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If Star Scientists do not patent: The Effect of Productivity, Basicness and Impact on The Decision to Patent in the Academic World *Mario Calderini, *Chiara Franzoni e **Andrea Vezzulli *DISPEA, Politecnico di Torino, Turin **CESPRI, Università Commerciale L. Bocconi, Milan

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Academic Patenting. Rivalry vs. Complementarity Hp RIVALRY the pursuit of market goals may favor a re-arrangement of academic research agendas in favor of short-term exploitable trajectories of research the rules of market competition may not be compatible with the social norms of priority and free circulation of knowledge (Dasgupta and David, 1985; Heller and Eisenberg, 1998) COMPLEMENTARITY feedback from industrial work may be so rich to enable advances in knowledge or raise new quests for fundamental inquires (Rosemberg, 1982; Mansfield, 1995) Pasteurs Quadrant: in some areas considerations of use and fundamental understanding can be pursued at the same time (Stokes, 1997)

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Empirical Evidence CROSS-SECTION: most productive scientists in terms of publications are also more productive in terms of patents (Agrawal and Henderson, 2002; Stephan et al., 2007; Van Looy et al., 2004; Carayol, 2007) LONGITUDINAL: academic inventors are likely to experience a (temporary) increase in number of articles published in coincidence with the patent event (Azoulay et al., 2006; Breschi et al., 2007). patents are preceded by a flurry of publications (Azoulay et al., 2007), although propensity might be decrease for stars (Calderini et al., 2007). FIELDS: Life Sciences, Computer Sciences, Engineering, Physics, Chemistry OPEN ISSUES: Quality? How about ENGINEERING vs. SCIENCE?

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Sample and Data SAMPLE Names of 1323 Italian publicly-funded scientists in 2001 Material Sciences DATA Longitudinal data on all publications (ISI) and patents (EPO/USPTO) made by each scientist from the age of – ,856 scientific papers published 941 journals: Impact Factor (JCR) and Level (Chi/research report) 305 patents assigned to academic inventors Politecnico di Torino

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# Inventors and # Patents per type of assignee 83–87% patents (accounting for 80-81% inventors) was assigned to a firm (academic privilege) serial inventors Politecnico di Torino

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PRODUCTIVITY: 3-years moving average of the number of articles published by each individual BASICNESS: 3-years moving average of the rank (Level) of the journals where the individual published IMPACT: 3-years moving average of the Impact Factor of the journals where the individual published Variables: Productivity, Basicness, Impact Politecnico di Torino

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PRODUCTIVITY: 3-years moving average of the number of articles published by each individual Politecnico di Torino

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BASICNESS: 3-years moving average of the rank (Level) of the journals where the individual published Politecnico di Torino

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IMPACT: 3-years moving average of the Impact Factor of the journals where the individual published Politecnico di Torino

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Model estimate Proportional Hazard assumption (hp: all individuals have identical shape of hazard). Estimate by Partial Likelihood method (Cox, 1972), which avoids imposing a specific distribution for T (baseline cancels out). Politecnico di Torino

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Results: all publication indicators have a curvilinear effect on the probability of experiencing an event Politecnico di Torino

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Results: all publication indicators have a curvilinear effect on the probability of experiencing an event Indep var: i (t) Obs (131 failures) productivity 0.219(0.090)** productivity^ (0.009)** basicness 0.758(0.247)*** basicness^ (0.063)*** impact 0.365(0.176)** impact^ (0.043) Politecnico di Torino

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Results: publication&basicness and publiation&impact have a threshold effect on the probability of experiencing an event Politecnico di Torino

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Results: Effect of Productivity & Basicness and Productivity & Impact Indep var: i (t) Obs (131 failures) productivity (+45%) 0.374(0.141)*** basicness (+18%) 0.163(0.069)** prod x basic (-11%) (0.045)*** productivity (+18%) 0.166(0.066)** impact (+20%) 0.179(0.074)** prod x impact (-8%) (0.034)** Politecnico di Torino

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Productivity_Basicness and Productivity_Impact Effects Politecnico di Torino

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Curvilinear effects BASICNESS IMPACT Threshold 3.49 – 77th centile Threshold th centile

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Other results.Male gender: +140% hazard, but not significant for restricted event of patenting with a firm..No time/cohort effect: probability to patent has not changed over time..Experience of TTOs increases the hazard to patent..Probability to patent is higher in low-industry environments..Probability to patent with firms decreases with the size of institutions..Estimates on the restricted event to patent with a firm confirm all curvilinear effects. Politecnico di Torino

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Restricted event to patent with a firm: all curvilinear effects hold Indep var: i (t) (106 failures) productivity 0.264(0.099)*** productivity^ (0.010)** basicness 1.070(0.271) *** basicness^ (0.069) *** impact 0.400(0.186)** impact^ (0.043) Politecnico di Torino

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Restricted event to patent with a firm. All results hold. Effects increse in magnitudo. Indep var: i (t) (106 failures) Productivity (+53%) 0.427(0.146)*** basicness (+20%) 0.181(0.077)** prod X basicness (-12%) (0.048)*** productivity (+20%) 0.184(0.071)** Impact (+23%) 0.209(0.076)*** prod x impact (-8%) (0.034)** Politecnico di Torino

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Conclusions.Performances of scientists are a strong predictor of the likelihood to patent..All bibliometric indicators had a curvilinear effect: are there different career trajectories? i)low to medium levels of the indicators: any increase in performances increases the probability to patent: (e.g. higher productivity=more results to exploit; higher impact=higher reputation&visibility; higher level=more pervasive results) ii)high levels of the indicators: any increase in performances decreases the probability to patent: (e.g. higher productivity, higher impact, higher basicness= more funds for untargeted research) Strength of those effects may depend on: national system of research funding, technological regimes, type of firms in the region. Politecnico di Torino

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Discipline counts? Research Hypothesis not all disciplines earn equal benefits from serving practical ends. Whereas science is aimed at the understanding of phenomena, engineering is applied in scope, i.e. aims to solve problems of industrial (practical) relevance, although by means of a rigorous scientific method (see Walter G. Vincenti, 1990). NB: Here applied is used in its epistemological, rather than hierarchical meaning. Investigation is scoped to problems, but the process of knowledge creation may not necessarily be deductive (from basic disciplines), as the conventional wisdom suggests. HP: working on practical problems such as those posed by inventing a new functional tool can be in principle more fertile of ideas for engineering than for science.

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Dataset: Patents 83–87% patents (80% inventors) was assigned to a firm serial inventors Kruskal-Wallis Test confirms equality of populations for total patents invented in the overall observation period

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Dataset: Chemists vs. Engineers The majority of our materials scientists was a chemist or an engineer of materials. We run separate analysis for subgroups.

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Modeling dependent Variables: A. QUANTITY number of publications (3 models)B. BASICNESS number of basic publications (IpIQ basicness index=4) C. IMPACT impact factor Independent Variables: postpat dummy=1 if invented in previous year Controls: gender, region of affiliation, seniority, experience of TTO, field, coauthorship) PROBLEMS IN DATA TREATMENT 1.Endogeneity > Inverse prob. of treatment weights (Azoulay et al., 2006; Breschi et al., 2006) 2.A and B are positive integers with excess zeros > Zero inflated Negbin 3.C can be measured only when publications are not zero (left truncation) > Heckman selection equation 4.Patterns of publications are Subfield-specific. Consequently, each indicator in was normalized by subfield in the multivariate analysis.

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Analysis.A: Publications QUANTITY:1. count of publications > Zero Infl NegBin 2. log[publications+1] > OLS Fixed Effects 3. as in 2, but publications are weighted by coauthors ZINB (Dep var: postpat) OLS_FE (Dep var: Lpubl) OLS_FE weighted for co-authors (Dep var: lpubl) ALL ** 0.037* ENGINEERS 0.669**0.278*0.542 CHEMISTS **-0.027** *** Coefficients estimated for postpat (dummy=1 if author patented in the previous year Comparison of 3 alternative model estimates

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Analysis B: Number of basic publications (Level 4 IpIQ journals) BASICNESS:1. after patent dummy (postpat) > Zero Infl NegBin 2. log[publbas+1] (lpublbas4) > OLS Fixed Effects 3. as in 2, but basic publs are weighted by coauth. ZINB (Dep var: publbas4) OLS_FE (Dep var: Lpublbas4) OLS_FE weighted for co-authors (Dep var: lpublbas4) ALL ENGINEERS CHEMISTS ** ** *** Coefficients estimated for postpat (dummy=1 if author patented in the previous year Comparison of 3 alternative model estimates

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Analysis C: Impact (Journal Impact Factor) IMPACT: standardized Impact Factor (stdifac) : [(IF-mean(IF)/std.dev(IF)] > Heckman (postpat) HECKMAN_ML (Dep var: postpat) ALL 0.159*** ENGINEERS 0.281** CHEMISTS0.080 Coefficient estimate for postpat (dummy=1 if author patented in the previous year) Inverse Probability of Treatment Weighted Heckman selection equation. Standardized Impact Factor, conditional to having made at least one publications(accounts for left truncation at zero)

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Conclusions Our estimate of the post-patent productivity, impact and basicness of publications of a sample of Italian Material Scientists showed that: In the overall sample, productivity is not affected (or slightly positively affected) by patenting When separated into subfields, 1.Engineers experience an increase of publications after patenting 2.Chemists experience a decrease of publications after patenting 3.Engineers experience an increase of Impact Factor and hold basic publications unchanged. 4.Chemists experience a decrease of basic journal publications, and hold Impact Factor unchanged. 5.The increase of IF occurs at negative marginal return (neutralized after the 4th patent), but this effect is unlikely to occur in practice

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