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From science to license: an exploratory analysis of the value of academic patents

From science to license: an exploratory analysis of the value of academic patents. E. SAPSALIS *1 , B. van POTTELSBERGHE *². 2nd ExTra/DIME workshop EPFL, Lausanne, 29-30 Sept 2006. * ULB, 1 FNRS Research Fellow, ² Chief Economist at European Patent Office.

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From science to license: an exploratory analysis of the value of academic patents

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  1. From science to license: an exploratory analysis of the value of academic patents E. SAPSALIS*1 , B. van POTTELSBERGHE*² 2nd ExTra/DIME workshop EPFL, Lausanne, 29-30 Sept 2006 * ULB, 1 FNRS Research Fellow, ² Chief Economist at European Patent Office The views expressed in this article are purely those of the authors and may not in any circumstances be regarded as stating an official position of the EPO or of the ULB. This paper was partly written when E. Sapsalis was appointed Adj. Associate Research Scholar at Columbia Univ. (NY-USA). We thank the FNRS, the ULB and the foundation MC Adam for supporting financially this research stay Contact: esapsali@ulb.ac.be

  2. Objective • Analyse the value determinants of the technological, industrial, entrepreneurial impact of academic patents

  3. Content • Academic patenting revolution • Data • Empirical Models • Results • Conclusions

  4. Academic Revolution

  5. The academic revolution Source: European Patent Office: own calculations

  6. IP-oriented emerging technologies ; Biotech, Nanotech,… Patent-oriented laws USA/European countries: Dayh-Dole Act like legislations More active role that academia has been asked to play in the Knowledge Economy Academic Patenting Revolution

  7. Pending questions • Management of Technology transfer • Spin-offs; licenses; research contracts/ alliances etc… • Debates related to the roles of university • Dissemination of science • The balance between the different missions of universities • Quality of research; quality of patents

  8. Patent Value

  9. State of the art (1) • The distribution of patents’ value is highly skewed • Value Proxies • Monetary value of a patent (e.g. Harhoff et al., 1999, 2002) • Present value evaluated by experts (e.g. Reitzig, 2003) • Forward citations (e.g. Lerner, 1994; Sapsalis and van Pottelsberghe, 2006, 2007) • Composite indicator (e.g. Lanjouw and Schankerman, 1999) • Creation of a start-up (e.g. Shane, 2001) • Probability to get a patent … • Granted (e.g. Guellec and van Pottelsberghe, 2000) • Opposed (e.g. Lanjouw and Schankerman, 1997) • Renewed (e.g. Lanjouw and Schankerman, 1999) • Licensed (e.g. Dechenaux et al., 2003)

  10. State of the art (2) • Value determinants • Forward citations ++++ (ex: Shane, 2001) • Patent family size ++ (ex: Lanjouw and Schankerman, 1999) • Results of opposition & annulment procedures : + (ex: Harhoff et al, 2003) • Backward patent citations: + (ex: Harhoff and Reitzig, 2000) • Non-patent citations: (+) (ex: Harhoff and Reitzig, 2000) • Claims: (+) (ex: Lanjouw and Schankerman, 1997) • Patent scope: (+/-) (ex: Lerner, 1994) • Time: + (ex: Guellec and van Pottelsberghe, 2002) • Technical field: (*) (ex: Harhoff et al, 1999) • Ownership characteristics: (*) (ex: Guellec and van Pottelsberghe, 2002)

  11. Value determinants

  12. Data sets

  13. Data • Data Source: DELPHION database • Patents’ priority date: 1985-2003 • Assignees : 6 Belgian universities • UCL, ULB, Ulg, KUL, UG, VUB • EPO patents grouped in patent families • 364 EPO patent families • 334 EPO patent families with available exploitation data • 142 licensed patents • 53 licensed to spin-offs • 89 licensed to established companies

  14. Belgian academic patents

  15. Models

  16. Negative Binomial Model Number of patent citations Probit/Logit Model License agreements With established companies With spin-offs Empirical implementation (1)

  17. Dependent variables: Technological impact : # FPC Industrial impact: dummy variable standing for a license given to industry Entrepreneurial impact: dummy variable standing for a licence given to a spin-off Empirical implementation (2)

  18. Independent variables: Technological impact: # FPC & origin Science knowledge : # NPC & origin Technological knowledge: # BPC & origin Ownership: # Inv; # Ass & type IP protection: Time; Patent Family; Claims; Scope Empirical implementation (3)

  19. Setting hypotheses (1) • Technological impact •  Industry License = f+(FPC-self; FPC-PRI ; FPC-Co) •  Startup License = f+(FPC-PRI ; FPC-Co) • Scientific base •  # forward patent citations = f+(NPC-self); f -(NPC-non self) • Industry License = f+(NPC-self); f -(NPC-non self) •  Startup License = f+(NPC-self); f -(NPC-non self)

  20. Setting hypotheses (2) • Technological Base •  # forward patent citations = f+(BPC-PRI) ; f -(BPC-Self) •  Industry License = f+(BPC-self; BPC-PRI ; BPC-Co) •  Startup License = f+(BPC-PRI ; BPC-Co) • Ownership •  # forward patent citations = f+(Ass-PRI); •  Industry License = f+(Ass-Ind); •  Startup License = f+(NPC-self); f -(NPC-non self)

  21. Setting hypotheses (3) • IP Protection •  # forward patent citations = f+(Fam; Claim); •  Industry License = f+(Fam; Claim); f -(Scope) •  Startup License = f+(Fam; Claim; Scope);

  22. Econometric Results

  23. ImpactsTechnological, industrial and entrepreneurial

  24. Obs 334 334 301 Log Lik. -453 -139 -120

  25. LicensingEstablished Companies vs. Spin-offs

  26. 129 Obs ; 13 Time dummies ; Log Lik. :-54

  27. Concluding remarks (1) Policy implications Focus on high level scientists  importance of tacit knowledge Importance of collaboration Academic collaboration: + tech impact ; - ind impact Industrial collaboration: + ind impact  importance of close contact with industry

  28. Concluding remarks (2) Management implications TTO and Funding bodies  Management of IP co-developed by different public research institutions Spin-offs and established companies exploit different types of patents Further research Analyse commercial impact Analyse the impact of academic inventions on industrial portfolio

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