Innovation in General Purpose Technologies : How Knowledge Gains when It Is Shared

This dissertation tackles the different aspects of the creation and transmission of (new) knowledge in the context of the characteristics of a general purpose technology (GPT). Particular emphasis is put on the role of the composition of knowledge as well as the corresponding (presumed) knowledge spillovers on the one hand and on the concrete impact of collaboration and knowledge sharing in innovator networks on the other hand. The thesis offers a coherent literature review in its first part, analysing the theoretical role of knowledge for innovation and growth as well as the role of knowledge diffusion and sharing. Although the development of GPTs is particularly knowledgeand innovation-intensive and GPTs are found to be ’engines of growth’, the role of knowledge for innovation in GPTs has not been distinctive subject to investigation yet. Therefore, the two mentioned sets of research questions were tackled empirically in this thesis using the showcase example of nanotechnology. Nanotechnology is argued to be the key technology of the future, and empirical analyses in this thesis using patent and publication data provided evidence that there is sensible reason to consider nanotechnology as GPT. The first array of research questions is concerned with the role of local knowledge composition and spillovers for the development of nanotechnology. Two different approaches capture these issues. The first one investigates how the characteristics of the regional technological nano-knowledge base as approximated (mainly) by patents influence the creation of new nanoknowledge. Panel negative binomial regression analyses are employed to disentangle the effects. The second approach captures the performance of nano-firms depending on the local endowment with knowledge as investigated by means of OLS and fixed effects panel analyses. The central finding is that the regional endowment with knowledge impacts the development of nanotechnology. Concerning the composition of the knowledge bases, evidence suggests that specialisation and diversity are positively impacting innovation in nanotechnology. More particularly both are necessary to support nanotechnology’s characteristics both as high-technology and as GPT. Focusing on the role of collaboration and knowledge sharing in networks, the second array of research questions is tackled by another two analyses. One analysis focuses on the development of the role of collaboration and networking. The means of social network analysis of German nanotechnology patents’ co-contributorship networks shed light on the relationship between collaboration, the efficiency of the networks and the technological overlap (and hence the potential for cooperation) and the development of nanotechnology. The second analysis more particularly puts an emphasis on the factors that impact the generality of a patent. Therefore variables such as intensity of collaboration, access to knowledge, experience and overlap of technological background are included into fractional logit analyses. Findings include that the performance of a GPT can be enhanced through collaboration by offering efficient means for the organisation and coordination of knowledge sharing and knowledge spillovers and by fostering an increase in the technology’s generality level due to knowledge sharing in teams and networks.