Laboratory of Industrial and Energy Economics
National Technical University of Athens (LIEE – NTUA)
Innovation and Entrepreneurship Unit
The role of University-Industry R&D Collaboration in
Firms’ Innovative Performance in the Midst of an
economic Crisis: Empirical Evidence from Greece
Yannis Caloghirou*, Ioannis Giotopoulos **
Efthymia Korra***, Aggelos Tsakanikas****
*Professor, Laboratory of Industrial and Energy Economics, National Technical University of Athens
(LIEE/NTUA), Scientific responsible for the Innovation and Entrepreneurship Unit
**Assistant Professor, Department of Economics, University of Peloponnese
***Research Fellow, Foundation for Economic and Industrial Research
****Assistant Professor, LIEE /NTUA
T2S 2015 Conference, 28-30 October 2015, Dublin
Outline
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The topic addressed: research questions
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Motivation
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Data and Methodology
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Empirical results
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Conclusions – policy implications
2
The topic addressed: research questions
The topic
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Explore the role of University – Firm R&D collaborations on
firms’ innovative performance in times of crisis.
Research questions
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How do the potential effects of University – Firm R&D
collaborations on innovation evolve as the crisis deepens?
In which way strategic orientation, intention of competition,
human capital and financial constraints of firms affect their
innovative performance?
Motivation (I)

In today's turbulent economic environment, a firm's ability to
catch up with technological progress and continuously
innovate is crucial for its survival and growth.

However, it is increasingly difficult for firms to explore new
technologies completely on their own as a result of limited
expertise and resources, especially in adverse times.

One of the key mechanisms in improving firms’ knowledge
and innovative content is by collaborating in R&D projects
with Universities.
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Motivation (II)
Scholars highlight the role of University – Firm R&D
collaborations in transforming academic discoveries into
commercial technologies (Faulkner and Senker, 1994; George
et al., 2002; Markman et al., 2009).
From a firm's perspective, collaborations with universities are
imperative for exploiting scientific knowledge and novel ideas
(Caloghirou et al. 2001, Audretsch et al., 2012; Subramanian et
al., 2013).
But in which way do the linkages of University – Firm R&D
collaborations and firm innovation evolve during a crisis?
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The case study of Greece: a developed economy not based on cheap
labor cost trying to “innovate” out of a crisis that caused a 25% GDP
contraction (2007-2013)
State-of-the-art (I)
Theoretical and empirical work in innovation economics suggests that
industry-science relations positively affect innovation performance through
the use of scientific knowledge (Kline and Rosenberg 1986, Rosenberg &
Nelson 1994, Feller 1990, Mowery 1998, Mansfield 1995, Cohen et al 2002).
Veugelers and Cassiman (2005) argue that R&D cooperation between
universities and industry is characterized by
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high uncertainty,
high information asymmetries between partners,
high transaction costs for knowledge exchange requiring the presence of
absorptive capacity at each side of the market transfer,
high spillovers to other market actors (i.e. a low level of appropriation of
benefits out of the knowledge acquired),
and, restrictions for financing knowledge production and exchange activities due
to risk-averse and short-term oriented financial markets.
State-of-the-art (II)

Tether (2002) suggests that collaboration with universities is generally aimed at
radical breakthrough product innovations that may open up entire new markets or
market segments;

Agrawal (2006) found that when firms involve university based inventors in
commercializing an invention, they tend to be more successful than when they do
not.
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Henard and McFadyen (2006) argue that, because universities are venues for a
wider range of ideas and multidisciplinary perspectives than most companies, their
potential to deliver on multidisciplinary research initiatives is greater. No other
organization possesses a comparable breadth of new knowledge.

As Agrawal and Henderson (2002) and Henard and McFadyen (2006) suggest,
temporary exchanges of researchers, conference attendance, graduate student
internships, and a variety of other creative mechanisms allow universities and
companies to connect and exchange knowledge in a mutually profitable relationship.
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Contribution
Despite some recent studies examine how the crisis
affected the linkages between
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innovation and R&D expenditures, size, age, concentration
(Berchicci et al., 2013)
innovation and human resources, high-tech specialization,
financial development (Filippeti and Archibugi, 2011)
innovation and in-house R&D, financial constraints, explorative
and exploitative strategies (Archibugi et al. 2013)
However, few studies as far have explored the role of
University – Firm R&D collaborations on firm innovation
in times of crisis: the unique case study of Greece
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8
Data used
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2 extensive surveys
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In the largest Greek firms at the national and regional level
(in terms of employment)
In two waves with a structured questionnaire
CATI approach, but also some face to face interviews
1st wave: Burst of the crisis 2nd wave: Peak of the crisis

Period: 2011
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Period: 2013
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Total number of firms: 2025
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Total number of firms: 2048
1500 firms have participated in both waves
Methodology

Two separate equations were estimated by applying
binary probit regressions per period (wave)
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(1) Product Innovation;
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(II) Process Innovation;
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f {R&D collaborations, Exploration Strategy, Low Cost Strategy,
Differentiation Strategy, Bank financial constraints,Value chain
financial constraints, Price competition, Quality competition,
Training Program, Education Level, Age, Size, Industry dummies}
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Dependent variables
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Innovation
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Product Innovation: Has the company introduced any new
or improved products over the 3-year period covered by
the survey (no=0; yes=1)
Process Innovation: Has the company introduced any new
or improved processes over the 3-year period covered by
the survey (no=0; yes=1)
Independent variables:
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University – Firm R&D collaborations : To what
extent does your company use universities and research
centers as a source of knowledge (not at all: 1, …. 5: to a
great extent)
Strategic Factors
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Low Cost Strategy: Does the company produce standardized
products/services for mass markets? (no=0; yes=1)
Differentiation Strategy: Does the company produce
differentiated products/services? (no=0; yes=1)
Exploration Strategy: To what extent does your company ‘s
strategy involve the following: (i) entering new markets (ii)
increase range of goods or services; (not at all: 1, …. 5: to a
great extent)
Independent variables:
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Liquidity Constraints
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Liquidity Constraints_Bank Credit: To what extent does your company
face liquidity constraints due to restricted access to credit lines?(not at
all: 1, …. 5: to a great extent)
Liquidity Constraints wrt Trade credit: To what extent does your
company face liquidity constraints because of your suppliers and/or
customers liquidity problems?(not at all: 1, …. 5: to a great extent)
Competition Pressure
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Price competition: To what extent does your company face pressure
from cost based competitors? (not at all: 1, …. 5: to a great extent)
Quality competition: To what extent does your company face pressure
from quality based competitors? (not at all: 1, …. 5: to a great extent)
Independent variables:
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Human Capital
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Firm characteristics:
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Training Programs: Does your company perform corporate
training programs? (no=0; yes=1)
Education Level: What percentage of employees have
completed tertiary education?
age(ln)
Size (ln employees)
Sector dummies: 5 categories (1: Extracting, 2:
Manufacturing, 3: Construction, 4: Trade, 5: Services)
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Product Innovation
University-Firm R&D collaborations
Exploration Strategy
Low Cost Strategy
Differentiation Strategy
Liquidity Constraints_Bank Credit
Liquidity Constraints wrt Trade
credit
Price based Competition
Quality based Competition
Training
Education Level
Size
Age
1st wave (2011)
2nd wave (2013)
0.025*(0.015)
0.056***(0.013)
0.083***(0.015)
0.066***(0.014)
0.009(0.034)
0.047(0.032)
0.125***(0.033)
0.097***(0.033)
0.008(0.013)
-0.022*(0.012)
0.005(0.014)
0.002(0.016)
0.016(0.014)
0.017(0.014)
0.029(0.018)
0.002(0.015)
0.151***(0.039)
0.117***(0.037)
0.148**(0.062)
0.041(0.057)
0.042***(0.015)
0.032**(0.014)
-0.021(0.032)
-0.04(0.034)
Notes: The estimations include sector dummies. Marginal effects are presented
***, **, * denote significance on p<1%, 5%, 10%
Process Innovation
1st wave (2011)
2nd wave (2013)
University – Firm R&D
collaborations
0.028**(0.013)
0.03***(0.01)
0.053***(0.014)
0.024**(0.012)
0.000(0.03)
0.046*(0.026)
0.051*(0.031)
0.060**(0.028)
-0.005(0.011)
-0.005(0.01)
0.003(0.013)
-0.024*(0.012)
0.002(0.013)
0.016(0.011)
-0.009(0.016)
-0.014(0.012)
0.100***(0.034)
0.116***(0.027)
-0.055(0.056)
-0.050(0.046)
0.052***(0.013)
0.019*(0.011)
-0.023(0.029)
-0.022(0.024)
Exploration Strategy
Low Cost Strategy
Differentiation Strategy
Liquidity Constraints_Bank Credit
Liquidity Constraints wrt Trade
credit
Price based Competition
Quality based Competition
Training
Education
Size
Age
Notes: The estimations include sector dummies. Marginal effects are presented
***, **, * denote significance on p<1%, 5%, 10%
Discussion of results: on the role of
liquidity constraints

Recent crisis led bank credit constrained firms and/or firms with trade
credit problems to postpone or cancel their plans to be engaged into
innovative activities. BUT only small effect
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

Credit crunch affects negatively product innovation in the midst of the crisis.
Liquidity constraints related to the supply chain (i.e. customers/suppliers) have a
negative impact on process innovation in the midst of the crisis.
These findings are in the same line with:
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Savignac (2007) who reveals that financial constraints significantly reduce the
likelihood that firms will be engaged to innovative activities.
Paunov (2012) who finds that the recent crisis caused significant innovation
project discontinuations possibly related to increased financing constraints.
Silva and Carreira (2011) who insinuate that financial constraints negatively
influence the amounts invested in research and development and consequently
affecting negatively the innovation process.
Discussion of results: product/process innovation
and University-Firm R&D collaboration

Firms amend for lower R&D expenses by developing
or strengthening the collaborations with universities

As the crisis deepens, firms rely more heavily on
collaborative research

At the beginning of the crisis the probability for firms to
introduce product or process innovation:
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
As the crisis deepens product and process innovation
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Is affected in a significant and positive way by University-Firm R&D
collaborations
Are both positively related to University-Firm R&D collaborations
and to an even greater (stronger significance).
Discussion of results: on the role of
human capital
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Firms, which invest highly in R&D, are more prone to have
absorptive capabilities to learn and interact with
universities (Cohen et al., 2002; Fontana et al., 2006)

Training of employees plays a crucial role on product/process
innovation in times of crisis

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Training facilitates employees' exposure to variety of knowledge and
openness to innovative ideas (Brockbank, 1999; Beatty and Schneier, 1997;
Jaw and Liu, 2003).
In collaborative research, technical expertise merely
comes from the pool of researchers in the university
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Employees’ education level has been found significant only for
product innovation at the beginning of the crisis
Discussion of results: on the role of
strategic factors
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In times of crisis (2011-2013) the probability to innovate is
positively related to exploration and differentiation strategies.
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Large firms seeking new business lines to acquire market share or to
open new markets during economic turbulences seem to successfully
cope with these difficult conditions through risk taking and
experimentation.
Thus, firms in such conditions characterized by market contractions can
establish their power and nullify their competitors’ strength by
identifying a new segment and serving new customers who have a
different value system (Porter 1985).
Low cost strategy matters only for process innovation in the
midst of the crisis (2013)
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Large firms appear to pay special attention to cost reduction because of
the greater pressure from the deep recession: lower demand,
contraction of disposable income
Conclusions
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Liquidity constraints with respect to bank credit and trade
credit hinder product and process innovation respectively, in the
midst of the crisis.
Crisis facilitates the transition from a corporate model of
knowledge production to a new distributed, inter-organisational,
innovation model
In the new distributed model of innovation
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Knowledge transfer mechanisms (i.e. training) play an enhanced role
In the midst of crisis when unemployment rates are increasing
there is a wider supply of well educated personel
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Firms do not differentiate on grounds of employees’ education level
Exploration and differentiation strategies continue to drive
innovation even in turbulent economic conditions
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References I

Agrawal, A. (2006). "Engaging the inventor: Exploring licensing strategies for university inventions and
the role of latent knowledge." Strategic Management Journal 27: 63-79.

Archibugi, D., A. Filippetti, et al. (2013). "Economic crisis and innovation: Is destruction prevailing over
accumulation?" Research Policy 42(2): 303-314.

Audretsch, D. B., D. P. Leyden, et al. (2012). "Universities as research partners in publicly supported
entrepreneurial firms." Economics of Innovation and New Technology 21(5-6): 529-545.

Berchicci, L. (2013). "Towards an open R&D system: Internal R&D investment, external knowledge
acquisition and innovative performance." Research Policy 42(1): 117-127.

Cohen, W. M., A. Goto, et al. (2002). "R&D spillovers, patents and the incentives to innovate in Japan
and the United States." Research Policy 31(8): 1349-1367.

Cohen, W. M., R. R. Nelson, et al. (2002). "Links and impacts: the influence of public research on
industrial R&D." Management science 48(1): 1-23.

Caloghirou, Y., A. Tsakanikas, et al. (2001). "University-industry cooperation in the context of the
European framework programmes." The Journal of Technology Transfer 26(1-2): 153-161.

Faulkner, W. and J. Senker (1994). "Making sense of diversity: public-private sector research linkage in
three technologies." Research Policy 23(6): 673-695.

Feller, I. (1990). "Universities as engines of R&D-based economic growth: They think they can."
Research Policy 19(4): 335-348.
References II

Fontana, R., A. Geuna, et al. (2006). "Factors affecting university's industry R&D projects: The
importance of searching, screening and signalling." Research policy 35(2): 309-323.

George, G., S. A. Zahra, et al. (2002). "The effects of business-university alliances on innovative output
and financial performance: a study of publicly traded biotechnology companies." Journal of Business
Venturing 17(6): 577-609.

Jaw, B.-S. and W. Liu (2003). "Promoting organizational learning and self-renewal in Taiwanese
companies: the role of HRM." Human resource management 42(3): 223.

Mowery, D. C. (1990). "The development of industrial research in US manufacturing." The American
Economic Review: 345-349.

Paunov, C. (2012). "The global crisis and firms' investments in innovation." Research Policy 41: 24-35.

Porter, M. E. (1985). "Technology and competitive advantage." Journal of business strategy 5(3): 60-78.

Rosenberg, N. and R. R. Nelson (1994). "American universities and technical advance in industry."
Research policy 23(3): 323-348.

Subramanian, A. M., K. Lim, et al. (2013). "When birds of a feather don't flock together: different
scientists and the roles they play in biotech R&D alliances." Research Policy 42(3): 595-612.

Veugelers, R. and B. Cassiman (2005). "R&D cooperation between firms and universities. Some
empirical evidence from Belgian manufacturing." International Journal of Industrial Organization
23(5): 355-379.
Thank you
Aggelos Tsakanikas:
atsakanikas@central.ntua.gr