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Regional Innovation Systems approach to regional innovation

Regional Innovation Systems approach to regional innovation

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Regional Innovation Systems approach to regional innovation

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  1. Regional Innovation Systems approach to regional innovation Professor Bjørn Asheim, Director, CIRCLE (Centre for Innovation, Research and Competence in the Learning Economy), Lund University, Sweden. Lecture at NORSI PhD course on ‘Innovation Systems, Clusters and Innovation Policy’, University of Agder, Kristiansand, October 23rd 2012

  2. C I R C L E Centre for Innovation, Research and Competence in the Learning Economy

  3. Innovation as a progressive force • Productivity growth (process innovation) • More value added production (product) • Smarter ways of doing things (organisational) In a globalising knowledge economy: • Secure growth (developed economies) • Promote growth (developing economies) • Enable growth (less developed economies) Strategic mechanism for solving societal problems (growth, poverty, environemtal, ageing)

  4. Innovation as a progressive force • Innovation represent ’the high road strategy’ that is the only long-term, sustainable growth alternative for developed, high-cost economies as well as for developing economies • Innovation is not only R&D in high-tech industries (linear model), but can take place in all kinds of economic activities (interactive process - broad based innovation policy)

  5. Theoretical perspectives: Marx • Marx: Innovation represents the civilisational (i.e. dynamic/progressive) tendencies of capitalism • Caused by the two main contradictions: • Capital – labour (Nordic trade unions’ wage demands forcing capitalists to innovate) • Between capitals (high road strategy) It is not innovation that is the cause of the economic and financial crisis but lack of control of the repressive tendencies of capitalism (i.e. its unregulated development of e.g. the financial sector – deregulation/liberalisation)

  6. Theoretical perspectives: Schumpeter • Schumpeter defined innovation as ’new combinations’ of existing knowledge. • He argued that innovation was the source of economic and social change. Without such innovation, resulting from the activities of entrepreneurial individuals and firms (contradictions between capitals), society would be stagnant

  7. Theoretical perspectives: Innovation systems • OECD work in 1982 (’Science, Technology and Competitiveness’) developing an alternative to mainstream, static economic’s view on international competitiveness as based on ’relative wages’ (i.e. the ’low road’ strategy). • Instead a dynamic perspective on innovation and learning in the promotion of economic growth with an active role of government stimulating learning and innovation was proposed (i.e. the ’high-road’ strategy). • Innovation at the centre of economic growth • IS both selection environments (shaping selection processes) and sources of new variety creation (shaping creativity)

  8. Economic performance: Global competitiveness report (World Economic Forum) 2005 2008 2009 2010 2011 2012 • Finland: 1 6 6 7 4 3 • Sweden: 3 4 4 2 3 4 • Denmark: 4 3 5 9 8 12 • Norway: 9 16 14 14 16 15 • Spain: 36 • Italy: 42 • Portugal: 49 • Greece: 96

  9. Innovation Systems and R&D(OECD Science, Technology and Industry Scoreboard 2011) • Promoting Innovation Systems approach: • Finland: Science and Technology Policy Council (now renamed as Research and Innovation Council) and TEKES • Sweden: VINNOVA (Swedish Governmental Agency for Innovation Systems) • R&D as share of GDP (2011), Researchers per 1000 • Finland 4.0% 16.6 • Sweden 3.6% 10.5 • Denmark 3.0% 12.3 • Norway: 1.8% 10.1

  10. Origins of the innovation system approach • Lundvall, Aalborg university: Work during the last part of 1980s (also with Freeman). Edited book from 1992 on ’National Systems of Innovation: Towards a theory of innovation and interactive learning’ • Nelson, Colombia university. Edited book from 1993 on ’National Innovation Systems: A Comparative Analysis’ • Edquist: Edited book from 1997 on ’Systems of Innovation: Technologies, Institutions and Organizations’

  11. Varieties of innovation systems • ’Technological’ systems (Carlsson and Stankiewicz, 1995) • ’Sectoral’ systems (Malerba, 1997) • ’Regional’ systems (Cooke, 1992; Asheim 1995) • Some of the crucial ideas of the IS concept such as vertical interaction and innovation as an interactive process appear in Porter’s cluster concept (1990/98) and the Triple-Helix model of Etzkowitz and Leydesdorff (2000) • Complementary perspectives to the NIS approach

  12. Regional Innovation Systems (RIS) narrowly (I) and broadly (II) defined • (I) A RIS is constituted by two sub-systems and the systemic interaction between them (and with non-local actors and agencies): • The knowledge exploration and diffusing sub-system (universities, technical colleges, R&D institutes, technology transfer agencies, business associations and finance institutions) • The knowledge exploitation sub-system (firms in regional clusters as well as their support industries (customers and suppliers)) • (II) A wider system of organisations and institutions supporting learning and innovation, and their interactions with firms in the region. Integrating innovation policy with education and labour market policies

  13. What characterises most regions? • Very few regions are only high-tech regions (Sillicon Valleys) • Often regions have a combination of (few) high-tech (R&D/ science based) companies (SMEs and large firms/MNEs) and a majority of traditional, medium and low tech SMEs, and large firms • It seems as SMEs are either innovative (e.g. DBFs) and not rapidly growing, or rapidly growing but not innovative (e.g. many service gazelles) • Many regions only have traditonal, low tech SMEs (neither innovative nor rapidly growing) • Still different types of regions can have the same level of economic performance

  14. Differentiated knowledge bases Knowledge creation and innovation take place in all kind of industries but is done in different ways, needs different kinds of knowledge and skills and requires different forms of innovation support No type of knowledge should a priory be considered superior with respect to generating economic growth and innovation Characterise the nature of the critical knowledge which knowledge creation and innovation processes in different industries cannot do without (ontological, generic category) Distinguish between three different knowledge bases: a) analytical (science based) b) synthetic (engineering based) c) symbolic (art based)

  15. Differentiated knowledge bases: A typology

  16. Synthetic Automotive Food Film Pharmacuticals Advertisement Biotechnology Symbolic Analytical Knowledge bases and firms: illustrating empirical examples Symbolic


  18. Different modes of innovation • ’How Europe’s Economies Learn. Coordinating Competing Models’ : Different modes of innovation (Lorenz and Lundvall, 2006) • STI (Science, Technology, Innovation) – analytical knowledge/basic research (science push/supply driven) and synthetic knowledge/applied research (market/user driven) • DUI (Doing, Using, Interacting) – Competence building and organisational innovations – synthetic and symbolic knowledge (market/user driven) • Combining modes of innovation (STI/DUI) makes firms perform better (Berg Jensen et al., 2007) • Firms sourcing broadly (both R&D and experience based knowledge) are the most innovative (Laursen and Salter, 2006)

  19. How to understand regional competitiveness? • Regional dimension: Heterogeniety, contingent factors (e.g. historical, cultural, social, economic, environmental) important ): Diversity and variety • Competition: Based on unique capabilities and competences • Existing competitiveness: growing of existing industries (incremental (process) innovations in existing technological trajectories securing high productivity) – path extension (positive lock-ins) • Future competitiveness: - evolutionary dimension: upgrading existing industries (changing technological trajectories through regional branching) – path renewal - institutional dimension: promoting new emerging industries (radical (product) innovations) – path creation

  20. What is Constructing Regional Advantage (CRA) • New regional development strategy promoting competitiveness on individual and systems levels to meet challenges of the globalising knowledge economy • Building on the IS approach on how to increase competitiveness but advocating a more pro-active and collaborative approach and including the meso (firm) and micro (entrepreneurs and work organisation) levels in addition to the system/macro level • Addressing system failures of weak connectivity and lack of transformative capacity within and between (regional) innovation systems • Support openness and diversity of IS (differentiated knowledge bases/related variety/cognitive distance) in the promotion of platform based strategies of regional development

  21. Definition of Constructing Regional Advantage • Constructing Regional Advantage means: • turning comparative advantage into – or • creating competitive advantage through an explicit policy push promoting a Chamberlinian monopolistic competition based on product differentiation resulting in unique assets or products • Report from DG Research, European Commission, May 2006 • Basic assumption also in the innovation systems and Porter’s cluster approaches • Strenghtening innovation systems policies

  22. Distributed knowledge networks • At present, the awereness and importance of implementing strategies for external knowledge sourcing is increasing, linked to the challenges and opportunities of global innovation networks • Concepts such as open innovation and innovation systems build on the recognition that interorganisational linkages are critical to the innovative capabilities of firms and the growth of economies • As a result of the increasing complexity and diversity of knowledge creation and innovation processes, firms need to access and acquire new, external knowledge to supplement their internal, core knowledge base(s) • Transition from internal knowledge base(s) within firms to distributed knowledge networks across a range of firms, industries and sectors locally and globally

  23. Global open innovation • Evolutionary theory suggests the broader and more diverse the knowledge bases, the larger the scope for innovation • In most economies the most important source of variety in knowledge bases is found abroad • The ability of entrepreneurs and firms of a region to tap into global networks of knowledge and use it productively (open innovation) will in many cases be more important than the creation of new knowledge at home • The global dimension of distributed knowledge networks has increased dramatically in importance over the last decade • In sum, all this implies that territorial innovation systems are ’forced open’, that they can no longer be built solely as sets of user-producer relationships and that an excessive, singular focus on localised learning from the policy system may be harmful

  24. Knowledge bases and proximity • The absorptive capacity for accessing, diffusing and making use of new external and internal knowledge is unenven due to the heterogeniety of firms’ competence bases and the importance of their position in internal and external innovation networks • Proximity dependent on the knowledge bases of firms • Analytical knowledge based firms (e.g. biotech) are part of a local node of excellence in global knowledge networks and epistemic communities - less sensitive to proximity – codified knowledge • Synthetic and symoblic knowledge based firms are more dependent on local knowledge networks and communities of practice - distance matters more – context dependent – higher content of tacit knowledge • For all knowledge bases: Early phasis of innovation facitlitated by F-2-F interaction

  25. Figure: Knowledge sourcing through collaboration in life science regional national international Source: Martin & Moodysson 2012

  26. Figure: Knowledge sourcing through collaboration in food international national regional Source: Martin & Moodysson 2012

  27. Figure: Knowledge sourcing through collaboration in new media regional national international Source: Martin & Moodysson 2012

  28. Regional innovation policies: A classification of policy instruments

  29. Clusters and Regional Innovation Systems (RIS) • Regional Innovation Systems support several clusters • The traditional constellation of regional clusters surrounded by innovation promoting organisations (universities, development agencies) in a RIS is normally found in contexts of industries with a synthetic (and symbolic) knowledge base(s) (rationale: to upgrade historical technological trajectories) • The existence of a RIS as a necessary part of the development of an emerging regional cluster will normally be the case of industries based on an analytical knowledge base (rationale: to support commercialisation of newly created knowledge)

  30. New regional innovation policy • Centres of Expertise – focused cluster/RIS policy • Cooperation between global competitive firms and leading research universities • Nordic countries (Finland, Sweden, Norway) • Upgrading of existing industries and regional branching based on related variety (i.e. industries with the same and/or complementary competences and knowledge bases) • Evolutionary perspective – path renewal through changing technological trajectories • Institutional perspective – new path creation based on emerging, knowledge based spin-offs (Sweden – university driven (exploration)

  31. The concept – Strong R&I milieus • Strong R&I milieus is a VINNOVA ’invention’ – not used internationally – shows VINNOVA’s innovativeness with respect to policy initiatives (e.g. VINNVÄXT) • Centres of Excellence; Centres of Expertise; Technopoles; Science Parks; Clusters (Technology clusters); Poles de Competitivite, RIS • Builds on and inspired by: • (Regional) innovation systems – innovativess and competitiveness can be promoted through policy push. Strong R&I milieus a ’sharpening’ of (R)IS – stronger focus on knowledgecreation – university driven (exploration) • Triple Helix – university, industry, (regional) government – normative (regional) innovation policy approach • Mode 2 – interdisciplinary, problem-oriented, application driven research at universities

  32. Proximity and the global – local nexus:Swedish regional innovation policies • Strong Research and Innovation milieus – strengthening of RIS approach (a narrow based innovation policy) • Sweden – VINNOVA’s regional innovation policy approach. Spatial agglomerations but with an explicit reference to the importance of links to global knowledge networks – open innovation • Emphasizing proximity (not only spatial but also organisational) between knowledge exploration and exploitation • ’Strong’ emphasises of global excellence in knowledge exploration as well as in knowledge exploitation • Institutional perspective (policy push/Triple Helix) promoting innovation (10 years/matching funding) • Top-down/bottom-up strategy

  33. Roles of universities in RIS: • Third mission (after teaching and research): direct interaction between universities and society as key actor in the knowledge exploration subsystem of RIS • Creating high-tech firms • Consulting for local industry • Delivering advice for politicians • Informing general public debates • Universities are increasingly of strategic importance for regional development in the knowledge economy by often being the only actor bringing global state-of-the-art science and technology into the region • Generative role: discrete outputs in response to specific demands • Developmental outputs: development of regional institutional capacities (e.g. in the context of RIS)

  34. VINNOVA - Strong R&I milieus

  35. Requirements for a successful Triple Helix collaboration

  36. Geography dimension - regional concentration of R&D activity Share of national investment EUR per capita NORWAYCapital 45 1 956 Trondheim 17 1 964 SWEDEN Capital 33 1 768 Gothenburg 22.5 1 273 Lund 16.5 1 278 Linköping 18 1 216 FINLAND Capital 56 1 431 Tampere/Åbo 23.5 1 179 Oulu 16.5 1 761 DENMARK Capital 63 2 597

  37. Why a broad based innovation policy? • Is more R&D driven innovation policies always the only answer to improving regional innovativeness and competitiveness? Hardly, as • Regions’ industrial structure are heterogenous, where a one dimensional R&D (S&T) based policy will not work. A fine tuned regional innovation policy is needed (Constructing Regional Adventage) • Many drivers of innovation (supply, demand, market, employee driven) • Many types of innovation (radical vs incremental; product, process, organisational) • Many regions and nations starting to have a stronger focus on this problematic. Thus, the idea of a broad based innovation policy get increasingly more support • Needs both narrow and broad RIS to be implemented combining the STI and DUI modes of innovation

  38. The combination of STI and DUI modes of innovation • Cognitive distance has to be reduced and absorptive capacity increased to achieve such a combination (especially for traditional SMEs) • The STI mode includes both synthetic and symbolic knowledge bases, and the DUI mode is also present in firms based on the STI mode. This represent bridging mechanism reducing the cognitive distance • Internal competence building through developmental learning in learning work organisations and organisational changes increase absorptive capacity • Needs both narrow and broad RIS to be implemented

  39. VRI – a Norwegian innovative regional policy program: A broad based policy • Anticipated later theoretical developments: • DUI mode of innovation with learning work organisations as the micro foundation • Combining DUI and STI – later research has shown that firm sourcing broadly for knowledge for innovation are more innovative – Triple Helix on regional level • Combining research with action research by creating regional learning arenas in the form of regional partnerships (regional development coaltions = learning regions) • Norway had a broad based innovation policy on the regional level 3-4 years before Finland introduced such a policy on the national level

  40. Forms of work organisation across European nations (micro foundationof theDUI mode of innovation) • ‘Learning’ forms of work organisation (CME): • + : Netherlands, Denmark, Sweden and Norway • - : Southern countries and Ireland • ‘Lean’ forms of work organisation: • + : UK, Ireland, Spain and France • - : Netherlands, Denmark, Sweden, Germany and Austria • ‘Taylorist’ forms of work organisation: • + : Southern countries and Ireland • - : Netherlands, Denmark and Sweden • ‘Simple’ forms of work organisation: • + : Southern countries • - : Netherlands, Denmark, Finlandand UK

  41. The forms of work organisation in the EU • Learning forms of work organisation: (39.1%) • autonomy in work • learning dynamics (learning new things, problem solving) • complexity of tasks • responsibility for quality control • low work rate constraints, repetitiveness and monotony • team working and job rotation not characteristic • “Swedish socio-technical” model • “American team working” model (Appelbaum et Batt) • Lean forms of work organisation: (28.2%) • team working • job rotation • quality management (quality norms and quality control) • learning dynamics • work rate constraints, repetitiveness and monotony • relatively low autonomy in work • “Lean production” (Womack et alii; MacDuffie et alii) • “Controlled autonomy” model (Appay; Coutrot)

  42. .8 NL SE DK .7 DE AT LU FI Learning/ Learning + Lean .6 BE FR .5 UK .4 0 50 100 150 EPO High Tech Patents

  43. Interactive learning in learning work organisations

  44. The Norwegian ’puzzle’ • Norwegian ’puzzle’ (OECD): High welfare and per capita income levels, one of the highest GDP globally, and strong performance with respect to productivity in combination with a very low level of investment in R&D (also when controlled for industry structure) • Focus on incremental process innovations in resource based industries (metal, oil and gas) • High level of absorptive capacity due to one of the highest levels of tertiary education in Europe

  45. The Norwegian ’puzzle’ • The high level of absorptive capacity results in a high level of adoption of new technologies, efficient knowledge diffusion and frequent cooperation in innovation • However, such characteristics of a national innovation system is ’typically not captured by conventional indicators of innovation input or output’ (Fagerberg et al. 2009a)

  46. Norwegian oil and gas industry • Even if around 30% of all firms in (a wider defined) oil and gas industry use 4 percent or more on R&D (however, big variations between the subsectors in the industry) ’most past innovations were driven by the close cooperation between operators and suppliers in the development of large fields’ (Sasson and Blomgren, 2011) • This type of innovations as a result of practical challenges related to field development is typical examples of application development

  47. Modes of innovation – technological and application development • Two modes of innovation (synthetic knowledge based, engineering industries with batch production): • Application development. Incremental innovations through user-producer relationships with demanding customers and suppliers in connection with the actual production. In-house experience based competence dependent on a highly qualified workforce. D(oing), U(sing), I(nteracting) mode of innovation • Technological development. Research projects together with universities to develop platform technologies as the basis for application development. S(cience), T(echnology), I(nnovation) mode of innovation

  48. Innovation indicators and measurement • However, many such innovations, which ’relied on well-developed engineering competence and highly competent labor, ...., may not even be classified as innovations by CIS (community innovation study)-type surveys that mainly focus on product and process innovations’ (Fagerberg et al., 2009a) • This implies that ’learning-by-doing and engineering based activities such as the design of large process plants in oil refining or basic metals are not captured by the Frascati mmanual of definitions of R&D and may not be captured by the design category in the CIS expenditures question’ (Fagerberg et al. 2009b) • This measurement problem together with the importance of learning work organisation as the micro foundation of the DUI mode of innovation may well be able to explain why the Norwegian ’puzzle’ is not a ’puzzle’ after all

  49. The Learning Region: Foundations, State of the Art, FutureEd by Rutten & Boekma, Elgar 2007 • Foundations: • Storper: Regional ’worlds’ of production (1993) • Florida: Toward the learning region (1995) • Asheim: Industrial districts as ’learning regions’ (1996) • Morgan: The learning region: institutions, innovation and regional renewal (1997)