© goddard & isabelle 20061 druid summer conference june 18 th, 2006 john gabriel goddard imri...

© Goddard & Isabelle 2006 1

DRUID Summer ConferenceJune 18th, 2006

John Gabriel GODDARDIMRI (Université Paris-Dauphine)

<[email protected]>

Marc ISABELLEIMRI (Université Paris-Dauphine) & CEA

<[email protected]>

Part I / How do Public Laboratories Collaborate with Industry? New Survey Evidence from France

Part II / Managing Intellectual Assets Within Knowledge-based Partnerships: Insights from a Survey of Public Laboratories


Outline of the presentation

Introduction– Public research and industry: the context

Overview– The survey– The sample– The collaborations

– Part II

Conclusions and perspectives

References

– PROs’ patents and licenses: the visible part of the iceberg?

Results– Part I




Public research and industry: the context

Shift since 1980s, first experienced in US (Bayh-Dole act)

– more collaboration between public research and firms

– increase in patent filing by public research organisations

– increase in licensing agreements from PROs to firms

double purpose =

In France, loi de 1999

– speed the innovation rate in the economy

– increase leveraging of resources from their activities by PROs




PROs’ patents and licenses: the visible part of the iceberg?

Most survey-based studies focus on PROs’ patenting and licensing activities (Thursby et al., 2001; Thursby & Thursby, 2003)

Very few address the issue of other channels of K&T transfer to firms (Cohen et al. work with Carnegie-Mellon survey, Levin et al. with Yale survey)

– fit with linear model– involve codified knowledge– transfer embodied technologies

Possible reasons for this bias =

– two-way interactions– involve tacit knowledge– technologies issued from PROs are embryonic

– substantive: patented inventions expected to be commercially useful

– methodological: extensive record of information / databases associatedwith patents




The survey

Focus on IP issues (protection of intangible assets, transmission / diffusion of knowledge)

Questionnaire sent to 1800 lab directors 1st semester, 2004

Questionnaire similar to Cohen et al. (1994)

Large French government labs (CNRS, CEA, INRA, INSERM, INRIA, Institut Pasteur, Institut Curie)

Selected S&T fields: chemistry, life sciences, ICT

Targeted on public research labs

NB: information about the collaboration portfolio of public labs, NOT about collaborations themselves




The sample

146 responses 130 labs have collaborations with firms

PROsnumber=146

regionnumber=146

sizenumber=146

S&T fieldsnumber=146

7,200 personnel wide variation, long tail (4 megalabs over 250 pers.)

fairly representative of PROs’ size (except INSERM)

life sciences dominant, ICT marginal

dominance of IDF, probable bias in favour of PACA (many chemistry labs of CEA there)




The collaborations

874 collaborations of every nature (6,9 per lab on average)

localisation of partnersnumber=874

location of collaborative worknumber=130

number of partnersnumber=130

duration of collaborationsnumber=130

weak correlation with size

mostly national, significant regional drive

predominantly long-term

essentially done in public-lab (87%)




Probing into the invisible part of the iceberg


14 pre-identified modalities of collaboration

Answers on a 4-point scale Distribution of responses for each modalitynumber=130

Interpretation

– prevalence of informal / knowledge-targeted / two-way modalities

– IP-related K&T transfer through license agreements at a distant 2nd place


Extra resources are effectively leveraged


9 pre-identified benefits of collaboration for the public lab

Answers on a 4-point scale

Rate of “Yes” for each benefitnumber=130

Interpretation

– perceived benefits closely connected to tangible / intangible inputs obtained

– development of technology transfer activities again at a distant 2nd place (and mobility towards industry)

“Significant” + “Decisive” “Yes”


Traditional outcomes outstrip IP-related ones


14 pre-identified outcomes of collaboration


Rate of “Yes” for each outcomenumber=130

Interpretation

– … related to dominance of research-type modalities

– patents & copyrights, licenses of all types 2 to 3 times less frequent than publications or theses…

“Frequent” + “Very frequent” “Yes”

– however, embodied technologies (new products & processes + software) as frequent as publications


Labs’ activities significantly impacted by collaborations


Significant impact on research programmes and themes (rate of “Significant” + “Decisive” = 58%)

number=130 Impact on research style answers on a 3-point scale

number=130

Impact on research practices 7 pre-identified practices answers on a 4-point scale “Significant” + “Decisive” “Yes”number=130

Interpretation

– stands out against secondary importance of IP- and technology-related modalities / benefits / outcomes?

– firms’ preferences shape collaborative labs’ activities

– exposure to skewing problem (Florida & Cohen, 1999)


4 pre-identified ways of allocating IP


Rate of “Yes” for each allocationnumber=130

Interpretation

– 40% of the labs interact under several ownership rules flexibility, but in response to what?

– joint ownership as frequent as separate ownership…


– possible correlation with the modalities of collaboration (ex. technical assistance tends to be associated with exclusive ownership of the firm)


Balanced allocation of IP stemming from collaboration


10 pre-identified legal mechanisms for results’ appropriation by firms


Rate of “Yes” for each mechanismnumber=130

Interpretation

– possible correlation with S&T field (ex. much confidentiality but no patents in brain-related research and nuclear research)

– confidentiality and patents dominate: ex ante / ex post complements?



Firms gain various legal rights over collaborative results


Contractual right to suppress specific information before publication 52% of labs

Actual suppression of information in publications 26% of labs

Interpretation

– 2,0 x more actual suppressions in chemistry than in life sciences (significan--ce to be tested…)

– stronger contractual information control than in prior survey (52% vs. 35% for Cohen et al., 1994)

Secrecy over all of the results 25% of labs


Tight information control ex ante and ex post

– right to suppress information often associated with contractual provisions for publication delay (32% of labs 31% for Cohen et al.)

– occasional suppressions while not specified in the contract


Contractual provision for publication delay 55% of labs

Delay > 6 months in about half cases

Interpretation

– delays 1,6 x more harmful in life sciences than in chemistry (significance to be tested…)

– consistent with prior survey results (55% 53% for Cohen et al.)

Delay not harmful or only marginally so for 78% of labs


Publication delays: widespread but not too worrying


4 pre-identified levels of barriers to scientific communication

Interpretation

– limitations harmful to the cumulative process of S&T knowledge building (barriers with public research organisations)

– Firms build tight fences around knowledge because it spills over so easily – from possible competitors up to the larger public


Pervasive limitations concerning scientific communication


Rate of “Yes” for each levelnumber=130


– natural locus of S&T production torn apart in the case of limitations towards colleagues in the same lab (8% of labs)


Conflict or discord with a partner about IP issues in 2003 15% of labs

Interpretation

– probabilistic effect (more partnerships more conflicts) seems to prevail over capacity effect (more effective management of collaborations by big labs)

– many disputes between supposedly “collaborating” partners… but rapidly settled for the most part


IP as a source of (short-lived) conflict between partners

Mostly big labs (median = 60 employees vs. 28 for the sample) with many partners (median = 6 vs. 4)

Disputes had been resolved in 2004 (i.e. by the time of the survey) for 74% of labs

– possibly because of strong incompleteness of R&D contracts


Interpretation

– patents and secrecy (firms’ preferred mechanisms) at a distant second place… although not marginal

– multiple protection is a common strategy (71% of labs)


Public labs protect their intellectual assets through distinctive strategies

6 pre-identified mechanisms of intellectual assets protection by labs


Rate of “Yes” for each mechanismnumber=130


– prevalence of contractual protection mechanisms


THANK YOU!

… but they must be carefully managed to avoid negative consequences on knowledge circulation and diffusion

Perform in-depth comparison with Cohen et al., 1994

Identification of cluster effects

Regression analysis

Public labs are already implementing distinctive strategies to protect their intellectual assets (as compared to firms)

Conclusions and perspectives

Technology management in this context is only of limited use: most technologies are embryonic, calling for two-way interactions and tacit knowledge transfer

Collaborations with firms allow public labs to leverage additional resources and thereby to increase their scientific output




Agrawal A., (2001), “University-to-industry knowledge transfer: literature review and unanswered questions”, International Journal of Management Reviews, 3(4), 285-302.

Cohen W.M., Florida R., Goe R., (1994), “University-Industry Research Centers in the United States”, Report to the Ford Foundation, Mimeo, Carnegie Mellon University.

Cohen W.M., Florida R., Randazzese L., Walsh J., (1998), “Industry and the Academy: Uneasy Partners in the Cause of Technological Advance”, in Roger Noll (ed.), Challenge to the Research University, Washington, DC: Brookings Institution.

Cohen W.M., Nelson R.R., Walsh J., (2002), “Links and Impacts: The Influence of Public Research on Industrial R&D”, Management Science, 48, 1-23.

Henderson R., Jaffe A.B., Trajtenberg M., (1998), “Universities as a Source of Commercial Technology: A Detailed Analysis of University Patenting, 1965–1988”, Review of Economics and Statistics, 80, 119-27.

Jaffe, A. (1989), “Real Effects of Academic Research”, American Economic Review, 79, 957-70.

Mowery D.C., Sampat B.N., (2005), “The Bayh-Dole Act of 1980 and University–Industry Technology Transfer: A Model for Other OECD Governments?”, Journal of Technology Transfer, 30, 115-27.

Thursby J.G., Jensen R., Thursby M.C., (2001), “Objectives, Characteristics and Outcomes of University Licensing: A Survey of Major U.S. Universities”, Journal of Technology Transfer, 26, 59-72.

Thursby J.G., Thursby M.C., (2003), “Industry/University Licensing: Characteristics, Concerns and Issues from the Perspective of the Buyer”, Journal of Technology Transfer, 28, 207-13.

References



© goddard & isabelle 20061 druid summer conference june 18 th, 2006 john gabriel goddard imri...

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