1. KIT Knowledge, Innovation and Territory ESPON 2013 Programme European Territorial Evidence for EU Cohesion Policy and Programming 13-14 June 2012 Aalborg, Denmark

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 (1) The KIT project has the general aim to help – on the basis of sound scientific research – the setting up of strategies on innovation that are consistent with the overall reforms of EU Cohesion Policy. The KIT project provides suggestions for implementing smart specialization policies in the field of innovation - called for by the EU in its official document Regional Policy Contributing to Smart Growth in Europe (EU, 2010) - and to launch a territorial strategy to achieve a smart growth in the years to come.

5. General goal of the KIT project (2) The KIT project is at the heart of an important policy debate. ERDF Reform 2009 - 2012 DG-Regio and ESPON 2006-2013 DG Research - 2009Europe 2020 - 2010 Barca Report 2009 KIT Project Regional Patterns of Innovation 2011-12 Smart Specialization in R&D policies Smart Growth pillar Innovation Europe Flagship Initiative Smart Innovation Policies

6. General goal of the KIT project (3) The achievement of such a goal requires greater understanding of: -diffusion processes of knowledge and innovation; -the identification of the pathways towards innovation and modernization; -the socio-economic impacts of innovation and knowledge in space. Main result: the geography of innovation is much more complex than a simple core-periphery model. The identification of regional specificities in innovation patterns is essential to build targeted normative strategies efficient for a cohesion policy goal.

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

8. Specific goals of the KIT project B) Identification of the regional pathways towards innovation and modernization and their territorial elements 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

9. Specific goals of the KIT project B) Identification of the regional pathways towards innovation and modernization and their territorial elements 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

10. 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).

11. The 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.

12. 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: CIS/EUROSTAT

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

14. Share of innovation by type of knowledge-economy regions Product innovation Process innovation Product and/or process innovation Marketing and/or organization al innovation Household propensity to adopt innovation Environment al innovation TAR17,4213,7643,6632,75570,007 Scientific18,1613,4843,7129,51620,007 Networking16,1913,244,2431,95570,007 Other6,349,8827,420,58410,003

15. R&D expenditures on GDP and innovation R&D expenditure / GDPShare of firms introducing product and/or process innovation

16. 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?

17. Patenting activity: comparison with China and India

18. … 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 a European Research Area.

19. Results and 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?

20. Specific goals B) Identification of the regional pathways towards innovation and modernization and their territorial elements 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

21. 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 knowledge to innovation - from innovation to regional performance of knowledge and innovation

22. 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

23. 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

24. An imitative innovation pattern 5) An imitative innovation area Innovation imitation through territorial attractiveness PhasesTerritorial preconditions for knowledge creation Knowledge outputTerritorial preconditions for innovation InnovationEconomic 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

25. Territorial patterns of innovation Pattern 1= A European science-based area Pattern 2 = An applied science area Pattern 3 = A smart technological application area Pattern 4 = A smart and creative diversification area Pattern 5 = An imitative innovation area

26. Territorial conditions associated to each pattern Regional preconditions for knowledge and innovation creation Regional preconditions for external knowledge and innovation acquisition

27. Results and questions from the patterns identification 1.Differentiated patterns of innovation and modernization, much more complex than a core-periphery model; 2.our impression is that none of these patterns is by definition superior to another and, on the contrary, each territorial pattern may provide an efficient use of research and innovation activities generating growth. But this last statement calls for empirical analysis.

28. Specific goals B) Identification of the regional pathways towards innovation and modernization and their territorial elements 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 knowledge production to R&D expenditure? 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. Pattern 5 Pattern 1 Pattern 2 Pattern 4 Pattern 3

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

32. What is the return of knowledge production to human capital? Increasing returns up to a certain threshold, then decreasing returns. Elasticity is higher than for R&D. Pattern 5 Pattern 4 Pattern 1 Pattern 2 Pattern 3

33. What is the return of knowledge production to external knowledge ? Pattern 5 Pattern 4 Pattern 3 Pattern 2 Pattern 1 Pattern 5 Pattern 4 Pattern 3 Pattern 2 Pattern 1

34. Do knowledge spillovers play a role in producing internal knowledge? Intra-regional inventors mobilityInter regional inventors mobility Does innovation impact on employment growth rates? Map: Elasticity of employment growth to product innovation On average, product innovation is a labour saving activity but: - it creates jobs in regions where production functions are present (new products need to be produced)

35. Does R&D expenditure generate innovation?

36. Elasticies of GDP Growth to Knowledge and Innovation GDP growth (2005-2007) R&D on GDP Share of innovative firms Elasticity of GDP growth to R&D Elasticity of GDP growth to innovation EU average3.641.3735.540.120.38 European science-based area (ESBA) 3.292.5663.160.240.41 Applied science area (ASA)3.651.8446.920.150.49 Smart technological application area (STAA) 3.171.7138.430.160.26 Smart and creative diversification area (SCDA) 3.850.9727.690.100.22 Imitative innovation area (IIA) 4.20.4118.14Not significant Note: elasticity values to knowledge and innovation are computed according to the estimated coefficients reported in table 4. Elasticity values of GDP growth to knowledge are computed according to model 2 (EU average value) and model 4 (elasticity values by patterns of innovation). Elasticity values of GDP growth to innovation are computed according to model 6 (EU average value) and model 10 (elasticity values by patterns of innovation).

37. Does R&D expenditure generate GDP growth? Map: Elasticity of GDP to R&D by patterns A critical mass is required in order to achieve increasing returns (U- shaped form). Pattern 2 Pattern 1 Pattern 5 Pattern 3 Pattern 4

38. Do knowledge and capabilities increase TFP?

39. 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 Pattern 5 Pattern 4 Pattern 3 Pattern 2 Pattern 1

40. Case studies 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 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 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

41. 12 case studies 6 case case on best practice of knowledge creation: - Electronics (Pisa, Tuscany) - Automotive in Piedmont - Biotech in Oxford - ICT in Cambridge - ICT in Kosice - ICT in Bratislava 6 case studies on best practice of knowledge acquisition: - Wine in Tuscany area; - Wood processing in Banska Bystrica region - Digital media in Cardiff (Wales) - Food sector in West Wales - ICT Milan (Lombardy) - Automotive in Bratislava region

42. Value added of the case studies Territorial elements explain innovation patterns more than the sectoral elements. Case studies have provided an in-depth analysis of the territorial elements behind patterns of innovation. Case studies demonstrated the dynamics of regions from one pattern of innovation to another. Inductive analysis witnesses that the territorial elements supporting the different innovation patterns are those conceptually identified.

43. 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

44. Key policy messages (1) Unconventional policy warnings with regard to some general beliefs, namely: - an innovation-driven economy is not necessary linked to a knowledge economy; - formal knowledge is not the only knowledge asset on which a modern economy rests; -R&D expenditures are not the only policy tools to develop innovation and growth;

45. Key policy messages (2) - if a knowledge economy is developed, this does not give rise to the same growth opportunity everywhere; - external knowledge cannot easily and automatically be used in an efficient way by all regions. There is a clear need for thematically-regionally focused innovation policies.

46. Smart innovation policies Smart innovation policies may be defined as those policies able to increase the innovation capability of an area by boosting effectiveness of accumulated knowledge and fostering territorial applications and diversification, on the basis of local specificities and the characteristics of already established innovation patterns in each region.

47. Smart innovation policies Territorial patterns of innovation Policy aspects European science-based area (Pattern 1a) Applied science area (Pattern 1b) Smart technological application area (Pattern 2a) Smart and creative diversification area (Pattern 2b) Imitative innovation area (Pattern 3) Policy goalsMaximum return to R&D investments Maximum return to applications and co-operation in applications Maximum return to imitation Policy actions for local knowledge generation (Embeddedness) Support to R&D in:Support to creative application, shifting capacity from old to new uses, improving productivity in existing uses, through: Fast diffusion of existing innovation Enhancing receptivity of existing innovation New basic fields General Purpose Technologies Specialized technological fields Incentives to technological development and upgrading Identification of international best practices Support to search in product/market diversification Support to entrepreneurial creativity Support to local firms for complementary projects with MNCs Support to local firms for specialized subcontracting

48. Smart innovation policies Policy actions for exploitation of knowledge spillovers (Connectedness) Incentives to inventors attraction. Support of research cooperation in: Incentives for creative applications through:Incentives for MNCs attraction GPT and trans-territorial projects (ERA) specific technologies and trans-territorial projects (ERA), in related sectors/domains Encourage labour mobility among related sectors/domains Co-operative research activities among related sectors Co-operative search for new technological solutions participation of local actors to specialized international fairs attraction of star researchers even for short periods work experience in best practice knowledge creation firms of the same domains Bargaining on innovative local content procurement by MNCs Policy styleProvide a critical mass of funds Support triangular projects by Universities-Research Centres-Enterprises Stimulate knowledge and technological transfer mechanisms in related sectors Thematical/ regional orientation of R&D funding: Stimulate a bottom up identification of industrial vocations, by raising awareness on local capabilities and potentials, in order to: Stimulate cooperation projects between MNCs and local firms Towards researchers and laboratories in general purpose technologies in specific fields of technological specialization of the area targeted choice of joint research activities with partners external to the area Stimulate co-operation with strong external partners in the specialization sectors of the area Support local actors participation to international fairs in specialization sectors Support targeted work experiences in best practice knowledge creation firms BeneficiariesUniversity, research centers, large local firmsLocal firmsLocal entrepreneursLocal firms

49. Evolutionary smart innovation policies Creation of new local competences adding local value to external competences 3 2 1 5 Reinforcement of local applied science Diversification of technological fields in which to innovate New applications in new industries Reinforcement of local science-based knowledge 4 Elasticity of GDP to R&D R&D / GDP

50. Thank you very much for your attention!