Workshop
University-Industry Linkages:
from Theory to Policy Università Roma Tre, Rome, 26-28 May 2014
University-Industry Linkages and Local Economic Development
Simona Iammarino
London School of Economics
Department of Geography & Environment
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Outline
• To identify for U-I links:
broad trends
main types
motivations & conditions
• To highlight the importance of geography for U-I links
• To shortly give account of some empirical evidence on U-I research collaborations and proximity
• To emphasise the critical role of U (and tis multiple relationship with I) for regional development
• To draw some implications for local economic development (LED) policy
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3 3
Trends in U-I linkages
• 1980s onwards – Changes driven mainly by
– Increased speed and complexity of knowledge and technology creation and exploitation
– Increased globalisation, competition and emphasis on innovation: firms need to get closer to knowledge sources
– declining profits and/or increasing costs of research encouraged firms to outsource more basic research (not only to U)
– budgetary constraints faced by governments and universities: search for new funding sources
– Industry increasingly interested in university research as well as highly specialised personnel – seen as offering specific opportunities for cooperation
– ‘Heroic myths’ highly localised: MIT & Route 128, Stanford & Silicon Valley, ‘the Cambridge Phenomenon’
– Government policies – at both national and local level – encouraging e.g. technology transfer, collaborative research in key areas, commercialisation of research
4 4
Typologies of U-I links
Great emphasis of the literature on:
• academic capacity to generate and exploit IPR via
patenting
• academic spinoffs
However:
variety of U-I interactions far more important than
patents, licencing and academic start-ups
See D’Este & Patel, 2007
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Typologies of U-I links (II)
D’Este & Patel, 2007, Table 2, p. 1301
Motivations for U-I links
University: • Obtain financial support for
its missions
• Broaden experience of
students and faculty
• Identify significant and
interesting research
problems
• Increase employment
opportunities
• Enhance regional economic
development
Industry: • Access research infrastructure
• Access expertise
• Aid renewal of firm’s technology
• Gain access to potential
employees
• Expand contacts for corporate lab
• Increase pre-competitive
research
• Leverage internal research
capabilities
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Conditions for U-I links
More likely to occur for some firms than for others due to firm’s characteristics (most studied: e.g. Faulkner et a., 1995; Mansfield, 1995; Marsili, 1999; Mohnen & Hoareau, 2003; Arundel & Geuna, 2004; Fontana et al. 2006; Abramovsky et al., 2007, D’Este & Iammarino, 2010)
• Size of firm affects collaboration
• R&D investment and/or R&D intensity:
• Type of innovation: product versus process innovation:
• Independent versus subsidiaries
• Technological and industrial sector
More likely to occur in some universities than in others (e.g. Howell et al., 1998; Meyer-Krahmer & Schmock, 1998; Etzkowitz & Leydesdorff, 2000; Cohen et al., 2002; Feldmand et al., 2002; D’Este et al.,
2005) due to differences in: • Academic culture of the University
• Development strategy of the University
• Local context
• Scientific discipline
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The rising importance of localised U-I links
• Universities as key actors in the generation and diffusion
of new knowledge and externalities (spillovers), and at
the centre of academic and policy attention
• 3 broad strands of literature interested in U-I linkages for
the creation and diffusion of new knowledge across
space: 1) studies on localised knowledge spillovers
(LKS); 2) studies on the systemic nature of knowledge
and innovation, i.e. ‘Systems of Innovation’, ‘Triple Helix’;
3) studies on industrial clustering, local and regional
systems and development
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While LKS places more weight on externalities
(geographical proximity) from academic research, and the
SI/TH/industrial clustering literatures emphasise U-I
interactions and networks (regional location), ALL 1-2-3
share similar underlying assumptions:
• Spatial proximity favours U-I linkages because of the
tacit and sticky nature of knowledge
• Thus, knowledge that spills over “is a public good, but a
local one” (Breschi and Lissoni, 2001b, 980)
Problem with tacit vs. codified dichotomy: what is "tacit" (the
transit) depends on the shared codification capabilities of
the actors (e.g. Steinmueller, 2000; Cowan, David & Foray, 2000; Antonelli,
2003; Foray, 1998, 2004)
Common grounds
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Table 3. Distribution of partnerships according to regional location of business units and universities
Region Business Units Universities
East Midlands 8.5 8.9
East of England 12.8 10.1
London 5.6 15.4
North East 3.6 4.0
North West 10.8 12.3
North. Ireland 1.0 1.5
Scotland 4.5 9.2
South East 21.8 10.8
South West 9.7 5.6
Wales 2.3 3.2
West Midlands 9.1 7.5
Yorkshire & Humberside 4.8 11.6
Outside UK 5.4 n.a.
Total 100% 100%
Number of observations 4525 4525
Partnerships: within the same region, 20% ; between neighbouring regions, 35%; between faraway regions, 45%
Example: UK
U-I research linkages and regions D’Este & Iammarino (2010)
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Short background:
Effects of geographical space depend on other forms of
proximity (i.e. cognitive, organisational, social, relational,
institutional) (e.g. Nooteboom, 1999, 2007; Torre & Gilly, 2000; Boschma,
2005; Ponds et al., 2007; Massard & Mehier, 2010; Balconi et al., 2011)
Indirect role of space in fostering knowledge creation,
interactive learning and innovative networks by bridging and
reinforcing other forms of proximity among different actors (U-I)
involved in knowledge creation and diffusion
“Geographical proximity can be considered a necessary, but not sufficient
precondition for the existence of a territorially based system of innovation [...] “
(Fisher, 2001, 210)
“[...] geographical proximity per se is neither a necessary nor a sufficient
condition for learning to take place” (Boschma, 2005, 62)
What type of proximity matter for U-I links? D’Este, Guy & Iammarino (2013)
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Characteristics of U-I research partnerships
Discipline % of partnerships
Chemical Engineering 5.9
Chemistry 9.4
Civil Engineering 11.0
Computer Science 7.4
Electrical and Electronic Engineering 14.5
General Engineering 11.6
Mathematics 2.5
Mechanical, Aero. and Manuf. Eng. 21.3
Metallurgy and Materials 9.9
Physics 6.3
Total (%) 100%
Breakdown by discipline of university departments
involved in the partnerships (no. obs.: 4525 partnerships)
74% of the
partnerships are
with Engineering–
related departments
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Industry % of firms
Chemicals & Chemical Related 11.8
Electrical / Electronics 9.3
Instruments 5.9
Machinery / Metals 10.4
Transport 7.7
Utilities & Construction 7.9
Manufacture n.e.c. 3.9
Computer Services 5.1
Research & Development 5.4
Consultancy and other Business Services 17.4
Services n.e.c. 15.4
Total (%) 100%
Service firms
account for
43% of
partnerships
Breakdown by industry (no. obs.: 4525 partnerships)
Characteristics of partnerships (II)
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Industries draw upon different sources of knowledge from universities. It makes sense
to consider the degree to which industries share similar profiles (or distinct profiles)
Industry / Discipline Chem.
Eng.
Chemistry Civil
Eng
Computer
Science
Electrical
Eng.
General
Eng
Maths Mechan
Eng.
Materials Physics Total
Food Products & Beverage 26 4 0 13 0 0 13 30 13 0 100
Basic Chemicals 19 43 4 2 3 5 0 10 4 10 100
Pharmaceuticals 23 51 4 10 2 0 3 2 3 1 100
Glass, ceramics 8 9 14 1 7 14 1 13 22 9 100
Machinery & Equipment 6 6 4 4 17 18 2 32 7 4 100
Office Machinery & Comp. 0 8 3 27 26 8 4 10 3 10 100
Electrical Machinery 3 1 3 6 39 16 1 13 8 11 100
Medical & Surgical Instrum. 3 18 1 4 15 24 0 14 6 15 100
Motor Vehicles 1 2 0 4 15 13 1 52 10 2 100
Aircraft & Spacecraft 0 2 1 1 15 16 0 39 24 2 100
Telecommunications 0 3 1 46 33 6 6 1 1 1 100
Software consultancy 4 2 8 30 14 10 8 23 2 1 100
R&D Services 9 12 21 4 10 7 4 15 5 14 100
Architectural & Engin. Cons. 5 3 25 4 10 12 2 24 12 3 100
Proportion of partnerships across scientific disciplines, by industry (D’Este et al. (2012), following Cohen et al., 2002)
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-.002
0
.002
.004
.006
Mar
gina
l Effe
ct o
f Firm
-Uni
vers
ity P
roxi
mity
0 20 40 60
Spatial Clustering of Firms - Unweighted Index
Marginal Effect of Firm-University ProximityProbability of Partnership
As Clustering of Firms Varies
Figure 1a
-.002
0
.002
.004
.006
Mar
gina
l Effe
ct o
f Firm
-Uni
vers
ity P
roxi
mity
0 20 40 60
Complementarity-Weighted Spatial Clustering of Firms
Marginal Effect of Firm-University ProximityProbability of Partnership
As Clustering of Firms Varies
Figure 1b
Main result
Industrial clustering and geographical proximity are substitutes: geographical
proximity decreases importance in shaping the probability of U-I partnership formation
when firms are part of an industrial cluster. In most densely and technologically
related clusters, geographical proximity becomes almost unimportant
The 1° mission of U, and the region
• Graduates’ entry into the labour market is a critical mechanism
through which public investment in higher education bares its
returns (e.g. Pavitt, 1991; Salter and Martin, 2001)
• As well as carrying up-to-date knowledge, graduates bring into the
labour market competencies and capabilities to combine and use
knowledge in new productive ways (e.g. Walters, 2004; von
Tunzelmann and Wang, 2007)
• The returns to public, as well as private, investment in human capital
crucially depends on the use that graduates can make of their
education in the labour market, that is, on the degree of their
education-job match
• However, the geographical dimension of graduates’ skill use and
recognition by labour markets, especially at the sub-national level, is
still underexplored
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Table 2 - Employment rate and indicators of education-job (mis)match by Italian macro-region
% Empl.
rate
% Degree
necessary for job
(q.1b)
North 83.4% 68.5%
Centre 72.0% 67.4%
South 59.8% 72.6%
58.3%
55.3%
60.9%
12.1%21.7%
18.3%
11.3%
10.9%
9.1%
10.3%
11.7%
% Apparent
overeducation
% Apparent
match% Real match
69.5%
66.2%
70.0%
20.2%
% Degree
formally required
(q.1a)
% Real
overeducation
Figure 1 – The matrix of education-job (mis)match
Was the degree effectively necessary to carry out the job?
YES NO
Was the degree
formally required?
YES REAL MATCH:
matched qualification, full skill
utilisation
APPARENT OVEREDUCATION:
matched qualification, skill
underutilisation
NO APPARENT MATCH:
overqualification, full skill
utilisation
REAL OVEREDUCATION:
overqualification, skill
underutilisation
E.g. Graduates’ education-job (mis)match (Iammarino and Marinelli, 2014)
Graduate self-
assessment Employer’s
requirement
Some implications for LED
• Increasing U-I partnerships can help transform local innovation systems into more collaborative entities, but…
– U-I research links may be especially important when new technologies/industries emerge, and become less important as the technologies become established
• Geographical proximity matters in U-I relationships, but…
– Promotion of U–I linkages on a more selective basis: factors that enhance knowledge diffusion at the local, regional or national level
• Engagement should not only be about excellence but also about….
– Competencies, skills, human capital: skill-matching in the local labour market: business sector demand and university/education institutes supply; production & retention of skills and HK
• University education and research have a value per se, independent of whether or not they are connected directly with industry
• ‘Weaker’ universities to be supported to improve internal scientific qualities, rather than being pushed to becoming problem-solvers for industry (especially in backward regions and emerging economies)
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Thus, our main points are:
• Attention on the factors driving the formation of ‘valuable’ linkages rather than to U–I linkages per se (e.g. Giuliani & Arza, 2009)
• Critical: typologies of U-I linkages numerous and varied: which links for which place?
• U can help bridge different knowledge bases present in the region (i.e. science-based, engineering-based, but also design-based, cultural/arts-based), and therefore spur the process of diversification based on relatedness and complementarity
Some implications for LED (II)
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….However, the key importance of universities for
NIS and RIS has still to be seen in the traditional
roles of providing highly qualified graduates, doing
excellent scientific work, providing basic science
and R&D
(Franz Tödtling - Expert meeting on The future of academic research, Vienna,
19-20 October 2006; emphasis added)
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Thank you for your attention!
