KIT Knowledge, Innovation and Territory

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, Politecnicodi 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. RaffaelePaci (Full Professor of Applied Economics) • Proff. EmanuelaMarrocu 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. JordiSuriñach (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. 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 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. A) Main spatial trends of innovation and knowledge B) Territorial elements explaining the spatial trends 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 Specific goals of the KIT project

7. A) Main spatial trends of innovation and knowledge B) Territorial elements explaining spatial trends 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 Specific goals of the KIT project

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 • productinnovation; • processinnovation; • product and/or processinnovation; • marketing and/or organisationalinnovation • environmentalinnovation • social innovation • Source: Regionalised data fromnationalCIS/ EUROSTAT source

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

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

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

17. R&D expenditures on GDP and innovation R&D expenditure / GDP Share 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 fewregionshaveachieved the 3% ofR&D/GDP, and most are below 0.5%. Only a fewregions show a pattern ofinnovationthatgoesfromR&Dtoinnovation. Questions: How do regions innovate withoutR&D? Which are the territorialpreconditions in orderforregionstomovefromknowledgetoinnovation and togrowth?

22. A) Main spatial trends of innovation and knowledge B) Territorial elements explaining spatial trends 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 Specific goals

23. 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

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

25. Region j Basic knowledge (General Purpose Technologies, GPTs) Education, human capital, accessibility, urban externalities Specific and applied knowledge Territorial creativity Region i Collective learning Product and process innovation Economic efficiency Specific and applied knowledge Capabilities Entrepreneurship 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

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

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. A) Main spatial trends of innovation and knowledge B) Territorial elements explaining spatial trends 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 Specific goals

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

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? Patents Innovation 0.05 Patents in: European Research Area 0.16 Knowledge Diversification Area 0.01 Smart Specialization Area 0.03 Innovation Smart Upgrading Diversification Area -0.04 -0.05 Creative Imitation Area

34. Does R&D expenditure generate increases in GDP growth rates? R&D GDP growth rate 0.05 R&D in: European Research Area 0.0023* Knowledge Diversification Area 0.0013* Smart Specialization Area 0.0009 GDP growth rate Smart Upgrading Diversification Area 0.0006 -0.0016 Creative Imitation Area * 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. A) Main spatial trends of innovation and knowledge B) Territorial elements explaining the spatial trends 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 Specific goals of the KIT project

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

40. Smart innovation policies: policy actions

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 muchfor your attention!