The literature on R&D collaboration highlights a broad set of rationales for allying with other organizations. At the same time, it has been reported that there exists a large variety of forms of collaboration. Nevertheless, the relation between the motives to collaborate and the different forms of collaboration has not been examined. In this paper, we attempt to fill this gap by highlighting and explaining the heterogeneity in the forms of collaboration as a result of several interdependent simultaneous choices. Using a sample of more than 3,000 R&D collaborations, a typology of their characteristics allows us to distinguish five discrete forms of collaboration. Then using a multinomial logit estimation, we show how the forms of collaboration vary according to the firms' attributes (size, R&D internal effort, group membership), market and objectives pursued. We also obtain new results on the effects of incoming spillovers as well as appropriability conditions.

Keywords:

• R&D collaborations
• collaboration design
• cooperative strategies
• knowledge spillovers

Acknowledgements

We would like to thank three anonymous referees who provided very helpful suggestions as well as the ANR (Agence Nationale de le Recherche) for financial support (project ANR-06-JCJC-0076). All errors remain our own.

Notes

¹ Another limitation is linked to the problem of sample selection bias. In particular, the vast majority of studies on cooperative R&D make use of samples of innovative firms (e.g. Community Innovation Survey (CIS) of the European Commission).

² For instance, Bönte and Keilbach (2005) report that 70 per cent of the firms in their data-set are engaged in informal cooperations vs. 40 per cent in formal ones (some of which are also engaged in informal cooperations).

³ See SESSI (2004) for more information about the characteristics of the respondents.

⁴ Becker and Dietz (2004) find that about 37 per cent of German firms collaborate with other organizations to jointly develop new products. Tether (2002) finds that 45 per cent of English innovating firms cooperate with other organizations. A total of 18.9 per cent of innovative Spanish firms cooperate (Lopez, 2008).

⁵ The introduction of spillovers at the firm level can generate potential endogeneity problems (Belderbos et al., 2004; Lopez, 2008). We suppose that this problem is smaller as the strategy of one firm should not strongly modify the industry variable.

⁶ Since individuals of our data-set are firms' relations and since a firm can describe several relations, we make use of the cluster option in Stata. We also ran a regression with data clustered by sector. Effects remained unchanged. Notice that, in addition, we have no way of knowing whether the same partnership has been surveyed on both sides of the relation. This may introduce another kind of within group effect which we cannot treat here (we thank a referee for this remark).

⁷ Notice that we also tested the influence of the geography on the relations but couldn't find any significant effects. The proximity of the partner is never a main determinant for the choice of the partner. We simply observed that subcontracting relations are often national or regional while the partner for the management of a joint venture is often an affiliate of a foreign group.

⁸ We have tested the non-linearity effect of the size. The results show that there is no such effect.

⁹ The strong correlation between the joint venture and belonging to the same group seems to indicate that the research joint venture often represents intra-group relations.

¹⁰ In the same way, firms in CIS surveys are not interviewed on their cooperations if they do not innovate.