KIT Knowledge, Innovation and Territory

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, 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 (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. ERDF Reform 2009 - 2012 DG-Regio and ESPON 2006-2013 DG Research - 2009 Europe 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 General goal of the KIT project (2) The KIT project is at the heart of an important policy debate.

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. A) Main spatial trends of innovation and knowledge B) Identification of the regional pathways towards innovation and modernization and their territorial elements 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

9. A) Main spatial trends of innovation and knowledge B) Identification of the regional pathways towards innovation and modernization and their territorial elements 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

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 • productinnovation; • processinnovation; • product and/or processinnovation; • marketing and/or organisationalinnovation • environmentalinnovation • social innovation • Source: CIS/EUROSTAT

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

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

15. R&D expenditures on GDP and innovation R&D expenditure / GDP Share 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 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?

20. A) Main spatial trends of innovation and knowledge B) Identification of the regional pathways towards innovation and modernization and their territorial elements 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

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

22. 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

23. 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

24. 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

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 • Differentiated patterns of innovation and modernization, much more complex than a core-periphery model; • 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. A) Main spatial trends of innovation and knowledge B) Identification of the regional pathways towards innovation and modernization and their territorial elements 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 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 5 Pattern 4 Pattern 4 Pattern 3 Pattern 3 Pattern 2 Pattern 2 Pattern 1 Pattern 1

34. Do knowledge spillovers play a role in producing internal knowledge? Does innovation impact on employment growth rates? Intra-regional inventors’ mobility Inter regional inventors’ mobility • 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. 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). Elasticies of GDP Growth to Knowledge and 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 4 Pattern 3 Pattern 5 Pattern 2 Pattern 1

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. 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 Case studies

41. 12 case studies • 6 case case on best practiceofknowledgecreation: • - Electronics (Pisa, Tuscany) • Automotive in Piedmont • Biotech in Oxford • ICT in Cambridge • ICT in Kosice • ICT in Bratislava • 6 case studies on best practiceofknowledgeacquisition: • Wine in Tuscany area; • Wood processing in BanskaBystrica region • Digital media in Cardiff (Wales) • Foodsector in West Wales • ICT Milan (Lombardy) • Automotive in Bratislava region

42. Value added of the case studies Territorialelementsexplaininnovationpatterns more than the sectoralelements. Case studies have provided an in-depth analysis of the territorial elements behind patterns of innovation. Case studiesdemonstrated the dynamicsofregionsfromone pattern ofinnovationtoanother. Inductiveanalysiswitnessesthat the territorialelementssupporting the differentinnovationpatterns are thoseconceptuallyidentified.

43. 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

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

48. Smart innovation policies

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

50. Thank you very muchfor your attention!