In this presentation we show the results of a case study in which we tried to analyze the extent to which business funds received by universities correlate to the university-industry co-publications. The case study focuses on the technical university of Valencia.

1. INSTITUTE OF INNOVATION AND KNOWLEDGE MANAGEMENT
Do university-industry co-publication volumes correspond with university funding from business firms?
Joaquín M. Azagra-Caro | Leiden, 4 September 2014
Co-authors: Alfredo Yegros-Yegros, MayteLópez-Ferrer, Robert J.W. Tijssen

2. Introduction
•University-industry interactions are a slightly controversial source of potential benefits, among other, to partially contribute to economic development
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•Different indicators to monitor and foster university- industry interactions (contract research, R&D projects, patent licenses, creation of start-up companies…)
Major drawback Not freely available

3. University-industry co-publications (UICs)
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•One of the very few sources for gathering aggregate- level proxy measures of university-industry interaction patterns and trends (Tijssen et al., 2009; Tijssen, 2011)
•Some studies rely entirely on UICs to capture university-industry interactions
–Analyses of UICs (Calvert and Patel, 2003; Ponds et al 2007)
–Effect of UICs on university commercialization technology (Wong and Singh, 2013)

4. Validity of UICs as proxy of university- industry interactions
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•UICs are a particular type of co-authorship, only partial indicators of research collaboration (Katz and Martin, 1997)
–One third of the companies providing funding to the university had not UICs with the university –only 16% of the companies publishing UICs also provided funding (Lundberg et al. 2006)
•Previous attempts of validation are scarce
–Collaborations might not produce UICs
–Some UICs might not necessarily entail collaboration
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5. Research question
•Our objective is to contribute to prove whether or not UICs are good proxies of university-industry interactions
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DoUICvolumescorrespondwithuniversityfundingfrombusinessfirms?
•Researchquestion
Business funding is associated with some of the most frequently occurring university-industry interactions (e.g. contract research or joint research agreements) (Roessner, 1993)
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•Needofaconceptualframework

6. Four types of theoretical relationships between funding and UIC –an interactive model
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University funding from business firmst-τ
UICt
University funding from business firmst+φ
University funding from business firmst
Industry financing
University signalling
Industry pull
Science push
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7. Data
•Polytechnic University of Valencia (UPV)
•247 UPV authors of UICs in 2008-2011 (Source: WoS)
•UPV researchers of projects with firms in three periods (Source: UPV technology transfer office)
–1,224 in 2000-2007
–1,004 in 2008-2011
–482 in 2012-2013
•Name matching of both databases
•Project data includes amount of funding
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8. Types of funding and UIC relationships at UPV
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Industry financing
University signalling
Industry pull
Science push
94%
6%
UPV participants in projects with firms 2000-2007
Non-UICauthors
UIC authors
93%
7%
UPV participants in projects with firms 2008-2011
Non-UICauthors
UIC authors
83%
17%
UPV UIC authors
Non-participantsin projects withfirms 2012-2013
Participants inprojects withfirms 2012-2013
72%
28%
UPV UIC authors
Non-participantsin projects withfirms 2008-2011
Participants inprojects withfirms 2008-2011
University funding from business firms2000-2007
UIC2008-2011
University funding from business firms2012-2013
University funding from business firms2008-2011
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9. Pairwise correlation coefficients (R)
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•Non-significant statistical relationships
Mean business project funding
(2000-2007)
Mean business project funding
(2008-2011)
# UICs 2008-2011
R = 0.01
R = -0.01
# UICs 2008-2011
(funding 2008-2011)
# UICs 2008-2011
(funding 2012-2013)
Mean business project funding
R = -0.01
0.15
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10. Regression analysis –control variables
•Individual characteristics (#projects, %PI, age, gender, visibility)
•Project characteristics (R&D type, year, duration, #firms, %foreign)
•UIC characteristics (#authors, %international, %third affiliations, #citations, year, journal, area)
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11. Let’s start with the left half of the picture
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Industry financing
Industry pull
University funding from business firms2000-2007
UIC2008-2011
University funding from business firms2008-2011
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12. Econometric models of financing and industry pull
•UIC = f(university funding from business firms)
•But UIC=0 may mean two things:
–Authors wanted to produce UIC and could not, e.g. for confidentiality or lack of scientific novelty
–Authors did not want to produce UICs, e.g. they used funding for other purposes or lack of environmental culture
•Correct verification of impact of business funding in two steps:
–Step 1 UIC(yes/no) = f (university funding from business)
–Step 2 For UIC>0, #UIC = f (university funding from business)
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13. Heckman selection models of financing and industry pull at the UPV
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•No sample selection bias
•No sign of financing or industry pull effects at the UPV
Step
Dependent variable
Coefficient of mean business project funding
(2000-2007)
Coefficient of mean business project funding
(2008-2011)
1
UIC (yes/no) 2008-2011
-0.94
-0.18
(1.58)
(0.48)
2
# UIC 2008-2011
2.14
-2.01
(4.24)
(1.25)
# observations
1,224
1,004
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14. Let’s move to the right half of the picture
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University signalling
Science push
UIC2008-2011
University funding from business firms2012-2013
University funding from business firms2008-2011
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15. Econometric models of signalling and science push
•University funding from business firms = f(UIC)
•But business funding=0 may mean two things:
–Researchers wanted business funding but did not get it, e.g. need of minimum scientific visibility
–Researchers did not want business funding, e.g. to preserve academic freedom
•Correct verification of impact of UICs on business funding in two steps:
–Step 1 Business funding(yes/no)=f(UIC)
–Step 2 For funding>0, amount of university funding from business firms=f(UIC)
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16. Heckman selection models of signalling and science push at the UPV
•Sample selection bias in science push
•Positive association between UIC and funding: high (science push) or borderline (signalling) –both in Step 2
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Step
Dependent variable
Coefficient of # UICs 2008-2011
(funding 2008-2011)
Coefficient of # UICs 2008-2011
(funding 2012-2013)
1
Business funding (yes/no)
-0.02
-0.05
(0.09)
(0.11)
2
Mean business funding
0.01***
0.12*
(0.00)
(0.01)
# observations
247
247
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17. Heckman selection models of signalling and science push at the UPV
•Sample selection bias in science push
•Positive association between UIC and funding: high (science push) or borderline (signalling) –both in Step 2
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Step
Dependent variable
Coefficient of # UICs 2008-2011
(funding 2008-2011)
Coefficient of # UICs 2008-2011
(funding 2012-2013)
1
Business funding (yes/no)
-0.02
-0.05
(0.09)
(0.11)
2
Mean business funding
0.01***
0.12*
(0.00)
(0.01)
# observations
247
247
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18. Do UIC output volumes correspond with university funding from business firms?
•In general, UICs can occur without business funding, and business funding without UICs – Answer: ‘no’
•For a minority of authors (those who participate in business funded projects), there is a positive association of current UICs and business funding –Answer: ‘yes’ (partial evidence of a science push)
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19. Conclusions
•Convenience of an interactive model to capture the complexity in the relationship between university funding from business firms and UICs
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•UICs as predicting factor: Wong and Singh (2013) also found a positive effect of UICs on university technology commercialization
•Scarce overlap between researchers participating in projects and publication of UICs (consistent with Lundberg et al, 2006)
•Studies based exclusively on UICs to analyse university-industry interactions do not fully capture business funded research –more evidence is needed
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20. Future research
•Analysis of the relationship of several project-related features and the generation of UICs (e.g. type of agreement, duration, gender…)
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•Broader approach, including any type of R&D activity and not only when the source of funding are business companies
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