Local and Regional Innovation
OECD Capacity Building Seminar
Supporting SMEs in a Time of Crisis
Jay Mitra
13 October, 2009
Definitional Issues

Entrepreneurship = new opportunity identification & realisation

(for the purpose of this paper ‘E’ = new business creation)

Innovation = successful exploitation of a new idea

Culture = a set of attitudes/beliefs common to a group

Culture = a set of activities concerned with moral, aesthetic, and
intellectual aspects of life (activities include some element of
creativity in production, communication of meaning & intellectual
property)

Culture = a diverse way of life (from beef steak to Beethoven to
Eminem)


Entrepreneurial Culture = diverse set of attitudes, beliefs, systems,
institutions and structures that are connected together with a view to
supporting new venture creation, innovation and growth in a
particular environment & in regional innovation systems.
Why Innovation Systems?

Innovation is non-linear but involves interaction
between many actors

Interest resulting from research on the success of
the Japanese model (Freeman, 1987)

Emergence of “innovation systems” models
(Freeman, 1987)
Key Models of Innovation Systems

National innovation systems (Freeman, 1987; Lundvall, 2007)

Regional innovation systems (Cooke 1992; Braczyk et al.,
1998)
Some Stylised Facts and Assumptions
F/A 1: Innovation = source of economic growth

The endogenous model)– critical importance of
technological change in economic growth ( total
factor productivity accounted for 87.5% of
economic growth – Solow, 1957) Romer, 1990,
OECD 2003

Strong emphasis on role of R&D, skilled labour
& knowledge spillovers – greater productivity,
product quality dependent on innovation
Some Stylised Facts and Assumptions
F/A 2: Innovation is not evenly spread but spatially
concentrated
Well-known concentrations = Oxford; Cambridge; SE, UK;
Lombardy; Bangalore, Shanghai
High urban focus – OCED countries
Significant local differences within countries (Camagni &
Capello, 1997; Keeble, 1996; Acs, 2002)
Different measures – innovation output (patent
applications) & input/output (employment in high
technology manufacturing & knowledge-intensive
industries)
Source: adapted from Eurostat
Subnational Variations in European Patent Applications, 2002
Top Territories
Patent
Applications
per million
inhabitants.
Bottom territories
Patent
Applications
per million
inhabitants
Zuid Nederland,
Netherlands
797
Noreste, Spain
34
Baden Wuttenburg,
Germany
597
Sud, Italy
14
Bayern, Germany
473
Attiki, Greece
13
Isole, Italy
11
Ile de France, France 313
Maner Suomi, Finland
312
French Overseas
Departments
6
Eastern, UK
253
Continente, Portugal
5
Westosterreich, Austria
223
Kentriki Ellada, Greece
4
SE, UK
205
Madeira, Portugal
1
Mean
131
Acores, Portugal
0
Median
96
Source: Eurostat
Subnational Variations in Innovation-Related Employment- High Tech
Manufacturing , 2003
Top territories
Employees in
HT
manufacturing
(% of total
Manufacturing
employees)
Bottom Territories
Employees in
HT
manufacturing
(% of total
Manufacturing
employees)
Aland, Finland
69
Centro, Spain
38
London, UK
61
Sur, Spain
38
Manner Suomi, Finland
59
Continente, Portugal
37
Hamburg, Germany
57
Voreia Ellada, Greece
36
SE, UK
57
Acores, Portugal
34
Brussels, Belgium
56
Canarias, Spain
33
Ile de France, France
56
Madeira, Portugal
32
SW, UK
55
Kentriki Ellada, Greece
29
Eastern, UK
54
Nisia Aigaiou, Kriti,
Greece
28
Mean
47
Median
48
Top Territories
A*
Bottom Territories
A*
SE, UK
17
Vlaams Gewest,
Belgium
5
Berlin, Germany
16
WM, UK
5
Scotland, UK
14
Sud, Italy
4
Schieswig Holstein,
Germany
14
Centro, Italy
4
Dunantul, Hungary
13
Yorkshire & Humber,
UK
4
Ile de France, France
13
Attiki, Greece
4
Kozep Magyarorszag,
Hungary
12
Este, Spain
3
Sudosterrrich, Austria
11
Sur, Spain
2
Baden Wurttermburg,
Germany
11
Noreste, Spain
2
Mean
8
Continente, Portugal
2
Median
7
* A = Employees In KI services
as % of total employees
Source: Eurostata
Subnational Variations in Innovation-Related Employment –
Knowledge Intensive Industries
Some Stylised Facts and Assumptions
F/A 3: SMEs participate in innovation process

Classic ‘structure-conduct-perfomance’ model = large firms have monopoly
positions, commit substantial R&D

Alternative model = SMEs have more impact (more radical innovation,
Baumol, 2002)

Importance of business churning (OECD, 2003) to national productivity

Empirical evidence suggests that both small and large firms play a part –
dependent on active links to knowledge of market (users) & knowledge of
materials & machinery (suppliers) & non-firm organisations

Small firms rely heavily on external environment

Spatial business clusters – association between spatial concentrations &
rates of technological innovation (Baptista and Swann, 1998)
Source: OECD, 2005ecd
Frameworks for Analysing Innovation Process in Agglomerations
Framework
Mechanisms supporting SME innovation
Porterian Clusters (Porter,
19900
Rivalry between competitors; specialised facotrs of production (land,
labour, capital); large & growing demand & sophisticated customers;
related industries & support institutions
Marshallian districts (Pyke,
et al, 1990)
Non pecuniary externalities from knowoedge spillovers through informal
personal exchanges, customer supplier transactions; labour pooling;
inter-firm linkages
Innovative milieux
Linkages between firms through labour mobility & informal networking,
supporting collective learning; reduction of uncertainty
Learning Regions (Storper,
et al, 1997; Morgan, 1997)
Untraded interdependencies between local firms & other organisations;
use of formal & informal information & collaboration networks & labour
market interactions; facilitated by trust & social capital & technology
support organisations
Local Innovation Systems
(Cooke, Heindrich &
Braczyk, 2004; Howells,
1999)
Knowledge generation, exchange & exploitation in system with
important learning interactions among suppliers, customers, public
research organisations, financial institutions. Supported by local
policies
Why is a Regional Innovation System important?

Innovation = 80% of productivity growth and comparable figure for GDP
(Freeman, 1994)

Regional disparities in innovation & GDP (Acs, 2002; Cooke et al., 2002)

Innovation = higher in regions with more knowledge generation e.g. R&D by
firms & institutions (Acs, 2002)

Region = new focus of economic policy (Cooke et al. 2003)
Why are Local/regional Innovation Systems Relevant?

Most processes driving innovation occur locally –
knowledge embedded in people ; distance decay effects
in rate of knowledge & information links;

SMEs have spatially restricted search patterns for
collaborative partnerships or technological inputs;

Different localities have different sector specialisations &
distinct sets of innovation processes;

Strong local differences in innovation performance
Source: OECD, 2005
Market Failures and SME Innovation
Type of Failure
Nature of Failure
Potential local policy
actions
Information failure
Barriers to flow of information on
innovation opps. Lead to missing markets
& constraints for SMEs in obtaining
finance, partners, etc.
Promotion of networks &
partnerships. Public support to
SME research projects
Public goods
Undersupply of non rival goods & non
excludable goods that contribute to SME
innovation – e.g. university research
Public policy of basic
innovation infrastructure locally
Externalities
Undersupply of activities that benefit
others in addition to producers – e.g.
training of highly skilled labour; reduced
incentives to SME innovation
Direct public support for SME
research projects for training of
highly skilled labour in local
specialisms
Monopolies
Incumbent firms restrict entry through
branding & other behaviour, constraining
ability of innovative, new & small firms to
enter market & compete
“Second best” policies
supporting SMEs in order to
“level the playing field”. Support
of new firm entry in local sector
specialsims.
Indivisibilities
Indivisible cost in creating knowledge. If
marginal cost pricing is used fixed cost is
irrecoverable, constraining production of
knowledge by SMEs & others
Public funding of public &
private research projects with
Potential spin offs for SMEs
System Failures & SME Innovation
source: OECD, 2005, Lundvall & Borras, 1997
Type of Failure
Nature of Failure
Potential Local policy action
Infrastructure Provision
Underinvestment in local infrastructure with which
firms interact – e.g. communications
infrastructure
Incentives for private or public communications &
knowledge transfer infrastructures
Transition & lock in
failures
Firms & localities are highly capable in their own
technological areas but in related ones. Unable to
switch from existing technologies
Incentives for technological activities that broaden
firm & organisational capabilities & nurturing of
emerging systems
Institutional failures
Institutional & regulatory context has unexpected
negative impact
Monitoring & adjusting local institutions &
regulations
Learning failures
Firms may not be able to learn rapidly &
effectively
Developing firm capabilities through human capital
programmes, support for R&D 7 technology
dissemination policies. Opening channels to
knowledge sources
Suboptimal balance bet.
exploitation &
exploration
Local innovation concentrations may work too
much on exploitation & not enough on exploration
(or vice versa)
Using public procurement & funding to support
exploration, introducing diversity in industry by
supporting new & small firms; supporting variety
through dissemination of codified information
Suboptimal balance bet.
selection & variety
Local innovation concentrations may have too
rapid selection whereby underperforming firms
close, & too little variety, in terms of firms &
activities carrying potentially promising
technologies
Strengthening competition policies & use industrial
& technological policies to support new firms
carrying potentially promising technologies ( or
weaken competition policies & limit use of industrial
& technological policies supporting firms that are
likely to fail)
Appropriability traps
Too stringent appropriability may limit
spread of knowledge within innovation
system
Encouraging local knowledge transfers
Complementarities
failures
The appropriate complementarities may not be
present in local innovation system
Formation of R&D networks; industry university
interfaces & bridging systems
What is Regional Innovation System?

“Regional innovation system consists of interacting



knowledge generation
and
exploitation sub-systems linked to global, national and other
regional innovation systems for commercializing new knowledge”
(Cooke, 2004 p.3)

Emphasis: Firms in interaction with other firms & knowledge
infrastructure at regional level.
Regional Innovation Systems (RIS)
ESSENTIAL NOTIONS:

Tacit knowledge = Innovation involves face-face interaction between actors
due to tacit knowledge e.g. experience (Maskell and Malmberg, 1999)

Costs of interaction = Regional level has lower distance, transportation &
communication costs (Audretsch, 1998; Krugman, 1991)

Local networks = Innovation is higher in regions with local networks of
SMEs and R&D (Maskell & Malmberg, 1999; Asheim & Gertler, 2004)
Sub-Systems of RIS
1.
2.
Knowledge Generation:

Public & private research laboratories

Universities & Colleges for scientific & technical training

Firms that transfer knowledge
Knowledge Exploitation:

Firms with regional & global value chain relationships

Venture capitalists

Consultants
Adapted from: Cooke et. al., (2003)
Basic Arguments of RIS
1.
Innovation process is social

Innovation = involves face-face interaction
between actors internal & external to the firm (Maskell
and Malmberg, 1999)
Basic Arguments of RIS
2. Region facilitates interaction

Region = lower distance, transportation & communication costs for
interaction (Krugman, 1993)

Face-to-face interaction and cooperation are easier at the regional
level
Basic Arguments of RIS
3. Regional concentration of R&D firms & institutions boosts
innovation

Combination of knowledge generation (e.g. by universities) &
exploitation (by SMEs with local networks) boosts innovation

Local concentration increases capacity to use external knowledge
for innovation
Adapted from: Cooke et al., 2003 ; Asheim & Gertler, 2004
Basic Arguments of RIS
4. External Links boost innovation

Entering global markets

Sourcing Knowledge from global sources (e.g. R&D)
Links between RIS and Entrepreneurship

Entrepreneurship – requires knowledge and resource seeking (e.g.
technical knowledge, finance, consultancy etc.)

Innovative activity of firms and entrepreneurs are largely based on localised
resources (Asheim et. al., 2003; Cooke et. al., 2000)

RIS provides access to critical resources for entrepreneurship within
proximity
RIS Public Governance System

Grass roots – SME dominated or industrial district (less public
governance)

Networked – Associated between regional governance & industry
pronounced

Centralist – Governance is strongly centralised
Cooke et. al (2003)
Problem of RIS: Few Regions in the world are high-tech clusters
Business innovation system
Typology of Regional Innovation Systems
Globalist
California
North-Rhine Westphalia
Mid-Pyrenees
Interactive
Catalonia
Baden-Wurttemberg
Quebec
Localist
Tuscany
Tampere
Northern Ireland
Grassroots
Networked
Centralist
Public Governance System
Source: Braczyk et. al. 1998; Cooke et. al. (2003 p.368)
Developing Innovation Systems

Identify Strong Sectors/Candidate Clusters

Investigate Regional Clusters

Identify Competitive Advantage

Identify Innovation Practices

Cooperative or Individualistic?

Innovation Support System
Conditions for Assessing RIS
1.
Infrastructure issues
2.
Superstructure
Conditions for Higher & Lower RIS Potential
Higher RIS potential
Infrastructure level

Regional private equity

Policy influence on infrastructure

Regional university-industry strategy
Superstructural level
Institutional dimension

Co-operative culture

Interactive learning

Associative consensus
Organisational Dimension (firms)

Worker mentoring

Externalisation

Interactive innovation
Organisational dimension (policy)

Monitoring

Consultative

Networking
Lower RIS potential












Decentralised spending
National financing organisation
Limited influence on infrastructure
Competitive culture
Individualistic
Institutional dissension
Self acquired skills
Internationalisation
Stand alone R&D
Reacting
Authoritative
Hierarchical
Adapted from: Cooke et. al. (2001)
Regional Enterprise Support System for Innovation
National Policy
Ministrics
Programme
approval
Assembly
Legitimation
Information
Advice
National
technology
agency
Information
Reporting
Requirement
Proposals
National
Research
Institutes
Information
Strategy
SME Agency
FDI Agency
Business associates
Regional steering
Training agency
Committee
Trade Board
Universities
Measures
Social partners
Venture Capitalists
Technology Consultants
Coordination
Local Cooperative Forum
Research Community
Local Government
Chambers of commerce
Source: Braczyk, Cooke and Heinreich, eds. (1998)
Policy Levers to Strengthen Local Innovation Systems
Creation & strengthening of
local networks
Encouraging local innovation
collaborations
Creation of bridging institutions
Ensuring openness of local
innovation system to sources of
knowledge outside system
Connectivities
Assets
Public investment in technology
development
Creation of S&T parks
Attracting inward investment
Supporting access to finance
Capabilities
Education & Training of individuals
Advice, training & consultancy to SMEs
Influencing motivation & abilities of universities &
Research organisations in collaborative research with SMEs
Comparison RIS & other Regional Models
Concepts
Definitions and differences
•
A concentration o f ‘interdependent’ firms within the same or adjacent
industrial sectors in a small geographic area
Regional
innovation
network
•
Increasingly organised co-operation (agreements) between firms, stimulated
by trust, norms and conventions
Regional
innovation
system
•
Co-operation between firms and different organisations for knowledge
development and diffusion
•
Increasingly organised co-operation with a broader set of civil organisations
and public authorities that are embedded in social and regional structures.
Regional
cluster
Learning
regions
Problems with Public Support for RIS

RISs are rare and newly discovered

Hard to detect systemic regional innovation

In Europe = high dependence on public expenditure
Source: Cooke (2001)
Problems with Public Support for RIS
RIS problems
Type of Problem
Typical problem region
Possible policy tools
Organisational
‘thinness’
Lack of relevant local
actors
Peripheral areas
Link firms to external recourses +
acquisition
Fragmentation
Lack of regional cooperation and
mutual trust
Some regional clusters
Develop regional ‘club goods’
Loc k-in
Regional industry
specialised in
outdated
technologies
Old industrial regions and raw
material based peripheral
Open up networks towards
external actors + local
mobilisation
Isaksen (2001)
Differences: National vs. Regional Systems
National Innovation
Systems
Regional Innovation
Systems
Inter-firm relations
- Market
- Clusters
Knowledge infrastructure
- Formal R&D laboratories
- National R&D
laboratories
- University research
- Firm external sources of
knowledge
Public Sector
(government)
- Emphasis on national
level
- Emphasis on regional
level
Financial institutions
- Formal savings
- Formal financial sector
- Venture capital
- Informal financial sector
Source: Acs (2002)
Case Study: Silicon Valley

A Region of 1500 Square Miles in California, US

One of the “most” innovative high-tech regions in the world

1.35 million jobs

Headquarters for over 400 public companies

Average salary of $65,000

Venture Capital Investments of over $8 billion
Source: Stanford University
“knowledge generation” in Silicon Valley (1)
Past:
 Linkages to Federal funding agencies and flood of Government Sponsored
Research at universities (Cold war effect in1950s)
Present:

Cutting-edge education to company employees

Small Business Innovation Research (SBIR) grants: Over $2B awarded in
U.S. in 2006
Source: Stanford University
“knowledge generation” in Silicon Valley (2)
Figure 5: Engineering School Ph.D. Production
180
160
140
120
100
Electrical
Ph.D. Total in Enginerring
80
60
40
20
81
80
19
79
19
78
19
77
19
76
19
75
19
74
19
73
19
72
19
71
19
70
19
69
19
68
19
67
19
66
19
65
19
64
19
63
19
62
19
61
19
60
19
59
19
58
19
57
19
56
19
55
19
54
19
53
19
52
19
19
19
51
0
Source: Stanford University
“knowledge Exploitation” in Silicon Valley

Stanford graduates, faculty & staff have launched approximately
1200 companies in the last 50 years

More than 50% of Silicon Valley product is due to companies started
by Stanford alumni
Source: Stanford University
Silicon Valley Innovations: Past & Present
Source: Stanford University
Some Silicon Valley companies
Conclusions

RIS consists of knowledge generation and exploitation subsystems

New focus of economic policy

Think local, act global - External links are important for RIS

RISs are rare and rely heavily on public expenditure
Some Preliminary Questions

Can/does higher education make a
difference?

Does it make a difference by itself or in
collaboration with other institutions?

Do small businesses interact with this
collaborative venture?
University Culture and
Entrepreneurship

What unites academics more? Car Parking or
intellectual discourse?

What price entrepreneurship?

“Loosely coupled systems” (Weick 1976)

Collegial academy of chaos

Four cultures of “collegium”, “bureaucracy”,
University Offerings versus Entrepreneurs’ Learning Needs
University/B-School Learning Focus
Critical judgment after analyzing large amounts
of information
Understanding and recalling the information
itself
Entrepreneurs’ Learning Needs
Gut feel decision making with limited
information
Understanding the values of those who
transmit/filter information
Assuming commonality of goals
Recognizing the widely varied goals of different
stakeholders
Seeking (impersonally) to verify the absolute
truth by study of information
Understanding the basic principles of the society
in the metaphysical sense
Seeking the correct answer, with (enough) time
to do it
Making decisions on the basis of judgment of
trust & competence of people.
Seeking to apply and adjust in practice to the
basic principles of society
Developing the most appropriate solution often
under time-pressure
Learning in the class room
Learning while & through doing
Gleaning information from experts and
authoritative sources for the sake of its
genuineness
Gleaning information from any and everywhere
& assessing its practical usefulness
Some Stylised Observations 1/2

Patterns of use of university (especially
research) output:

Economic stability = pure research; instability =
commercialisation

But note a few caveats:


a) Origins of university activity– industry focused
Technische Mittelschulen, Technische Hochschulen,
Fachhoschulen in Germany; USA – University of
Akron (polymers & elastomers), Cornell’s electrical
engineering dept.
Some stylised observations
2/2

Economic sectors with most rapid growth are closest
to science – microelectronics, software, biotech and
new materials.

Above industries also have high ‘social qualities’ –
high wages, good environmental characteristics, low
barriers to entry for small firms, relative
independence from geographic constraints

Universities benefit from government policy to
encourage entrepreneurship (licensed inventions
from govt. grants (Mowrey, Nelson & Sampat, 1999)

Real spur to entrepreneurship in universities =
business opportunity from basic science
The Forces At Work Regionalisation

New & diverse client bases for teaching & research

From traditional relationships with large corporations to
regional clusters of firms (not just money but changes in
nature & scope of technologies)

Regionalisation of regulating institutions leads to regional
networking & institutional capacity building

Universities as regional intermediaries & commentators

Regional networking as institutional survival
The Forces at Work – Forms of
Learning

New mode of learning production from
inter-disciplinary research centres &
reliance on external funding (Gibbon,
1994)

Interactive forms of learning inherently
bound in time & space – regional context
for learning & knowledge

International research transferred to
Forces at Work – The New
Culture

The new student – decentred world & multiple lives

Diverse forms of preparation

Episodic & fragmented engagement not holistic, intense, linear
forms of learning

Research generated in heterogeneous environments of producers,
brokers and users

Knowledge is more contextualised & intensely reflexive

Communicative culture – from cerebral, objective, codified &
symbolic (logos) to visual, intuitive, volatile, subjective

Wider social distribution of knowledge generation

(source: Scott, 2004)
The Knowledge Economy Factor
R&D, Universities, Small Firms, Skills Sets and
ICT
A Role For Learning, Research
and Higher Education;
Catalysts For An Entrepreneurial Culture?
The East of England