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Comments: Labour Mobility of Academic Inventors…

Comments: Labour Mobility of Academic Inventors…. Paula Stephan Georgia State University Lausanne September 2006. Topic. Topic is important Knowledge transfers are rarely examined through movement of people Yet clear mobility plays a role, especially in transfer of tacit knowledge

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Comments: Labour Mobility of Academic Inventors…

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  1. Comments: Labour Mobility of Academic Inventors… Paula Stephan Georgia State University Lausanne September 2006

  2. Topic • Topic is important • Knowledge transfers are rarely examined through movement of people • Yet clear mobility plays a role, especially in transfer of tacit knowledge • Certainly highly appropriate given focus of this conference

  3. Approach • Use PatVal database to analyze mobility of individuals who had a university affiliation at time of patent • A relatively broad definition of university employees in the sense that some do not have a PhD

  4. Sample/Goal • PatVal survey had a response from 9017 inventors of a patent between 1993-1997. Replied between July 2003-April 2004. • 433 of these were at a university at time of patenting event • Goal: analyze the mobility of these university inventors.

  5. Assignment Finding • 82.2% of the patents made by one of the 433 inventors with a university affiliation were not assigned to the university • This is “big” news. • Suggests assignment data grossly underestimates what is going on at the university • Raises question as to why--for some countries “Professor Privilege” explains outcome; but clearly more is going on here.

  6. Sample for Analysis of Mobility • Winnow sample of 433 to 230 • 22 move to a firm (9 self employed) • 22 move to another PRO • Further winnow sample of 230 to 198 • 19 move to a firm • 15 move to another PRO

  7. Hazard of Moving • Examine relationship between approximately 25 variables and hazard of moving subsequent to patenting • Estimate duration model using a step-wise approach, entering sets of variables in 9 clusters

  8. Major Findings • Less likely to move the more experience prior to joining university and more tenure at the university • Authors see this as consistent with work by Dasgupta and David—more university capital one has accumulated less likely to move

  9. Patent Characteristics and Mobility • Higher patent value (as assessed by respondent at time of interview) more likely to move—tacit knowledge interpretation is appealing. • Presence of co-inventors working in another organization increases likelihood of moving • Find no evidence that assignment relates to mobility.

  10. Which Sector? • Estimate a competing risks model of moving to either a company or a PRO • Results are somewhat fragile due to sample size but suggest • Patvalue relates to move to business • Collaboration relates to move to another PRO • Multiple co-inventors decreases probability of moving to a firm—no need for the tacit knowledge embodied in the inventor?

  11. Policy • Authors say results suggest that knowledge transferred to industry may be not of top quality as it is not the high caliber researchers that move but those of lower scientific and technological output. • Mobility that exists is concentrated in certain countries

  12. Questions/Comments • How much of “Big News” assignment finding relates to fact that 139 of the 433 were “working in a private organization during the patent discovery process” (p. 9) • Way in which multiple patents are handled is difficult to follow. Page 10 suggests that these inventors were dropped; other places get sense they were not dropped. • Is patent value variable credible? Would not the inventor see a high value ex post if industry were interested? • Selling. Ability to sell one’s science is important in engaging in entrepreneurial activity. Possible that those who are good at selling themselves (and hence get a position with industry) also see their patents as having a higher value.

  13. Cashing Out Hypothesis • One could hypothesize exactly the opposite result with regard to experience—and indeed Dasgupta and David have • Cashing out: One accumulates human capital and reputation and then cashes out towards end of career • Why don’t authors find such a result? • Do not enter variables in a non-linear manner • Include individuals in the sample who do not have long-run prospects of remaining in the university and must exit

  14. Other Comments • Small size of sample provides an opportunity • Do “case studies” by looking at cvs (if this is possible) of the 198; • see extent to which case study validates the empirical results • Examine contribution of movers subsequent to move • Create a matched sample of non-inventors so that larger question of how inventing affects mobility could be investigated

  15. Policy • Little evidence that it is “low” quality who move; It’s early career people who move • More general concern for Europe may be why so few PhDs work in industry. • A major means by which U.S. industry absorbs public knowledge is through hiring PhDs. • PhDs working in industry play not only an absorptive role but an innovative role as well.

  16. Thanks! • For providing an in-depth analysis of mobility • For raising a number of interesting questions that are seldom addressed by other researchers • For reminding us that assignment data provides but a small piece of the university-knowledge transfer picture.

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