Exploring connectivity : invention, innovation and knowledge transfer in the university-industry interface

Abstract: Universities are expected to create knowledge and be involved in knowledge transfer with society. This is accomplished through the universities’ three missions; 1) teaching, 2) research and 3) innovation and social engagement. The focus of this thesis is knowledge transfer for the purpose of innovation in the university-industry interface. Policy makers have strong faith in innovation and emphasise the importance of innovation and knowledge transfer in the intersection between universities and industry for future economic growth and employment. University scholars have, in the multi-disciplinary field of innovation studies, spent considerable effort to shed light on knowledge transfer processes and to investigate the myriad of mechanisms through which knowledge is exchanged. For instance, efforts have been made to measure knowledge transfer itself or the outcomes of knowledge transfer. A better understanding of knowledge transfer processes, outcomes and impact could provide a foundation for more efficient and tailored innovation support infrastructures, regulations and management of university-industry interaction. However, many prior studies are built on quantitative and unidimensional methods, often based on statistics that either over- or under estimates innovation and knowledge transfer. This thesis argues that there is a need to widen the perspective to get a better understanding of the knowledge transfer activities taking place in the university-industry interface. Also, there is a need of a more comprehensive innovation statistics and metrics in the university innovation interface. This thesis draws on, and aims at contributing to the research areas of university-industry relations, knowledge transfer and social network theory. Thus, this thesis addresses the question of how the mapping of ‘hidden’ connections could provide insights into the management of knowledge transfer in the university-industry interface. The four included papers address this overarching question in different ways with different methodological approaches. Based on the problem of lacking statistics on university patenting, Paper I investigates how inventive productivity can be measured in the academic setting. Paper I also introduces the Karolinska Institutet Intellectual Property (KIIP) project which included a description of the construction of the KIIP database. The KIIP database contains comprehensive statistics on patented inventions derived from Karolinska Institutet between 1995 and 2010. Paper II, is a longitudinal study of knowledge transfer paths from the university to third parties. It suggests the ABC-framework of patent ownership transfer modes. Using social network analysis, Paper III investigates the board network structure, composition and evolution of 65 university spin offs. Findings show that investors hold central network positions in the network over time and are therefore in a position to both facilitate and hinder knowledge transfer. Results also show that the board network has a stabile ‘small word’ feature over time indicating dense clustering and short transfer distances across the network. Paper IV takes an individual level perspective and addresses the question of how individuals search for knowledge to solve problems in product development processes. Based on grounded theory methodology, an emergent theoretical framework of individual level knowledge search processes is suggested that emphasises the importance of social networks. In conclusion, the findings of this thesis suggest the there is a need to apply a more holistic and multi-level methodological and theoretical perspectives to gain better understanding of knowledge transfer in the university-industry interface. This includes building comprehensive innovation statistics, applying analysis methods, such as social network analysis on micro-, meso- and macro level, developing qualitative impact oriented innovation measures, and using pedagogical strength of social network visualisations. By bringing such ‘hidden’ connections to the surface a more tailored management of knowledge transfer and innovation support systems could be developed.