Venture capitalists (VCs) often serve on the board of mature public firms long after their initial public offering (IPO), even for companies that were not VC-backed at the IPO. Board appointments of VC directors are followed by increases in research and development intensity, innovation output, and greater deal activity with other VC-backed firms. VC director appointments are associated with positive announcement returns and are followed by an improvement in operating performance. Firms experience higher announcement returns from acquisitions of VC-backed targets following the appointment of a VC director to the board. Hence, in addition to providing finance, monitoring and advice for small private firms, VCs play a significant role in mature public firms and have a broader influence in promoting innovation than has been established in the literature.

Our primary goal is to analyse the drivers of evolutionary network change processes by using a stochastic actor-based simulation approach. We contribute to the literature by combining two unique datasets, concerning the German laser and automotive industry, between 2002 and 2006 to explore whether geographical, network-related, and techno-logical determinants affect the evolution of networks, and if so, as to what extent these determinants systematically differ for science-driven industries compared to scale-intensive industries. Our results provide empirical evidence for the explanatory power of network-related determinants in both industries. The ‘experience effect’ as well as the ‘transitivity effects’ are significant for both industries but more pronounced for laser manufacturing firms. When it comes to ‘geographical effects’ and ‘technological ef-fects’ the picture changes considerably. While geographical proximity plays an important role in the automotive industry, firms in the laser industry seem to be less dependent on geographical closeness to cooperation partners; instead they rather search out for cooperation opportunities in distance. This might reflect the strong dependence of firms in science-driven industries to access diverse external knowledge, which cannot necessarily be found in the close geographical surrounding. Technological proximity negatively influences cooperation decisions for laser source manufacturers, yet has no impact for automotive firms. In other words, technological heterogeneity seems to ex-plain, at least in science-driven industries, the attractiveness of potential cooperation partners.

Empirical evidence on the evolution of innovation networks within high-tech industries is still scant. We investigate network formation processes by analyzing the timing of firms to enter R&D cooperations, using data on laser source manufacturers in Germany, 1990-2010. Network measures are constructed from a unique industry database that allows us to track both the formation and the termination of ties. Regression results reveal that a firm's knowledge endowment (and cooperation experience) shortens the duration to first (and consecutive) cooperation events. The previous occupation of strategic network positions is closely related to the establishment of further R&D cooperations at a swift pace. Geographic co-location produces mixed results in our analysis.

In the literature on environmental innovations R&D collaborations have been identified as a critical determinant of a firm’s environmental innovation performance. However, the literature suggests that R&D collaboration is not always beneficial. Therefore, a more elaborated analysis of the effects of R&D collaborations on a firm’s environmental innovation performance is necessary. This paper investigates the impact of R&D col-laborations with different partner types such as customers, competitors, suppliers, uni-versities, governmental research institutes, consultants and other firms within the same firm group on a firm’s environmental innovation performance. In addition, this paper addresses the question of whether the diversity of R&D collaboration partners is im-portant for the environmental innovation performance. Firm-level data from 2,337 Ger-man service and manufacturing firms are used in the regression analysis. The results suggest that R&D collaboration with suppliers, customers, universities, governmental research institutes, consultants and other firms within the same firm group has a signifi-cantly positive impact on a firm’s environmental innovation performance, whereas col-laboration with competitors has no significant impact. The diversity of R&D collaboration partners has a significantly positive impact on a firm’s environmental innovation performance.

We study how firm innovativeness is related to individual cooperation events and the structure and dynamics of firms’ ego-networks employing a unique panel dataset for the full population of 233 German laser source manufactures between 1990 and 2010. Firm innovativeness is measured by yearly patent applications as well as patent grants with a two year time-lag. Network measures are calculated on the basis of 570 knowledge-related publicly funded R&D alliances. Estimation results from a panel data count model with fixed effects are suggestive of direct innovation effects due to individual cooperation events, but only as long as structural ego-network characteristics are neglected. Innovativeness is robustly related to ego-network size and ego-network brokerage whereas ego-network density reveals some surprising results.

Innovation systems abroad become more and more important to multinational enterprises (MNEs) as sources of knowledge and technology. On the other hand, MNEs’ foreign subsidiaries can be considered agents of technological and economic development in their target location region. Applying a logit estimation, this discussion paper investigates which firm- and region-specific determinants influence cooperations in the area of research and development (R&D) between the foreign subsidiary and the regional innovation system. Results suggest that especially the foreign subsidiary’s mandate in terms of R&D and management, its size and the regional knowledge stock are positively associated with these co-operations. The analysis focuses on posttransition economies, using the example of five selected CEE countries and East Germany. We exploit a unique dataset – the IWH FDI Micro Database – which holds information on 1,245 foreign subsidiaries in this region.

Wissensintensive Interaktionen sind mit einer Reihe von Vor- und Nachteilen für die beteiligten Akteure verbunden. Deshalb hat sich ein Literaturstrang entwickelt, welcher der Fragestellung nachgeht, wie sich FuE-Kooperationen auf die Leistungsfähigkeit von Firmen und Regionen auswirken. Diese Studien kommen zu unterschiedlichen Ergebnissen. Das Papier versucht die verschiedenen Ergebnisse der Literatur zusammenzufassen. Ein weiteres Ziel ist es, die in der Literatur verwendeten Methoden zur Bearbeitung der Fragestellung kritisch zu diskutieren. Zudem geht das Papier der Frage nach, inwiefern die in der Literatur verwendeten Methoden und Ansätze die Ergebnisse der Studien beeinflussen. Zur Bearbeitung dieser Fragestellungen wird eine Metaanalyse der relevanten Literatur durchgeführt. Dabei wird gezeigt, dass FuE-Kooperationen einen positiven Effekt auf die Leistungsfähigkeit von Firmen und Regionen haben. Zudem gibt es starke Evidenz dafür, dass die verwendeten Methoden und Ansätze die Ergebnisse der Studien beeinflussen.

Innovation is the result of an interactive process. Knowledge-intensive interactions among different partners are associated with a variety of advantages and disadvantages for the actors involved. Therefore, a rich body of literature investigating the impact of R&D collaboration networks on the innovation performance of firms and regions has developed over the last two decades. Those studies come to different results. The aims of this paper are manifold. First, the paper summarizes the results of the relevant literature. Second, a brief overview of the established methods and approaches used in the literature to investigate this research question is given. The third objective is to answer the question whether the achieved results in the literature are predetermined by the employed methods. Finally, relevant gaps for further research are identified. To answer these questions a meta-analysis of the relevant literature is conducted. This study shows that knowledge-intensive interactions have a rather positive impact on the performance of firms and regions. There is also evidence that the employed methods and approaches used in the literature to investigate this research question predetermine the outcome of the research.

Technological innovation is fundamental to firm performance and economic prosperity. The aim of this book is to contribute to an in-depth understanding of collective innovation processes by analyzing publicly funded R&D cooperation and innovation networks in the German laser industry. Standing in a neo-Schumpeterian tradition, it employs interdisciplinary analytical concepts and draws upon a unique longitudinal dataset from the laser industry that covers more than two decades of observations. In brief, the book makes a valuable contribution by exploring how and why firm-specific R&D cooperation activities and network positions, large-scale network patterns, and evolutionary network change processes affect the innovative performance of laser source manufacturers in Germany.

We seek to understand the relationship between network change determinants, network change processes at the micro level and structural consequences at the overall network level. Our conceptual framework considers three groups of determinants – organizational, relational and contextual. Selected factors within these groups are assumed to cause network change processes at the micro level – tie formations and tie terminations – and to shape the structural network configuration at the overall network level. We apply a unique longitudinal event history dataset based on the full population of 233 German laser source manufacturers and 570 publicly-funded cooperation projects to answer the following research question: What kind of exogenous or endogenous determinants affect a firm’s propensity and timing to cooperate and enter the network? Estimation results from a non-parametric event history model indicate that young micro firms enter the network later than small-sized and large firms. An in-depth analysis of the size effects for medium-sized firms provides some unexpected yet quite interesting findings. The choice of cooperation type makes no significant difference for the firms’ timing to enter the network. Finally, the analysis of contextual determinants shows that cluster membership can, but do not necessarily, affect a firm’s timing to cooperate.