Research Open Innovation at the R&D Project Level

Abstract

In nowadays increasingly competitive technology landscape, collaboration with external partners in firms’ R&D process becomes an imperative for innovating firms (Chesbrough, 2003). Despite the popularity of open innovation and its proposed benefits, real-life practices show that not every successful firm adopts open innovation strategies, and among those that do conduct open innovation, many of them fail. Open innovation was found to have a positive (Laursen and Salter, 2006) or negative (Knudsen and Mortensen, 2011; Kessler et al., 2001) on firms’ innovation performance. Other scholars found it has no effect at all (Campbell and Cooper, 1999). The wide range of performance heterogeneity among firms in their open innovation practices calls for more in-depth examination of this strategy. The existing quantitative studies on open innovation have been mostly focusing on the firm as the observation unit. Although firm-level analyses are important for understanding open innovation principles, as the vast majority of R&D activities are essentially carried out as research projects (Pisano, 1990; Cassiman et al., 2009), aggregating data at the firm level may lead to spurious conclusions on the practice of open innovation, and subsequently, its effects on innovation performance. Responding to the call of Chesbrough and colleagues (2006, p. 287), “neither the practice of, nor the research on open innovation are limited to the level of the firm”, and “the sub-firm level of analysis is particularly salient in understanding the sources of innovation” (2006, p. 287), this thesis is among the very first contributions that examine open innovation at other levels, being the research project level. Research projects are highly relevant as a sub-firm level of analysis as most collaborative innovation initiatives are executed at the research project level: A wide range of characteristics of the research projects can capture the heterogeneity of the impact of open innovation on performance when it is measured at the firm level. More specifically, in this thesis I examine the effect of (outside-in) open innovation practices on two types of innovation performance of research projects, namely, project innovation speed and financial performance. I further investigated a number of contingent effects of open innovation, from internal, external, and the process perspective of open innovation. Based on data from a large multinational, multidivisional global firm, I tested a number of hypotheses relating to the effect and the contingencies of open innovation. The results shed lights on the existing open innovation literature. While my results bring evidence that open innovation is indeed beneficial for firms’ innovation performance, I find that the effect of open innovation hardly comes on its own. Rather, it is contingent on a wide range of factors, which are internal or external to the firm. Those factors include - but are not limited to - the type of partners that are involved into collaborations, the timing of collaborations, the project management process of the collaborations, as well as the technology fields targeted in the collaborations. Inappropriate management of these factors may result in a sub-optimal, effect of open innovation strategies. Hence, despite its potential benefits, firms should adopt open innovation with caution. Given its costs and risks, firms should bear in mind the pros and cons of open innovation strategies and use it flexibly depending on the circumstances. Drawing on the findings of this thesis, I can conclude the following: 1) In terms of the effect of open innovation, market-based partners (customers and suppliers) are beneficial to speed up the innovation, but do not affect project financial returns. On the contrary, science-based partners (universities and research institutions) are instrumental for generating higher levels of financials, but do not seem to influence project speed. 2) In terms of contingency effects of open innovation, I find that to generate higher financial returns, successful open innovators strictly manage market-based partnerships but loosely monitor science-based partnerships. Moreover, they innovate at a moderate pace, neither too fast nor too slow. Additionally, they follow a certain length of collaboration time in a continuous manner, and collaborate with science-based partners prior to collaboration with market-based partners. 3) Last but not least, successful open innovators collaborate more in technological fields that are relatively distant from their core technologies, instead of collaborating in their core technological fields.