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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.
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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, Mayte López-Ferrer, Robert J.W. Tijssen
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
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)
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
Science and Technology Indicators Conference
Research question
• Our objective is to contribute to prove whether or not UICs are
good proxies of university-industry interactions
5
Do UIC volumes correspond with university funding from
business firms?
• Research question
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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• Need of a conceptual framework
Four types of theoretical relationships between
funding and UIC – an interactive model
6
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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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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Types of funding and UIC relationships
at UPV
8
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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Pairwise correlation coefficients (R)
9
• 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 fundingR = -0.01 0.15
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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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Let’s start with the left half of the picture
11
Industry financing
Industry pull
University funding from
business firms2000-2007
UIC2008-2011
University funding from
business firms2008-2011
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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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Heckman selection models of financing and
industry pull at the UPV
13
• 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
Science and Technology Indicators Conference4/8/2014
Let’s move to the right half of the picture
14
University signalling
Science push
UIC2008-2011
University funding from
business firms2012-2013
University funding from
business firms2008-2011
Science and Technology Indicators Conference4/8/2014
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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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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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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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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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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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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www.ingenio.upv.es
INSTITUTE OF INNOVATION AND KNOWLEDGE MANAGEMENT