Knowledge networks in time and space : Investigations at the node, dyad and structural levels

Innovation is a combinatorial process, in which novelty emerges through the combination or recombination of existing knowledge and materials. It implies that the process of knowledge creation is partly embedded in knowledge relations derived from the process of knowledge sourcing. Notwithstanding the straightforward argument that knowledge relations bring about innovation, our understanding of how this process unfolds over time is still limited. This motivates the present PhD thesis, which focuses on the following questions: What are the key driving forces of knowledge transfer? and How do these forces vary between regions and sectors? This PhD thesis includes a number of case studies that provide empirical insights into these research questions. The study in Chapter 2 investigated the impact of space on the likelihood and effectiveness of knowledge exchange. In the analysis, a unique dataset was employed that covers co-inventive patent data over more than 170 years (1836–2010). The empirical findings underline the continuous importance of geographical proximity for the establishment of knowledge ties as well as the increasing importance of geographical proximity for the intensity of knowledge exchange. Chapter 3 focuses on the impact of social contexts on organizations’ knowledge sourcing behaviour. To study the effect of social contexts, we investigated the evolution of the knowledge network in the Berlin biotech cluster (1992–16), where organizations from the former East and West Germany are still embedded in completely different institutional and cultural contexts. By controlling for universal tie formation forces at the dyad (e.g. geographical proximity) and network (e.g., transitivity) levels, the study isolates the effect of context-related factors. Despite a large degree of labour mobility and top-down subsidization of East–West collaborations, we found that in recent years knowledge ties are more likely to have been established among organizations within the same social context. Chapter 4 explores knowledge-sourcing networks in low-tech sectors. The study is based on primary data in the Swarzedz and Kepno clusters in Poland. Contrary to the cluster lifecycle model, the findings show that firms and associated organizations fail to establish extra-regional knowledge ties. Instead, small and medium-sized firms as well as local institutions are the main agents of learning and innovation. The empirical study in Chapter 5 focuses on the importance of sectoral attributes shaping knowledge sourcing processes and how these evolve over time. The investigation used a dataset of R&D projects in Norway (2005–16) to analyse the dynamic impact of a set of proximity dimensions on collaborative tie formation in four sectors. An analysis based on the gravity model revealed that the impact of cognitive proximity and its magnitude vary between sectors and across time periods. Chapter 6 provides a conceptual framework to alleviate issues regarding network-related interventionist policies. Finally, Chapter 7 discusses the main findings of the preceding chapters and point out a number of limitations and unresolved problems. Accordingly, this suggests several possibilities for future research and discusses how these subsequent works will further contribute to our understanding of the driving forces of knowledge sourcing.