CLUSTER & INNOVATION POLICIES IN AN OPEN CONTEXT

James R. Wilson

Competitive Territories in the Global EconomySession 8, Thursday 5th December 2013

Email: jwilson@orkestra.deusto.esTwitter: jamierwilson

Web: jamierwilson.wordpress.com

WHERE ARE WE?

TOPIC 1. Regional competitiveness and development in the international context.

TOPIC 2. Territorial development based on clusters and local production systems: concepts, drivers and indicators.

TOPIC 3. Typologies and trajectories of clusters and districts.TOPIC 4. Social capital in local and global economies.TOPIC 5. Clusters in global value chains and global production

networks.TOPIC 6. The relationship between clusters and innovation systems.TOPIC 7. The nature of innovation systems: concepts, actors and

typologies.TOPIC 8. The efficiency and effectiveness of innovation systems.TOPIC 9. Enterprise innovation modes.TOPIC 10. Cluster and innovation policies in an open context.

WHY POLICY?

Why do we need public policy for innovation?

OPENING THE BLACK BOX OF INNOVATION

• The economics of innovation was relatively neglected by economists until fairly recently

• One of the reasons is that it is hugely complex:– Simple models of mainstream economics cannot cope– Innovation as a dynamic form of learning

The fundamental impulse that sets and keeps the capitalist engine in motion comes from the new consumers’ goods, the new methods of production or transportation, the new markets, the new forces of industrial organisation that capitalist enterprise creates

Schumpeter (1943)

Information interdependencies Path dependenciesDifficult to foresee

the potential significance of innovations

Information-poor and highly uncertain environment

• ‘Technology’ defines the existing methods available to the firm to produce their goods and services

• The firm can be thought of as a ‘production function’:

• This productive relationship (f) defines the output (Q) that can be produced from given quantities of labour (L) and capital (K) given available methods– The production function defines a given technology

• Technology is a constraint, and innovation has the potential to enhance production

A MAINSTREAM ECONOMICS APPROACH

Q = f (K, L, … )

Technology as an exogenous factor (Solow, 1956)

Technology as an endogenous factor (Arrow, 1962)

Knowledge is seen as a ‘good’ produced by an agent in the market

THE MARKET FOR KNOWLEDGE

• Neoclassical economics assumes that markets are perfect – Many buyers and sellers– Complete information– Homogenous goods– Zero entry and exit barriers– Perfect factor mobility

• A complete and functioning set of perfect markets will in theory lead to efficient allocation of resources across the economy– Firms and consumers respond to market signals to adjust their behaviour

to the optimal, generating ‘equilibrium’

• The only justification for government interference (policy) is when there is an imperfection in the market: the market fails

The market for knowledge fails in three key respects, creating a rationale for innovation policy

1. UNCERTAINTY

Uncertainty in returns from investing in innovative activities

Absence of complete information & asymmetry of information between firms and financers

Implies a strong element of risk & dulls incentives, particularly in the early stages of the innovation process

Result: Sub-optimal knowledge creation

2. LACK OF APPROPRIABILITY

The nature of knowledge makes it difficult to appropriate all of the returns from an investment: there are externalities

Positive externalities and spill-overs from knowledge creation mean that:

Social Return > Private Return

Knowledge has public good features: - Non-rivalrous- Non-excludable

Result: Sub-optimal knowledge creation

3. INDIVISIBILITIES

There are often indivisibilities in innovation activities

There are often high costs in the initial phases of an innovation process

Result: Sub-optimal knowledge creation

Creates barriers to investment & bottlenecks:

Implies advantages from certain scale & critical mass

• In practice these three types of market failures interact with one another with the overall result of sub-optimal knowledge creation

• Policies are justified where they aims to address one or a combination of these failures, e.g.:

• Innovation policies responding to market failure rationales are therefore ‘resource-based’:– Aim to encourage firms to exploit innovation possibilities more

intensively than they otherwise would

THE RATIONALE FOR POLICY

R&D Subsidies Tax breaks

on R&D

Patent protection

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THE SYSTEMIC REVOLUTION

• Market failure rationales make sense when we consider innovation as a linear process:

• The last two decades have seen the rise of evolutionary perspectives that question the linearity of knowledge generation– The black box of innovation is much more complex– Innovation outcomes are determined by a range of factors within a

system of relationships

↑ Innovation Input

↑ Innovation Output

Hence alongside market failures we can also observe systemic problems that lead to ineffective and inefficient innovation

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EVOLUTIONARY PERSPECTIVES: KEY FEATURES

• Learning is the central concept– Different actors and institutions interact within systems to develop

and transfer new knowledge– Innovation requires forms of collective action for learning that varies

among sectors, firms and agents

• Basic tension between the processes of variety creation and selection

• No ‘optimum’ or ‘equilibrium’ to be reached• ‘Bounded rationality’ a central concept

This may call for actions contrary to conditions of perfect competition; for example, cooperation and collaboration between firms to facilitate knowledge flows, government regulation and the creation of incentives Smith (2000)

Failures (or problems) can occur within the system that provide obstacles to interaction and learning

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THE RATIONALE FOR POLICY

• Policy can seek to address problems with respect to:1. The components of the system2. The dynamics of the system

• Laranja et al. (2009) identify three groups of problems:– Network failures: when the exchange of knowledge in the system fails

for different reasons (actors are not well connected to the network or their learning process is not being the appropriate one)

– Institutional failures: when institutions, like organizations and legal, social and normative frameworks are not fostering and facilitating innovation processes

– Lock-in failures: when innovation systems are isolated from other systems, which hinders the adoption of new paradigms making innovation more difficult

Systemic rationales lend themselves to ‘softer’ policies that do not seek to optimise a specific ‘hard’ outcome. Rather they seek to enhance learning by shaping institutions and fostering interaction, networks, etc.

HISTORY OF STI POLICY• STI policy has evolved with theoretical rationales, but new

rationales and policies do not replace older ones

Policy for Science

(Post WW2):

* Aim: Growth of science itself

* Space race between US and USSR

* Resource based policy engaged to promote an excellent infrastructure

* Focused on universities, research institutions and public R&D laboratories

Science in Policy

(1970s & 1980s):

* Aim: Science to achieve technological objectives

* Rooted in previous successes of science policy in establishing research institutions

* Expansion of institutions & catch-up with US

* Influenced by linear innovation theories and three pillars of (i) basic research, (ii) development and (iii) diffusion

Innovation systems (from 1980s):

* Aim: Broad-based innovation and

competitiveness

* Criticism of narrow focus of previous policies

* Importance of generic factors & interactive process

of innovation

* Relationships as important as system components

* Growth of demand-oriented & relationship- oriented

policies

Key sources: Gibbons et al (1994); Gassler et al. (2008); Godin (2006); Edquist (2001)

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GENERAL TRENDS IN PUBLIC POLICY

• Processes of devolution: decentralisation of policy responsibility to sub-national levels– Industrial Policy vs Regional Policy

• Change of focus from targeted towards more systemic approaches to policy– From neoclassical to systemic rationales– Joined-up policy-making

• Larger implication of the private sector in the design and implementation of policies

• Classic examples are the evolution of innovation policies and the emergence of cluster policies

Policy complexity in a given policy space (e.g. a region) arises as a result of the policy mix and the different administrative levels from which policies originate

Mix of rationales

Mix of domains

Mix of instrumentsP

olic

y-M

ix D

imen

sion

Supra-national level

National level

Regional level

Local level

Mul

ti-le

vel D

imen

sion

Policy Space

Policy system

Source: Magro and Wilson (2012)

POLICY COMPLEXITY

Example: Regional Innovation Monitor

INNOVATION: SOME SPECIFIC POLICY INSTRUMENTS

• Patent system• Public provision of R&D• R&D subsidies/grants to firms• ‘Cluster’ policies that encourage co-operative R&D• Government procurement policy• FDI policy • Competition policy• Education and training policy• Defence policy• Policy towards standards/compatibility• Environmental regulation• ...

DISCUSSION QUESTIONS

How strictly should patent laws and intellectual property rights be enforced? Why? Is this ALWAYS the case?

Is public spending to support basic research likely to be beneficial for firm innovation? What might maximize its value?

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RECAP: CLUSTER CONCEPT

A cluster is a geographically proximate group of interconnected companies and associated institutions in a particular field, linked by commonalities and complementarities. Porter (1998)

• Various practical problems with this concept:– Agglomeration or cluster?– Relation to similar concepts?

• Industrial Districts• Innovative Milieu• New Industrial Spaces• Innovation systems• Networks• Etc.

– Types of agents included?– Geographical scope?

‘Chaotic’ concept, but commonly understood broad basis for policy:

1. Geographic proximity of agents in related industries

2. Hypothesised benefits from co-operative relationships among these agents, alongside competition

IDENTIFYING THE NEED FOR CLUSTER POLICY

• Three broad cluster policy scenarios can be identified:

Scenario Policy RationaleNo existing agglomeration

Questionable policy rationale, except in very specific circumstances (e.g. strategic positioning for smart specialisation)

Existing agglomeration but weak institutional elements

Policy can help to maximise cluster potential, but in a long term process that fits the existing socio-institutional context

Existing agglomeration and functioning institutional elements

Policy may generate benefits depending on the specific socio-institutional context, but there are greater dangers of crowding out

CLUSTER POLICY

• Most regions in Europe now have some form of cluster policy, and it is extremely popular the world over

Five Pillars of European Cluster Support

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BIRTH OF BASQUE CLUSTER POLICY

• At the beginning of the 1990s, the Basque Country was losing its traditional competitive advantages– The Basque Government contracted Monitor to analyse future

competitiveness– This study defined a number of ‘clusters’

• The Basque Government established a competitiveness programme supporting workgroups in 9 priority clusters– These defined improvement priority areas and action proposals in each case

• This dynamic process of interaction among various agents enabled the detection of gaps in the Basque economy

Process leading ultimately to the creation of new institutions under the framework of a defined cluster policy

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TRAJECTORY OF BASQUE CLUSTER POLICY

Launch (1990s):

* Concerns around Basque competitiveness & consultancy report in early 1990s

* Workgroups in 9 priority clusters

* Process leading to creation of cluster associations supported by a cluster policy

* Mixed private-public finance to cover the cost of the 10 resulting cluster associations

Consolidation (2000s):

* Strategic reflection about the policy

* Formalisation of policy mechanisms for the functioning of the public-private relationship

* Identification of three core working areas for the associations: quality, internationalisation and innovation

* Emergence of 2 further cluster associations

Adaption to New Realities (from 2010):

* New competitiveness plan (2010-2013)

* Changes in management and governance of the

cluster policy

* Evolution of the policy to incorporate new activities:

support for ‘pre-clusters’

* Establishment of an ‘inter-cluster’ initiative to

reflect on the synergies between the activities of

different clusters

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POLICY SUPPORT FOR CLUSTER ASSOCIATIONS

• Cluster policy mission: the improvement of competitiveness responding to strategic challenges through cooperation

• Associations are required to undertake a strategic plan every 3-4 years and annual action plans

• Government representatives attend association meetings, but in non-voting capacity

• Mix of private and public funding: up to €240,000 per cluster association in public funds

Cooperation groups

To capture and diffuse strategic information

To identify synergies

To put in order and evaluate

synergies

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Activity Cluster Association Creation Number of Members

Policy Support

Home Appliances ACEDE 1992 8 Basque Gov (Industry)

Automotive ACICAE 1993 130 Basque Gov (Industry)

Energy Cluster de Energía 1996 88 Basque Gov (Industry)

Aerospace HEGAN 1997 37 Basque Gov (Industry)

Maritime Foro Marítimo Vasco 1997 163 Basque Gov (Industry)

Machine Tool Manufacturers AFM 1992 86 Basque Gov (Industry)

Paper Cluster de Papel 1998 20 Basque Gov (Industry)

Environment ACLIMA 1995 82 Basque Gov (Industry)

Port of Bilbao UNIPORT 1995 144 Basque Gov (Industry)

Telecommunications GAIA 1996 240 Basque Gov (Industry)

Audiovisual EIKEN 2004 43 Basque Gov (Industry)

Transport and Logistics CLUSTERTIL 2005 88 Basque Gov (Transport)

Food Cluster de la Alimentación 2008 31 Basque Gov (Industry)

Graphic arts Sector Association 2009 34 Basque Gov (Industry)

Iron and Steel foundry Sector Association 2009 68 Basque Gov (Industry)

Biosciences Biobasque 2006/2009 25 Basque Gov (Industry)

Habitat HABIC 2009 70 Basque Gov (Industry)

Forging and Casting Sector Association 2009 16 Basque Gov (Industry)

Construction Sector Association 2010 56 Basque Gov (Industry)

Hand Tools Herramex 2010 28 Basque Gov (Industry)

Steel production Siderex 2010 64 Basque Gov (Industry)

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CLUSTER ASSOCIATIONS: SOME CHARACTERISTICS

• Common aim to increase the competitiveness of cluster members and the industry(s) in which the cluster acts

• A mix of ‘value chain clusters’ and ‘transversal clusters’

• Heterogeneity in size, level of association, types of members– Members mainly firms, but some training centres, technology centres

and other public institutions

• Membership criteria are usually confined to pertaining to the relevant sector(s) and paying a membership fee

• Short administrative structure– Cluster director and a small staff of technicians

• Most associations work in three principle areas of action:– Technology– Quality– Internationalisation

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ILLUSTRATION: HEGAN

• Development of a nascent Basque aerospace sector from 1960s– 1960s: SENER (engineering) became involved in space projects– 1980s: Development of ITP (engines) and GAMESA (aeronautics structures)

– 1990s: Major collaborative projects with ROLLS ROYCE and EMBRAER

• Birth of HEGAN– Early 1990s: Study under Basque Government Competitiveness Programme– From 1993: Informal collaboration between GAMESA AERONAUTICA, ITP,

SENER, INASMET (technology centres) and the UPV Engineering School– 1997: HEGAN formally founded with 3 leading companies and 12 suppliers

• HEGAN Today– 35 Members (32 firms and 3 Research/Technology Centres)– Strong diversification in products and clients: Customer base includes

Airbus, Boeing, Bombardier, EADS, Embraer, Eurocopter, GE and Rolls-Royce

Source: HEGAN (2008), Report 1997-2007

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ROLE OF HEGAN

• Aeronautics is a research-driven, investment intensive industry – Basque firms do not have the capacity to control the market– Co-operation between local firms and as risk-sharing partners with leading

international firms is vital

• HEGAN has worked to respond to strategic challenges through facilitating cooperation– Aeronautics Technologies Specialisation Course (Bilbao Engineering School

and the Aeronautics Engineers School in Madrid)– Quality committee and development of own quality standard: HEGAN 9000– Environmental Agreement with the Basque Government

• Corresponded with a time of success for the sector:– Today turnover of almost €1000m and employment of around 7000 – More than 3-fold increase since 1997

SUMMARY

• Innovation policy is a critical element of government’s attempts to foster competitive territories:– Innovation is an engine of competitiveness

• Innovation policy today is highly complex:– Many different rationales for innovation policy– Policy comes from several different policy domains and levels– Policy involves the use of many different instruments

• Clusters and the cooperation that they foster are a key source of innovation– Cluster policy is extremely popular and max mix together other

elements of innovation policy

• Take time to THINK!– Read all the questions carefully and decide which you are best placed

to answer• Before starting your answers, take a few minutes to PLAN how

you are going to answer – A well structured answer will show that you can think logically about a

topic and is likely to get you better marks– Without planning, it is very easy simply to ramble, and not answer the

actual question!• Make sure you do ANSWER THE QUESTION!

– Ask yourself what exactly the question wants you to do, and then relate what you know about the subject to the question

– Make sure that you integrate relevant THEORY into your answer• Try to bring your answers alive with EXAMPLES

– This shows the examiner that you can relate your knowledge to the real world, which is very important in a course such as this

TIPS FOR THE ASSESSMENT

and good luck with the assessment!

Eskerrik asko / Gracias / Thank you

Email: jwilson@orkestra.deusto.esTwitter: jamierwilson

Web: jamierwilson.wordpress.com