Collaboration patterns between University of Cambridge and silicon fen firms based on publication analysis

This research investigates the theory of knowledge transfer through university industry collaboration and seeks to understand the possible collaboration patterns that exist between the University of Cambridge (UoC) and a cluster of high tech firms located in close proximity to the university known as Silicon Fen (SF). Main hypothesis of the research is whether ‗It is possible to establish patterns for collaboration between UoC and SF firms‘. To answer this hypothesis, 18 sub hypotheses are proposed and studied by a positivist deductive quantitative approach to correlate characteristics of firms such as size, sector, and age with various tangible indicators of collaboration, including the number of joint scientific publications (NJSPs) and joint patents (NJPs), as well as the scientific (CSC) and technological collaboration strength (TCS), and the number of women involved in copatenting (NWCP). Out of the 78,873 firms located in SF, more than 100 high tech collaborative firms are found to have JSP or JP with UoC. Accordingly, 5,782 JSPs and 55 JPs were sampled using bibliometric methods to evaluate the collaboration parameters and characteristics of corresponding firms. Among all business sectors, the Biotech/Pharma is found to have the greatest NJSPs, NJPs, CSC, TSC, and NWCP. It is also found that older/larger SF firms have greater NJSPs with UoC and CSC value, while older SF firms have greater NJPs. In contrast, younger SF firms have greater NJPs and TCS with UoC, while older SF firms have a greater NWCP. Therefore, results obtained confirm the main hypothesis of the research and may enable policymakers to provide effective strategies to enhance collaboration between less collaborative SF firms and UoC. The results contribute to the body of knowledge on university industry collaboration by providing evidence for the case of SF UoC as a cluster of high tech firms and a prominent research university located in close geographic proximity.