This PhD thesis explores the determinants and impact of UniversityIndustry (U-I) knowledge transfer. It focuses on the UK as well as a number of European regions and aims at filling several gaps in the literature. Firstly, I examine the role of scientific (i.e. university) and market (i.e. customers, competitors, suppliers) knowledge for patent inventors working inside firms. I use data from an original survey of industry inventors combined with patent data from the European Patent Office and I employ an econometric strategy rarely applied at inventor’s level (i.e. productivity approach). My finding is that the amount and quality of patents invented increase when inventors draw their knowledge jointly from a wide set of knowledge sources, rather than from only one of these. Secondly, I investigate the impact of U-I research collaborations on UK firms’ R&D activities. The data consists of a set of publicly funded U-I partnerships combined with firm-level data available from the UK Office for National Statistics. I combine propensity score matching with OLS regression to select an ad-hoc control group and obtain a reliable estimate of the impact of U-I collaboration on firms. My finding is that treated firms’ R&D expenditure and share of R&D employment both increase after participation to U-I partnerships. Thirdly, I explore the role of research quality as a determinant of UK university departments’ engagement in U-I collaboration. I use data on publicly funded U-I collaboration combined with data on UK universities and I employ OLS regression. My finding is that academic quality displays a mixture of negative and positive relationship with the volume of private funding for U-I collaboration, and that this is interdependent with the level of academia’s past experience in U-I collaboration. Together, these chapters make important contributions to a vast but still puzzled literature on U-I knowledge transfer activities.