Lessons from EU experience: Cluster policies and Innovation Policy Governance

1. Seventh Annual MeetingInnovation Systems Research Network Toronto, 5-6 May 2005 Clusters, Cluster policies and Innovation Policy Governance: Lessons from EU experience Claire Nauwelaers MERIT, Maastricht University (the Netherlands)

2. Back to the quest for roots of “success” of “places” • Generalised awareness of the role of innovation as crucial ingredient for economic development • Interactive view of innovation - innovation differs from R&D – role of framework conditions • System-based approach to innovation, emphasis on learning and diffusion / absorption of knowledge • Mobility of tacitknowledge embedded in humansbecomes a key performance factor – « talent » • Glocalisation : localised nature of (tacit) knowledge spillovers - importance of global connections

3. Positive relation between regions’ innovation and economic performance www.trendchart.org

4. The Innovation System (encompasses “triple helix”, “four pillars”) Innovation policy Incubators, Mentoring… Public R&D Firms system Large, small, MNCs, NTBFs, … Intermediaries MARKETS Human capital Training & Education Business support Venture Capital Rules & Regulations Framework conditions

5. Policies for innovation systems From “stocks” to “flows” as main focus of policy attention • Flows in the system need to be addressed in priority From “raising resources” towards “promoting change” • Performance is affected by learning abilities of firms and others From “best practice” towards “context-specific” solutions • Policies should be fine-tuned to specific system failures From “standard” policy-making towds policy “learning process” • There is a need for more strategic intelligence in policy-making

6. Cluster policies : trials towards systemic innovation policies • Cluster concept : variations around core idea of agglomeration and interaction benefits • Specific focus on the organisational aspect • Most successful forms of clusters : those that open new window of opportunities and cause changes ininnovationbehaviour – learning • Public authorities become part of the system

7. The real nature of Cluster policies Cluster policies = efforts to improve policy interfaces • Rather than a new policy area Cluster policies = finding the right mix of instruments • Originating from technology, industrial or regional policy toolboxes Clusters as means to reach goals, rather than ends • This makes evaluation of success absolutely critical

8. A simple typology of cluster policies

9. Main characteristics of cluster policies in the EU • Most countries are engaged in some sort of cluster policy • Explicit or implicit policies • Originate from technology, industrial or regional policies (path dependency) • Different targets • Variety in portfolio of instruments, borrowed from parent policy areas, tailor - made mix • From top-down to bottom-up • Different levels of intervention • Various entry points in an idealised sequence for policy design : mapping – selection – initiation – growth support – exit • European dimension : in infancy Variety in cluster policy models

10. The versatility of the Cluster concept Mega-Clusters Local Networks Knowledge-based

13. Notion of Cluster « success » vary Mega-Clusters : « Competitiveness » Local Networks : « Thickness » Knowledge-based : « Innovation »

14. State-of-the art in cluster evaluation Cluster evaluation : in infancy. Interest in cluster « per se » • Cluster benefits often taken for granted rather than analysed Cluster policy evaluation : need to question additionality • Finland has not developed an ICT cluster policy… Ex-ante assessment more developed than ex-post evaluation • Empirical techniques seldom used in policy evaluation High focus on localized linkages demonstration • Often disappointing: clusters = local nodes in global networks Neglect of competition as a main driving force • Major focus on cooperative and supply-chain relationships

15. Future of cluster policies Understand position of clusters in their life-cycle • From emergence to growth to maturity and decline Focus on innovative combinations of activities (cluster v. sector) • Empirical methods (e.g. location quotient) useful but not sufficient Analyze untraded interdependencies (innovation, social capital, talent…) • Analyzes based on input-output tables fail to measure this Define functional regions (cfr. German networks of excellence) • From firm dynamics rather than political boundaries Examine external and internalconnections (Italian Industrial districts) • A combination of both is necessary for clusters’ success Assign clear goals to policy (cfr. The Netherlands) • Success should be measured against expected benefits

16. Key challenges for cluster evaluation • Concentrate evaluations on clustering processes and trajectory rather than on static measures • FDI, firms displacement and creation,... • People mobility, employment growth • Role of key actors or events • Focus evaluations on immaterial flows rather than material flows • Innovations, technology licensing, patents citations,...(realm of innovation policy) • Managerial skills, entrepreneurial skills,… (realm of human resource policy)

17. Regional Innovation Policy :The way forward • Government’s role shifts from investor to facilitator - promotion of public/private partnerships and interface management • Improving knowledge governance in firms and clusters of firms becomes a key issue for policy • Policies need to "open borders" : between : • traditional fields of policy intervention • industries traditionally defined • various forms of knowledge production and diffusion

18. Regional Innovation Policy :The way forward • Danger of fragmentation of innovation policy : need for intra-government policy coordination • Increasing role of regions for innovation : need for vertical policy coordination • More efficiency through “Policy packages” rather than isolated instruments • Need for more policy intelligence • monitoring and evaluation of policies • sound analyses of innovation systems • « intelligent » benchmarking practices – no « best practices » ! • long term views • inclusive policy design processes