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

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

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)

• Pasteur’s Quadrant: in some areas considerations of use and fundamental understanding can be pursued at the same time (Stokes, 1997)

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?

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 23 • 1970 – 2001• 20,856 scientific papers published • 941 journals: Impact Factor (JCR) and Level

(Chi/research report)• 305 patents assigned to academic inventors

Politecnico di Torino

# Inventors and # Patents per type of assignee

(1) (2)

Assignee type # Inventors with at least one patent in the category

# Patents (1)

# Inventors with patents only in the category

# Patents (2)

Inventor 9 9 6 6

research institution 24 36 13 19

Firm 106 252 95 219

research institution & f irm 4 5 4 5

inventor & f irm 1 1 1 1

Grand Total 131 303 119 250

• 83–87% patents (accounting for 80-81% inventors) was assigned to a firm (academic privilege)• “serial inventors”


• 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

10

)(

L

articlesL

llti

L

lti

Pit

pitp

articles

level

0)1(

1

L

lti

Pit

pitp

articles

factorimpact

0)1(

1

_


0

1

2

3

4

5

6

7

8

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35

years of career

Pro

du

cti

vit

y

mean st.dev median

10

)(

L

articlesL

lltiPRODUCTIVITY: 3-years moving average of the

number of articles published by each individual


0

0.5

1

1.5

2

2.5

3

3.5

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35

years of career

Basic

ness

mean st.dev median

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

L

lti

Pit

pitp

articles

level

0)1(

1


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

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35

years of career

Imp

act

mean st.dev median

L

lti

Pit

pitp

articles

factorimpact

0)1(

1

_


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).

)exp(

)exp(

))(exp()(

))(exp()(

)(

)(

0

0

j

i

j

i

j

i

x

x

txt

txt

t

t

))(exp()()( 0 txtt ii


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

Dep. Variable Coeff. St. Error Coeff. St. Error Coeff. St. Error Coeff. St. Error Coeff. St. Error Coeff. St. Error

gender 0.460 (0.213) ** 0.417 (0.235) * 0.467 (0.214) ** 0.436 (0.236) * 0.452 (0.213) ** 0.409 (0.235) *

exptto 0.010 (0.004) *** 0.014 (0.004) *** 0.011 (0.004) *** 0.014 (0.004) *** 0.010 (0.004) *** 0.014 (0.004) ***

instdim -4.0 e-04 (2.2 e-04) * -4.7 e-04 (2.4 e-04) ** -4.1 e-04 (2.2 e-04) * -4.9 e-04 (2.3 e-04) ** -4.1 e-04 (2.2 e-04) * -4.9 e-04 (2.4 e-04) **

productivity 0.219 (0.090) ** 0.264 (0.099) ***

productivity^2 -0.019 (0.009) ** -0.022 (0.010) **

basicness 0.758 (0.247) *** 1.070 (0.271) ***

basicness^2 -0.170 (0.063) *** -0.248 (0.069) ***

impact 0.365 (0.176) ** 0.400 (0.186) **

impact^2 -0.065 (0.043) -0.060 (0.043)

Obs.

Log likelihood

Prob > chi2

*p≤0.1,**p≤0.05,***p≤0.001

(5)(4) (6)

All patents (131 failures)

Firm-Assigned Patents (106 failures)





(1)

0.000***

19459

-867.624

(2) (3)

19806

-694.204

19806

-698.235

0.001***

19459

-869.551

0.004*** 0.001***

19459 19806

-870.290 -699.332

0.007*** 0.001***


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

Indep var: i (t) Obs. 19459 (131 failures)

productivity 0.219 (0.090) **

productivity^2 - 0.019 (0.009) **

basicness 0.758 (0.247) ***

basicness^2 - 0.170 (0.063) ***

impact 0.365 (0.176) **

impact^2 - 0.065 (0.043)


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


Results: Effect of Productivity & Basicness and Productivity & Impact

Indep var: i (t) Obs. 19459 (131 failures)

productivity (+45%) 0.374 (0.141) ***

basicness (+18%) 0.163 (0.069) **

prod x basic (-11%) - 0.118 (0.045) ***

productivity (+18%) 0.166 (0.066) **

impact (+20%) 0.179 (0.074) **

prod x impact (-8%) - 0.082 (0.034) **


Productivity_Basicness and Productivity_Impact Effects



0

1

2

3

4

5

6

7

8

9

10

0 0.4 0.8 1.2 1.6 2 2.4 2.8 3.2 3.6 4 4.4 4.8 5.2 5.6 6

productivity

haz

ard

rat

e

mean basicness - 1sd (0.08)mean basicness (1.78)mean basicness + 1sd (3.49)

Curvilinear effects

0

0.5

1

1.5

2

2.5

3

0 0.4 0.8 1.2 1.6 2 2.4 2.8 3.2 3.6 4 4.4 4.8 5.2 5.6 6productivity

haz

ard

rat

e

mean impact - 1sd (0)mean impact (1.03)mean impact + 1sd (2.34)

BASICNESS IMPACTThreshold 3.49 – 77th centile Threshold 2.34 68th

centile

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.


Restricted event to patent with a firm: all curvilinear effects hold

Indep var: i (t) (106 failures)

productivity 0.264 (0.099) ***

productivity^2 - 0.022 (0.010) **

basicness 1.070 (0.271) ***

basicness^2 - 0.248 (0.069) ***

impact 0.400 (0.186) **

impact^2 - 0.060 (0.043)


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%) - 0.131 (0.048) ***

productivity (+20%) 0.184 (0.071) **

Impact (+23%) 0.209 (0.076) ***

prod x impact (-8%) - 0.086 (0.034) **


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.


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.

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

sc_field Cumpat_2001 Std. Dev. Freq.CHEMISTRY 0.224 0.941 917ENGINEERING 0.298 1.126 309PHYSICS 0.143 0.550 35OTHER 0.000 0.000 13Total 0.237 0.977 1274

Dataset: Chemists vs. Engineers

n.average

agepat cumpat publ_m publbas4 ifac

CHEMISTRY 917 35.687 0.014 0.224 1.457 0.537 2.367ENGINEERING 309 35.482 0.019 0.298 0.771 0.582 1.166PHYSICS 35 35.032 0.008 0.143 1.014 0.490 2.676OTHER 13 35.394 0.000 0.000 0.327 0.908 1.884Total 1274 35.614 0.015 0.237 1.267 0.712 2.258Chi-sq with ties 2.627 7.934** 2.191 653.91*** 8616.1*** 3427.7***

Test: Equality of populations (Kruskal-Wallis test)

The majority of our materials scientists was a chemist or an engineer of materials. We run separate analysis for subgroups.

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 yearControls: 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 Negbin3. C can be measured only when publications are not zero (left

truncation) > Heckman selection equation4. Patterns of publications are Subfield-specific. Consequently, each

indicator in was normalized by subfield in the multivariate analysis.

Analysis .A: Publications

QUANTITY:1. count of publications > Zero Infl NegBin2. log[publications+1] > OLS Fixed Effects3. 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 0.018 0.086** 0.037*

ENGINEERS 0.669** 0.278* 0.542

CHEMISTS -0.216** -0.027** -0.329***

Coefficients estimated for postpat (dummy=1 if author patented in the previous yearComparison of 3 alternative model estimates

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 -0.090 -0.021 -0.019

ENGINEERS -0.360 -0.004 -0.015

CHEMISTS -0.451** -0.072** -0.372***

Coefficients estimated for postpat (dummy=1 if author patented in the previous yearComparison of 3 alternative model estimates

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**

CHEMISTS 0.080

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)

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

patenting2. Chemists experience a decrease of publications after patenting3. 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

Documents

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

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