1. Science – industry interaction and the early careers of Swiss PhDs Christian Zellner & Stéphane Lhuillery EPFL – CdM – CEMIe-mailchristian.zellner@epfl.chchristian.zellner@epfl.ch Odyssea – Station 5tel + 41 21 6930047 CH-1015 Lausannefax+ 41 21 6930020

2. Mobility and embodied knowledge transfer – different approaches based on: the measurement of mobility patterns (transition rates) from public research organisations to firms, based on the hypothesis that mobility leads to knowledge transfer (e.g., Schmoch et al 2000, Graversen 2001) surveys among firms comparing the importance of mobility with alternative transfer mechanisms (Cohen et al, 2002, Arvanitis et al 2005)  beneficial effects likely to exist, but sectoral variations and nature of the contribution to corporate innovation still relatively unexplored

3. Objective of the project: to address this issue on a systemic level by analysing the embodied knowledge transfer associated with mobility in Switzerland across fields of study and sectors to jointly analyse data on the destinations of graduates with their self-reported assessments on the transfer of various types of scientific knowledge to investigate whether the intensity of knowledge transfer by those trained to PhD-level differs from the experience of other graduates

4. Survey and sample data from the bi-annual Swiss « Absolventenbefragungen » (graduate survey) carried out by the Swiss Statistical Office –contacts each cohort approximately one year after graduation (could be at Masters- or PhD level) –postal survey / e-survey optional; participation voluntary main focus on graduates’ transition into the labour market covers all universities including the two Federal Institutes of Technology (ETHZ, EPFL) sample from the 1999 survey (cohort graduated in 1998), containing 5752 graduates at Masters- and 977 at PhD-level 3073 observations retained for the analysis, of which 673 hold a PhD (21%)

5. Distribution over fields of study (N=3073)

6. Distribution over sectors / industries (N=3073)

7. Destination of PhDs only by field of study

8. Dependent variables MATCH – perceived match of qualifications with the current job AUTONOMY – perceived autonomy and scope for exerting influence on the job SPECIAL – extent to which specialised scientific knowledge is required on the job MULTIDISC – extent to which multidisciplinary thinking is required on the job SCIENTIFIC - extent to which scientific methods are applied in the job CRITICAL - extent to which critical thinking and judgement are required on the job

9. Specification of the model For j = 1,…,6

10. Main results PhD mobility leads to significantly higher transfer of specialised scientific knowledge and scientific methods than do lower degrees; match of qualifications is higher mathematics and computer science, as well as various enginering disciplines are characterised by more intensive transfer of specialised scientific knowledge scientific methods most important in computer science, physics, biology and mechanical engineering, but few significant differences across destination sectors respondents‘ position, differentiated by supervision responsibility, strong determinant of the transfer of specialised knowledge and importance of critical thinking

11. Conclusions results broadly reflect the specificities and traditional strengths of the Swiss economy, illustrating the strong links between higher education system and economic structure (i.e., financial industry, health, manufacturing, ICT, chemical industry) embodied knowledge transfer not automatic result of mobility, but depending on how graduates are deployed by the firm (including position and autonomy granted)