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This study explores the motivations and barriers that influence university scientists' decisions regarding invention disclosures for patenting. With the legislative shifts such as the Bayh-Dole Act, universities have gained ownership rights to patents, creating an entrepreneurial environment. However, many scientists still struggle with the motivation to disclose their inventions due to conflicting interests and a lack of institutional support. By examining the interplay between personal motives, institutional incentives, and the broader context of technology transfer, this research aims to shed light on the "taste for patents" among university researchers.
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A Taste for Patents … at University?The Roleof University Scientists‘ Attitude Towards Invention Disclosure“Scientists and Inventors” WorkshopLeuven, 11.05.2012ChristophIhl, Thomas Walter, Jan ReerinkTechnology & Innovation Management GroupRWTH Aachen
Overview I. Motivation & Research Questions II. Theory & Prior Research III. Empirical Study IV. Results V. Discussion & Conclusion
Motivation: University-invented vs. university-owned patents • Legislation has empowered universities to own patents; e.g. • US: Bayh-Dole-Act, 1980 • Germany: abolition of professors’ privilege (ArbNErfG, 2002) • (Some) universities want to be entrepreneurial • Still, substantial knowledge leaks through universities’ backdoor :academic patents owned by firms or scientists, other transfer channels • Scientists’ lack of motivation or conflicts in motivation to disclose their inventions to universities? • Universities’ lack of incentive provision or supportive environment? • Take a look inside the black box of scientists’ decision making: i.e. attitudes, motives & preferences for incentives…
Research Questions: „Taste for Patents with University?“ … … scientists’ attitude towards filing an invention disclosure with their university to examine patentability: • How does it exist?Consisting of motives in line with vs. barriers in contradiction with a “taste for science”? • How does it arise? Formed by individual background and/or institutional context? • How does it matter?Workingindependently from vs. crowded in/out by external incentives?
Overview I. Motivation & Research Questions II. Theory & Prior Research III. Empirical Study IV. Results V. Discussion & Conclusion
Research framework Incentives InstitutionalContext Taste Invention Disclosure Individual Background
Theory & Prior Research: Scientists‘ motivestobescientists • “Taste for Science” (Merton, 1973) • Autonomy : academic freedom to solve interesting puzzles & publish • Reputation: peer recognition from first discoveries & citations • Money: financial rewards less important at the margin • “Scientists pay to be scientists” (Stern, 2004) • Scientific norms (“communism”, “desinterestedness”) even disregard personal value appropriation (Merton, 1942) • “Puzzle, ribbonandgold” (Stephan & Levin, 1992) • Scientists’ taste for science have been subject to a number of recent studies (e.g. Agarwal & Ohyama, 2010; Lacetera& Zirulia, 2008; Roach & Sauermann, 2010; Sauermann& Stephan, 2010)
Theory & Prior Research: Motives tocommercialize • Many studies have looked into scientists’ attitudes & motives to engage in technology transfer in general (e.g. D’Este & Perkmann, 2011) • Also barriers, negative consequences (e.g. Baldini, 2007; Krabel & Mueller, 2009) • Role adaption => attitude change (Jain, George, Maltarich2009) • Recently, attitudes / motives in relation / contrast to a “taste for science” =>”taste for commercialization (Lam, 2011; Sauermann & Roach, 2012) • ‘Loose collection’ of motives, barriers & incentives w.r.t. invention disclosure (Baldini et al.,2007) • Goal: examine effects of scientists’ attitude specifically on the decision to disclose inventions at university & relative to incentives
Theory & Prior Research: Incentives tocommercialize • Motivation crowdingtheory: distinctionbetweenmotives & incentives(e.g. Frey & Jegen, 2001; Sauermann& Cohen, 2008) • Incentives are situational and contingent on behavior • Motives are stable, trait-like and describe what on cares about • Incentives can change motivation & attitudes (crowding in / out)by changing self-determination / -esteem • Previousresearchhasinvestigatedspecificincentives in isolation, e.g. • Royaltyshares(cf. Jensen et al., 2007; Lach & Schankerman, 2008; Markman et al., 2004) • TTO, Grace period(Franzioni, 2010) • Interaction betweenfinancialmotiveandincentive on commercialization in general(Sauerman et al., 2010) • Goal: examine interaction effect between attitude towards invention disclosure & a full range of incentives to determine the way of crowding
Theory & Prior Research: Scientists‘ backgroundandexperience • Publications: => opportunity for patents vs. research basicness(Azoulayet al., 2007; Calderini et al., 2007) • Prior patents => they know how to do it vs. they can do it alone or have enough(Bercovitz, Feldman, 2008) • Industrial involvement: => inspiration vs. applied research / independence from university(Agrawal & Henderson; 2002) • Other: Gender, Nationality, Tenure, Tenured(Waverly, Ding et al., 2006; Bercovitz, Feldman, 2008) • Goal: explain attitude towards invention disclosure such that these trade-offs are revealed
Theory & Prior Research: InstitutionalContext • Faculty quality has been shown to have an impact on the technology transfer performance (van Looy et al, 2011; Perkmann et al, 2011) • Peer effects versus contextual effects (Azouly et al, 2009; Manski, 1993) • Social learning versus Symbolic compliance (Feldman & Bercovitz, 2008) • Goal: investigate whether attitude towards invention disclosure actually mediates contextual effects -> evidence for social learning
Overview I. Motivation & Research Questions II. Theory & Prior Research III. Empirical Study IV. Results V. Conclusion
Empiricalstudy:Sample description • Online survey between December 2010 and March 2011 • 9 major technical universities in Germany (TU9 association) • Identification of 17,178 faculty members from engineering, naturals sciences, life sciences => e-mail invitation • 1,686 (9.4%) usable responses • Excluding technical support staff => 1,408 participants, • 147 (10.4%) full professors, 244 (17.3%) post docs / junior professors, and 1,017 (72.2%) research associates / PhD students • 77.5% male • no significant difference between sample and invited population in terms of observable indicators gender, rank, discipline, university
Empiricalstudy:Sample description • To better account for different patentability across academic disciplines, we manually assigned each institute / chair to belong to one of the following categories (Jaffe, 1989; Zucker & Darby, 2006)
Empiricalstudy: Motives & Incentives todiscloseinvention • Extensive qualitative researchtoexploremotives & incentivespriortosurvey: • 20 interviews and 8 in-depth case studies with patent-experienced university officials and researchers at universities in the US, the UK and Germany between January and August 2008 • Measuring attitudes as expectancy*value (e.g. Ajzen, 1988) • Motives are framed as beliefs about expected consequences rather than evaluations / importances(Sauermann & Roach, 2012) because of higher predictive value (e.g. Ajzen, 1988, Bagozzi, 1984; Valiquette, Valios, Desharnais, & Godin, 1988; Pieters, 1988)
Empiricalstudy: Measurement & descriptive results for motives • Max. correlation=0.5; max VIF=1.8; max KI=16 • Cronbachα=0.86; AVE=0.43; min. loading=0.59
Empiricalstudy: Manipulation of Incentives • Manipulation ofincentives in a scenario-based conjoint experiment • Frommarketingtomanagement: • decision criteria of venture capitalists (Frankeet al., 2008) • IP managers preference for protection strategies (Fischer & Henkel; 2010) • employees’ preferences for incentives to innovate (Leptien, 1995) • employees’ preferences for incentives to engage in entrepreneurship (Monsen et al., 2010) • Suffers from hypothetical bias, but also has 4 advantages: • (1) further disaggregation of incentive effects on within researcher level • (2) full range or ‘bundles’ of incentives that are not yet implemented in reality • (3) overcome potential selection bias: scientists may systematically self-select to work at ‘entrepreneurial universities’ • (4) respondents have to engage in trade-offs, which reduces the threat of inflated importances obtained from Likertscales
Empiricalstudy: Manipulation ofIncentives • 4 attributes with 3 levels, 4 attributes with 2 levels • => 34* 24 = 1,296 possible combinations in a full factorial design • blocking factor with 3 levels added to split the design among groups • using Ngene software, we extracted a fraction of 36 conjoint scenarios, such that all main effects and selected two-way interactions could be estimated • respondents were randomly assigned to a block of 12 scenarios which were in turn randomized
Empiricalstudy: Exemplaryconjointscenario Ratings-based instead of choice-based CA (Elrod et al., 1992) “This combination of incentives motivates me to have my work results checked for patentability and commercial usability by means of invention disclosure filings” [0=Strongly disagree; 6=Strongly agree]
Empiricalstudy: Data on individual backgroundfromsurvey & secondarysources • Survey: • Gender • Nationality • Tenure • Tenured • Industrial involvement Scale • ISI WoS: papersandcitations per individual from2005-2010 • Patstat: patent applications per individual from 2005-2010: • 126 (8.95%) academicinventorswith454 patents, 43 university-owned; 11 co-ownedby firm
Empiricalstudy: Data on institutionalcontextfromsecondarysources • TU9 associationbased on thefederalstatisticaloffice: • Numberofstudents, professors, scientifcstafffor 2008 • Center for University Development (CHE) – Research Ranking 2009: • NumberofPhDtheses, thirdpartyfunds total, fromDFG & industry • Patstat: numberofuniversity-owned patent applicationsfrom 2005-2010 • ISI WoS: numberofpublicationswithuniversityaffiliationsfrom 2005-2010 • bothassignedtoacademicdisciplinesaccordingtoconcordancetables(Jaffe, 1989; Zucker & Darby, 2006)
Empiricalstudy: Econometricapproach • Accountingfornested, multileveldatastructure: • (1) Hierarchical linear model, random-effectsregression: • (2) Orderedlogitmodelwithrandomeffects: • Estimatedvia simulatedmaximumlikelihoodusing 100 Haltondraws • Interpretation ofestimatedcefficients via marginal effectsrecognizinginteractionterms(cf. Ai & Norton, 2003; Greene, 2010)
Overview I. Motivation & Research Questions II. Theory & Prior Research III. Empirical Study IV. Results V. Conclusion
Results: Partial effectof taste under high incentiveconditions
Overview I. Motivation & Research Questions II. Theory & Prior Research III. Empirical Study IV. Results V. Conclusion
Conclusion • Implications • „Taste“ canbeformedbothbyhiringtherightpeopleandculture / sociallearning => double benefit • Crowding-in on average, but crowding out for 25% ofpeoplewithvery high „taste“ => thesepeopleneedspecialnurture & appreciation • Limitations& next, futuresteps • furtherdisentanglecrowdingeffectsbyincentivesand (non-tenured) people • Look atmediation • Look atmoderationofindivdialbackgroundeffectsbycontext • further check & improvequalityof individual patent & pubdatafor all invitedscientists • collectdata on real patentingbehavior (in X years)
ThankYou! Christoph Ihl TIM Group RWTH Aachen University +49 241 809 3577 ihl@tim.rwth-aachen.de tim.rwth-aachen.de/ihl