Knowledge networks in innovation-driven collaborations

Knowledge intensive or high-tech industries are widely regarded as important for overall national economic growth and competitiveness, while survival of these industries relies on their ability to create new knowledge and transform that knowledge into new technologies. In these industries, one increasing mode of knowledge creation is through collaboration with peers and other partners. Such collaborations often happen within inter-organisational knowledge networks (k-networks). The increasing attention on k-networks stems from several reasons like turbulent and dynamic markets, cost reduction, fast response to market demands or limited core competencies. The high pace and radical innovation projects in knowledge-based industries emphasise the need for research in the area of k-networks, particularly in the biotechnology industry. In this context, understanding the way that k-networks can contribute to knowledge creation, seems critical for the survival of knowledge-based industries and accordingly also has a significant influence on society as a whole. While the literature focuses on the contribution of network structure, it also shows that the prior research has produced seemingly contradictory results. A growing body of research highlights the need for going beyond the network structure to address other constructs of k-networks and understand the way that interactions among these constructs may influence knowledge creation. My research first reviewed the k-network literature thoroughly and identified content and process together with network structure as inter-related constructs of k-networks. More particularly knowledge diversity as a characteristic of content, collaboration with partners as the characteristics of process and centrality and density as the characteristics of structure are identified as the constructs interacting with each other in the context of knowledge creation. These constructs are conceptualised into a theoretical model that is examined by employing a quantitative-qualitative mixed method inquiry. Focusing on the biotechnology industry of Victoria, Australia as a knowledge intensive industry in which knowledge creation is normally tied with patenting, my research used patent co-authorship network as a k-network that involves innovation-driven collaborations. To map the network and study the structural constructs, first social network analysis, was used. Then my research studied the interaction between constructs of the k-networks by using moderated multiple regressions followed by interaction analysis. As a result, three significant interactions were found which provided a basis to introduce a novel typology of k-network configurations. To seek confirmation and explanation for these quantitative findings, four cases were selected purposefully to study all the possible k-network configurations in more detail. Using this sequential quantitative-qualitative mixed method inquiry, my research shows how the interactions of the content-process-structure of k-networks may support knowledge creation for actors in the knowledge intensive industries. My research extends the knowledge network research particularly in the domain of inter-organisational innovation-driven collaborations. The thesis explores the implications of findings and the potential to contribute to explaining previous contradictory results in k-network research, as well as practical contributions for private companies and for policy makers.