KIT Knowledge, Innovation and Territory

1. KIT Knowledge, Innovation and Territory ESPON 2013 Programme Internal Seminar Crossing Knowledge Frontiers - Serving the Territories 17-18 November 2010 Liege, Belgium

2. The project team • Lead Partner (LP):BEST, PolitecnicodiMilano, Italy: • Project Coordinator: Prof. Roberta Capello (Full Professor in Regional Economics) • Project Manager: Camilla Lenzi (Assistant Professor) • Prof. Roberto Camagni (Full Professor in Urban Economics) • UgoFratesi (Assistant Professor), and Andrea Caragliu (Post-Doc Fellow) • Project Partner 2 (PP2):CRENOs, University of Cagliari, Italy: • Prof. RaffaelePaci (Full Professor of Applied Economics) • Francesco Pigliaru (Full Professor of Economics) and Stefano Usai (Associate Professor of Economics) • Alessandra Colombelli (Post-Doc Fellow) • MatteoBellinzas (Research assistant) • Project Partner 3 (PP3): AQR, University of Barcelona, Spain: • Prof. Rosina Moreno (Full Professor in Applied Economics) • Prof. JordiSuriñach (Full Professor in Applied Economics) • Prof. Raúl Ramos (Associate Professor in Applied Economics) • Ernest Miguélez (Technical Researcher and PhD student)

3. The project team • Project Partner 4 (PP4):LSE, Great Britain: • Dr. RiccardoCrescenzi (Lecturer in Economic Geography) • Prof. Andrés Rodríguez-Pose (Professor in Economic Geography) • Prof. Michael Storper (Professor in Economic Geography) • Project Partner 5 (PP5): University of Bratislava, Slovakia: • Prof. Milan Buček (Full Professor in Regional Economics and Policy) • Dr. Miroslav Šipikal (Coordinator - Senior Lecturer) • Dr. Rudolf Pástor (Researcher) • Project Partner 6 (PP6):University of Cardiff, Great Britain: • Prof. Phil Cooke (Full Research Professor in Regional Economic Development) • Julie Porter (Coordinator – Senior Researcher/Lecturer) • Selyf Morgan (Researcher)

4. General Goal (1) To contribute to the understanding of: • diffusion processes of knowledge and innovation and • the socio-economic impacts of innovation and knowledge in space, • by identifying the different “territorial patterns of innovation” in Europe. • A territorial pattern of innovation is defined as a combination of context conditions and of specific modes of performingthe different phases of the innovation process.

5. General Goal (2) The generalphylosophyof the project is in linewith the wordsofDanutaHübner (2009): “Innovation is not considered as a linear process that starts with research, eventually leading to development, translated later into growth in the territories that have more capabilities. Instead, it is the product of a policy mix, including several bodies and stakeholders in which the territories, their specificities and conditions are paramount”.

6. General Goal (3) In our project: • -> we do not look for the territorial capabilities that allow territories (in general) to exploit innovation and knowledge; • -> instead, we look for territorial specificities (context conditions) that are behind different modes of performing the different phases of the innovation process through the identification of territorial patterns of innovation.

7. Requirements Requirements for achieving this goal: • a consistent database for the state of the art in innovation and knowledge; • comparison with the EU and national data; • identification of the most important inter-regional spillover mechanisms; • the identification of new development opportunities through innovation for Europe and its territories; • an inventive framework for a scientific answer to the policy questions.

8. A) Main spatial trends of innovation and knowledge. (both endogenous knowledge creation and flows from outside) Output: typologies of innovative regions WP 2.1 and 2.2 B) Territorial elements explaining spatial trends. Different modes of innovation and knowledge creation and diffusion. A comparison with other regional knowledge economies in more advanced and emerging countries Output: typologies of territorial patterns of innovation WP 2 3.1 and 2.5 C) Impact of the different modes of innovation and knowledge on regional performance. Output: typologies of regional performance based on innovation and knowledge WP 2.3.2 D) Case studies WP 2.4.1 and 2.4.2 E) Policy implications for the development of a successful knowledge economy WP 2.6 Structure of the project

9. A) Knowledge Economy and itsSpatialTrends(I) Basic idea: knowledge-based economy has not got a unique interpretative paradigm. Different approaches are necessary: • A1. Sectoralapproach(presence in the region of science-based, high-technology sectors). • A2. Functional approach(presence in the region of functions like R&D and high education). • A3. Relation-based approach(presence in the region of interactive and collective learning processes).

10. A) Knowledge Economy and itsSpatialTrends(II) Spatialelementsmatter: • high-technology firms cluster along valleys, corridors, glens and high-tech districts to exploit the innovative atmosphere (technologically advanced regions); • high-education and research functions cluster in space since physical proximity acts as a driver of knowledge (scientific regions); • geographical areas characterised by cognitive proximity (shared behavioural codes, common culture, mutual trust and sense of belonging) show wider collective learning processes (networking regions).

11. A1) The sectoralapproach: a typology Specialisation in HT manufacturing HT manufacturing Technologically Advanced Regions (TAR) Specialisation in HT services EU average Low tech regions HT services

12. A1) The sectoral approach • Indicators to be collected and computed: • Regional specialization in HT manufacturing • As measured by employment in HT manufacturing according to Eurostat definition • Regional specialization in HT services • As measured by employment in knowledge intensive HT services according to Eurostat definition • Source: Eurostat

13. A1) The sectoralapproach High-tech services High-tech manufacturing

14. A1) The sectoral approach: a typology

15. A2) The functionalapproach: a typology Research activities Research intensive regions Scientific regions Human capital EU average Regions with other specialisations than R&D Human capital intensive regions

16. A2) The functionalapproach • Indicatorstobecollected and computed: • Researchand development • Expenditures; Expenditure as share of GDP; Expenditures per capita (1000 inhab.), • Personnel in R&D as share of total employment • Sources: Eurostat, ISTAT, Institut National de la Statistique et des ÉtudesÉconomiques • Patents • Number of patents; Patents per capita; Patents per capita percentage variation • Source: OECD REGPAT • Humancapital • Share of population with degree (ISCED 5-6) • Source: Eurostat • Fifth Framework Program • Participations; Funding; Funding per capita (Source: CORDIS)

17. A2) The functionalapproach: Human capital

18. A2) The functionalapproach: R&Dexpenditures

19. A2) The functionalapproach: Patents per capita

20. A3) The relational approach: a typology Spatial approach Localised knowledge spillovers regions Cooperative neighbouring regions e.g. collaboration in research projects among local actors e.g. knowledge spillovers Unintentional relationship Intentional relationship Formal networking regions Informal networking regions e.g. scientific associations e.g. collaboration in research projects A-spatial approach

21. A3) The relationalapproach Possibleindicatorstobecollected and computed: • Participations in the 5°FP projects in the neighbouring regions • Average funding in the 5°FP in the neighbouring regions • Average funding (per capita over total population) in the 5°FP in the neighbouring regions • Product+process innovations developed by other regions discounted by distance • Number of patent citations on total patents • Number of in-migrant and out-migrant inventors on total population • Number of co-patents on total patents • Sources: OECD - REGPAT, Cordis (Crenos elaboration)

22. A3) The relationalapproach: Knowledge spillover regions

23. A4) Spatialtrendsofinnovation in Europe • Indicatorstobecollected and computed: • Innovation • Technologicalinnovation • Productinnovation • Processinnovation • Marketing and/or organisationalinnovation • Adoption • Innovationadoption • Productinnovationadoption • Processinnovationadoption • Source: CIS/EUROSTAT

24. A) Spatialtrendsofinnovation in Europe Productinnovation Technologicalinnovation

25. A) Spatialtrendsofinnovation in Europe Processinnovation Marketing and org. innovation

26. A) Spatialtrendsofinnovation in Europe Facing some statistical difficulties at NUTS 2 • Official NUTS2 data available in a few countries • Product innovation only and process innovation only available for IT and RO • Product innovation and process innovation available for CH, CZ, DK, PL, UK (NUTS1) • RIS data (DG Enterprise, JRC and MERIT) and Regional Innovation Potential (DG Regio) to be checked and validated further. ESPON contact points have already been involved.

27. A) Social innovationadoption and use on-line orders broadband penetration rate

28. A) Environmentalinnovation

29. A5) Comparisonwith US, China and India • Innovation • Patents (source: OECD - REGPAT) • R&D (sources: Standard & Poor’s Compustat for US; China Statistical Yearbook on Science and Technology: Ministry of Science and Technology, Govt. of India) • Social Filter • Education: bachelor’s, graduate or professional degrees • Education: college level education • Agricultural Labour Force • Unemployment Rate • Young People • Sources: US-Census data; Chinese statistical resources website, National Bureau of Statistics of China; Ministry of Labour, Govt. of India, Central Statistical Organization (CSO), Census of India • Structure of the local economy • Domestic migration • Population density • % regional of national GDP • Krugman index of specialisation • Sources: US-Census data; Chinese statistical resources website, National Bureau of Statistics of China; Ministry of Labour, Govt. of India, Central Statistical Organization (CSO), Census of India

30. A5) Top 20 performers in US, China and India (patents on population)

31. B) Territorial patterns of innovation • A territorial pattern of innovation is a combination of context conditions and of specific modes of performingthe different phases of the innovation process. • Context conditions: • Internal generation • External attraction • Different phases of the innovation process: • - from information to knowledge • - from knowledge to innovation • - from innovation to regional performance of knowledge and innovation

32. B1) A totally endogenous innovation pattern Education, human capital, accessibility, urban externalities Collective learning Tacit knowledge Codified knowledge Product and process innovation Best practice governance Economic efficiency REGION I Entrepreneurship

33. B2) An endogenous innovation pattern in a dynamic area REGION J Education, human capital, accessibility, urban externalities Territorial accessibility Physical proximity Territorialpreconditions for interregional knowledge flows and innovation diffusion Collective learning Tacit knowledge Codified knowledge Product and process innovation Best practice governance Economic efficiency REGION I Entrepreneurship

34. B3) An endogenous innovation pattern in a scientific network REGION J Tacit knowledge Codified knowledge Education, human capital, accessibility, urban externalities Territorial receptivity Territorial relational capital Collective learning Tacit knowledge Codified knowledge Territorialpreconditions for interregional knowledge flows and innovation diffusion Product and process innovation Best practice governance Economic efficiency Education, human capital, accessibility, urban externalities REGION I Entrepreneurship

35. B4) An exogenously driven innovation pattern REGION J Tacit knowledge Education, human capital, accessibility, urban externalities Codified knowledge Territorialpreconditions for interregional knowledge flows and innovation diffusion Territorial creativity REGION I Best practice governance Product and process innovation Economic efficiency

36. B5) An imitative pattern of innovation REGION J Tacit knowledge Collective learning Product and process innovation Education, human capital, accessibility, urban externalities Codified knowledge Entrepreneurship Territorialpreconditions for interregional knowledge flows and innovation diffusion Territorial attractiveness REGION I Best practice governance Product and process innovation Economic efficiency

37. B6) An integrated innovation pattern REGION J Collective learning Product and process innovation Education, human capital, accessibility, urban externalities Tacit knowledge Codified knowledge Entrepreneurship Territorialpreconditions for interregional knowledge flows and innovation diffusion Education, human capital, accessibility, urban externalities Territorial relational capital Collective learning Territorial creativity Territorial attractiveness Best practice governance Product and process innovation Territorial receptivity Economic efficiency REGION I Tacit knowledge Entrepreneurship Codified knowledge

38. C) Impact of innovation and knowledge on regional growth • This WP will identify: • the role of innovation and knowledge on the performance of different territories; • the return of investments in regional innovation and knowledge in different territories; • the role of knowledge spillovers in the economic performance of different territories.

39. D) Case studies • 2 case studies per PP on regional best practices in knowledge creation • 2 case studies per PP on regional best practices in knowledge spillovers • Overall 12 case studies • Regions selection according to two dichotomies (see the next slide): • Concentrated vs diversified • Traditional vs advanced • Aim of the case studies: • - to strengthen the role of territorial elements in knowledge and innovation creation and knowledge spillovers according to the conceptual framework used in the project of territorial pattern of innovation • - to highlight the governance elements related to knowledge and innovation diffusion • Knowledge spillovers among regions and not only within regions • Agreement on the interview protocol, target groups of the planned interviews and selection process of the interviewees (to be provided in the Interim Report)

40. D) Case studies

41. E) Policy recommendations • The aim of the project is to produce policy recommendations on the achievement of a “smart growth” for Europe, intended as an economic growth based on knowledge and innovation. • In “EU2020” this priority rejects a “one size fits all approach”. • Recommendations in this field have to: • be tailored on each “territorial pattern of innovation” • be based on specific policy interventions • reinforce territorial preconditions that strengthen each innovation pattern in terms of economic performance.