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Inter-temporal patterns of R&D collaboration and innovative performance

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Abstract

While prior studies have investigated the effect of collaborative R&D with different partner types (suppliers, customers, competitors and research institutions and universities) on firms’ innovative performance, the implications of dynamic patterns in these collaborations have not received attention. In a large panel of Spanish innovating firms operating in a broad range of industries during the period 2004–2011, we examine the differential effects of recently formed, persistent, and recently discontinued collaboration on innovative performance. Persistence is the most common pattern of collaboration, while discontinuities are most often observed for competitor collaboration. We find that it is persistent collaboration that has a systematically positive effect on innovativeness. With the exception of recently formed collaboration with universities and research institutes, other temporal patterns of collaboration do not significantly improve innovation performance. Implications of these findings are discussed.

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Notes

  1. There is a rather extensive body of research investigating the antecedents of failure of inter-firm partnering (e.g., Das and Teng 2000; Lhuillery and Pfister 2009; Parkhe 1993; Saxton 1997). These studies, however, do not focus on the performance consequences of failure of inter-firm partnering. Belderbos et al. (2012) considered antecedents of persistence in collaboration. Lokshin et al. (2011) examined performance consequences of partnership malfunctioning but without differentiating among partner types or among temporal patterns of collaboration.

  2. We also estimated nonlinear relationships between firm size and innovation performance by including a quadratic term of size, but its coefficient was insignificant while the linear term remained significantly positive. Similarly, F-tests conducted on the coefficients of interests after performing split sample analysis for small and medium sized firm versus larger firms showed no significant differences between the two samples.

  3. We note that exporting may also be the result of successful innovation, implying reverse causality. Since export status is measured in year t − 1 and innovative performance in year t, this concern is mitigated. Excluding export status does not materially affect the estimation results for the focal variable, while the results indicate that it does have consequences for subsequent innovative performance.

  4. Given that the dependent variable is the natural logarithm of innovative performance (the sales due to innovative products per employee) the coefficients of the dummy variables represent approximately the proportional increase in innovative performance due to collaboration: \( \beta = \frac{d\ln y}{dx} = \frac{dy/y}{dx} \).

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Authors and Affiliations

  1. Department of Managerial Economics, Strategy and Innovation, University of Leuven, Naamsestraat 69, 3000, Louvain, Belgium

    René Belderbos

  2. Maastricht University, Maastricht, The Netherlands

    René Belderbos, Martin Carree & Boris Lokshin

  3. UNU-MERIT, Maastricht, The Netherlands

    René Belderbos

  4. Facultad Latinoamericána de Ciencias Sociales, Guayaquil, Ecuador

    Juan Fernández Sastre

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  1. René Belderbos
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  2. Martin Carree
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  3. Boris Lokshin
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  4. Juan Fernández Sastre
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Correspondence to René Belderbos.

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Belderbos, R., Carree, M., Lokshin, B. et al. Inter-temporal patterns of R&D collaboration and innovative performance. J Technol Transf 40, 123–137 (2015). https://doi.org/10.1007/s10961-014-9332-4

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