1. KIT Knowledge, Innovation and Territory ESPON Workshop at the Open Days 2012 Creating Results informed by Territorial Evidence 10 October 2012 Bruxelles, Belgium

2. The project team Lead Partner (LP): BEST, Politecnico di Milano, 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) Dr. Andrea Caragliu (Post-Doc Fellow) Project Partner 2 (PP2): CRENOs, University of Cagliari, Italy: Prof. Raffaele Paci (Full Professor of Applied Economics) Proff. Emanuela Marrocu and Stefano Usai (Associate Professors of Econometrics and Economics) Dr. Alessandra Colombelli (Post-Doc Fellow) Dr. Marta Foddi (Research Assistant) Project Partner 3 (PP3): AQR, University of Barcelona, Spain: Prof. Rosina Moreno (Full Professor in Applied Economics) Prof. Jordi Suriñach (Full Professor in Applied Economics) Prof. Raúl Ramos (Associate Professor in Applied Economics) Dr. Ernest Miguélez (Technical Researcher and PhD student)

3. The project team Project Partner 4 (PP4): LSE, Great Britain: Dr. Riccardo Crescenzi (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 Economics in Bratislava, Slovakia: Prof. Milan Buček (Full Professor in Regional Economics and Policy) Dr. Miroslav Šipikal (Coordinator - Senior Lecturer) Dr. Rudolf Pástor (Lecturer) Project Partner 6 (PP6): University of Cardiff, Great Britain: Prof. Phil Cooke (Full Research Professor in Regional Economic Development) Dr. Selyf Morgan (Researcher) Julie Porter (Support Coordinator)

4. General goal of the KIT project To contribute to the understanding of: -diffusion processes of knowledge and innovation and -the socio-economic impacts of innovation and knowledge in space,  in order to identify the best innovation policies to foster a “smart Europe”.

5. Main ideas throughtout the project -R&D (and formal knowledge in general) does not necessarily equal innovation; -Knowledge and innovation do not necessarily equal regional growth.  these linkages are strongly mediated by local territorial assets.

6. Specific goals of the KIT project B) Territorial elements explaining the spatial trends A) Main spatial trends of innovation and knowledge C) Impact of the different modes of innovation and knowledge on regional performance D) Case studies E) Policy implications for the development of a successful knowledge economy

7. Specific goals of the KIT project B) Territorial elements explaining spatial trends A) Main spatial trends of innovation and knowledge C) Impact of the different modes of innovation and knowledge on regional performance D) Case studies E) Policy implications for the development of a successful knowledge economy

8. Definition of the Knowledge Economy Basic idea: knowledge-based economy has not got a unique interpretative paradigm. Different approaches are necessary: A1. Sectoral approach (presence in the region of science-based, high-technology sectors). A2. Functional approach (presence in the region of functions like R&D, patents, human capital). A3. Relation-based approach (presence in the region of interactive and collective learning processes).

9. Technologically Advanced Regions in EU In 2007 technologically advanced regions, hosting both high-tech manufacturing industries and KIS, are the minority of regions. Moreover a relatively high number of regions are specialised in low- tech sectors.

10. Scientific regions In 2007 scientific regions, hosting both human capital and research and activities functions, are limited. What is even more striking is the high number of regions with no specialisation in knowledge activities.

11. Knowledge networking regions In 2007 there were quite a number of networked regions, both un-intentional (spatial) and intentional (non necessary spatial). Non-networked regions are especially poor and peripheral areas. External sources of knowledge acquisitions are diffused all over Europe.

12. Knowledge Economy in Europe The Knowledge Economy in Europe is a very fragmented picture. What is striking from this map is the high number of regions in which the knowledge economy is still in its infancy.

13. Spatial trends of innovation in Europe Innovation product innovation; process innovation; product and/or process innovation; marketing and/or organisational innovation environmental innovation social innovation Source: Regionalised data from national CIS/ EUROSTAT source

14. Spatial trends of innovation in Europe Product innovation onlyProcess innovation only

15. Spatial trends of innovation in Europe Product and/or process innovationMarketing and organizational innov.

16. Share of innovation by type of knowledge-economy regions

17. R&D expenditures on GDP and innovation R&D expenditure / GDPShare of innovating firms

18. R&D expenditures on GDP (average 2006-07) In 2007 33 regions had achieved 3% of R&D expenditures on GDP (11% of NUTS2, representing 16% of EU GDP) and concentrated in a few countries in the North of Europe. Moreover, a very high number of regions belong to the lowest class, with R&D on GDP lower than 0.5% (representing 5% of GDP). Do we really take advantage from an innovation policy with a common aim for all countries/regions?

19. Patenting activity: comparison with China and India

20. … and USA The spatial concentration of R&D in order to exploit economies of scale seems to be the model followed by emerging countries, re- launching in a decisive way the debate of the importance of the identification of an European Research Area.

21. Results ad questions from the descriptive analysis Results: Only a few regions have achieved the 3% of R&D/GDP, and most are below 0.5%. Only a few regions show a pattern of innovation that goes from R&D to innovation. Questions: How do regions innovate without R&D? Which are the territorial preconditions in order for regions to move from knowledge to innovation and to growth?

22. Specific goals B) Territorial elements explaining spatial trends A) Main spatial trends of innovation and knowledge C) Impact of the different modes of innovation and knowledge on regional performance D) Case studies E) Policy implications for the development of a successful knowledge economy

23. Territorial patterns of innovation A territorial pattern of innovation is a combination of context conditions and of specific modes of performing the 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

24. An endogenous innovation pattern 1)A European science-based area: basic general purpose technologies 2) An applied science area: high patent activities in diversified applied technology fields PhasesTerritorial preconditions for knowledge creation Knowledge outputTerritorial preconditions for innovation InnovationEconomic efficiency Specific, applied knowledge Education, human capital, accessibility, urban externalities Territorial receptivity Cross-regional cognitive proximity relational capacity Basic knowledge (General Purpose Technologies, GPTs) Collective learning Entrepreneurship Product and process innovatio n Economic efficiency Basic knowledge (General Purpose Technologies, GPTs) Specific, applied knowledge Education, human capital, accessibility, urban externalities Basic knowledge (General Purpose Technologies, GPTs) Specific, applied knowledge Region j Region i Territorial receptivity

25. A creative application pattern 3) A smart technological application area External specific technologies enhancing the upgrading of local innovation 4) Smart and creative diversification area External tacit knowledge enhacing local innovation PhasesTerritorial preconditions for knowledge creation Knowledge outputTerritorial preconditions for innovation InnovationEconomic efficiency Product and process innovation Economic efficiency Collective learning Entrepreneurship Specific and applied knowledge Capabilities Territorial creativity Basic knowledge (General Purpose Technologies, GPTs) Specific and applied knowledge Region j Education, human capital, accessibility, urban externalities Region i

26. An imitative innovation pattern 5) An imitative innovation area Innovation imitation through territorial attractiveness PhasesTerritorial preconditions for knowledge creation Knowledge outputTerritorial preconditions for innovationInnovationEconomic efficiency Education, human capital, accessibility, urban externalities Product and process innovatio n Economic efficiency Specific and applied knowledge Territorial attractiveness: FDIs Product and process innovatio n Collective learning Entrepreneurship Region i Basic knowledge (General Purpose Technologies, GPTs) Region j

27. Territorial patterns of innovation Pattern 1= European research area Pattern 2 = Knowledge diversification area Pattern 3 = Smart specialization area Pattern 4 = Smart upgrading diversification area Pattern 5 = Creative imitation area

28. Specific goals B) Territorial elements explaining spatial trends A) Main spatial trends of innovation and knowledge C) Impact of the different modes of innovation and knowledge on regional performance D) Case studies E) Policy implications for the development of a successful knowledge economy

29. Selected questions to be answered Knowledge input (R&D) Knowledge outputInnovation Productivity growth GDP growth Employment growth 3.1 3.3 3.2 4.1 4.3 4.4 4.2 Migration of inventors Research collaborations

30. What is the return of R&D expenditure to knowledge production? Map: Elasticity of knowledge production to R&D The return of R&D expenditure to knowledge production increases by increasing R&D expenditure up to a certain level, then it starts decreasing.

31. Elasticity of knowledge production to R&D: an international comparison

32. Do knowledge spillovers play a role in producing internal knowledge? Map: Elasticity of knowledge production to inventors mobility Map: Elasticity of knowledge production to research networks

33. Does formal knowledge create innovation? PatentsInnovation 0.05 Creative Imitation Area Smart Specialization Area Knowledge Diversification Area European Research Area Smart Upgrading Diversification Area Innovation -0.04 0.03 -0.05 0.16 0.01 Patents in:

34. Does R&D expenditure generate increases in GDP growth rates? R&DGDP growth rate 0.05 Creative Imitation Area Smart Specialization Area Knowledge Diversification Area European Research Area Smart Upgrading Diversification Area GDP growth rate 0.0006 0.0009 -0.0016 0.0023* 0.0013* R&D in: * Significant at conventional level

35. Does innovation generate increases in GDP growth rates? Yes, but if innovation achieves a critical mass! Imitative innovation generates lower GDP growth rates than new innovation

36. Specific goals of the KIT project B) Territorial elements explaining the spatial trends A) Main spatial trends of innovation and knowledge C) Impact of the different modes of innovation and knowledge on regional performance D) Case studies E) Policy implications for the development of a successful knowledge economy

37. ‘Smart innovation’ policies: definition ‘Smart innovation’ policies may be defined as: those policies able to increase the innovation capability of an area by boosting effectiveness of accumulated knowledge, fostering new applications and diversification, enlarging and deepening the local knowledge base, starting from local specificities and the established innovation patterns in each region.

38. ‘Smart innovation’ policies: goals, actions and styles Smart innovation policies adapt the two policy actions of the S3 – embeddedness and connectedness – to each Territorial Pattern of Innovation, differentiating for each pattern the policy goals to be achieved, and highlighting crucial policy styles to be adopted for their implementation.

39. ‘Smart innovation’ policies: policy goals Territorial patterns of innovation Policy aspects European science-based area (Pattern 1) Applied science area (Pattern 2) Smart technological application area (Pattern 3) Smart and creative diversification area (Pattern 4) Imitative innovation area (Pattern 5) Policy goals Maximum return to R&D investments Maximum return to applications and co-operation in applications Maximum return to imitation and diffusion

40. Smart innovation policies: policy actions Territorial patterns of innovation Policy aspects European science-based area (Pattern 1) Applied science area (Pattern 2) Smart technological application area (Pattern 3) Smart and creative diversification area (Pattern 4) Imitative innovation area (Pattern 5) Policy actions for local knowledge generation (Embeddedness) Support to R&D following local specificities - GPTs (pattern 1) - Specialized techn. (pattern 2) Incentives: -to technological upgrading and local networks (pattern 3) - to local creativity and identification of int.al best practices (pattern 4) Fast diffusion of existing innovation Policy actions for exploitation of knowledge spillovers (Connectedness) Incentives to inventors attraction and mobility according to local specificities Support of research cooperation according to local specificities Incentives for creative applications through: co-operative research activities among related sectors (pattern 3) attraction of “star” researchers even for short periods (pattern 4) Incentives for MNCs attraction and embeddedness in the local area

41. Evolutionary smart innovation policies -Some regions could be able to ‘jump’ over different and more complex innovation patterns (empirical evidence collected); -‘evolutionary’ policies could support these paths, with extreme attention and careful assessments, provided that context conditions and reliability of actors and strategies/projects could reduce risks of failure.

42. Thank you very much for your attention!