constructing regional advantage - dime
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CONSTRUCTING REGIONAL ADVANTAGE
principles – perspectives – policies
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CONSTRUCTING REGIONAL ADVANTAGE
principles – perspectives - policies
REPORT prepared by an independent expert group:
Chairman: Prof. Phil COOKE – Cardiff University – Cardiff - The United Kingdom
Rapporteur:
Prof. Bjørn ASHEIM - Lund University – Lund – Sweden
Prof. Jan ANNERSTEDT – Copenhagen Business School – Frederiksberg – Denmark Dr Jiří BLAŽEK – Charles University – Praha – Czech Republic
Prof. Ron BOSCHMA – Utrecht University – Utrecht – The Netherlands Prof. Daneš BRZICA – Institute of Slovak and World Economy – Bratislava – Slovakia Prof. Asa DAHLSTRAND LINDHOLM – Halmstad University – Halmstad – Sweden
Mr. Jaime DEL CASTILLO HERMOSA – Información y Desarrollo S.L.- Bilbao – Spain Prof. Philippe LAREDO – Laboratoire Territoires, Techniques, Sociétés - Paris– France
Ms Marina MOULA – Cyclotron Ltd – Athens – Greece Prof. Andrea PICCALUGA – Scuola Superiore Sant’Anna, IN-SAT Lab – Pisa - Italy
2006 Directorate-General for Research
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FOREWORD
“We want a Europe (in which) our best and possibly unique factor of competitiveness and prosperity (is) the creativity of our citizens [...]; not only the brains of our elites but the creativity and participation of all our citizens...” Janez Potočnick Commissioner for Science and Research (Mid-term Review of Lisbon Strategy- 2004)
Re-launching the Lisbon strategy that European leaders defined in 2000 and re-invigorating it by focusing on growth and employment in a stronger partnership with Member States, is one of the major challenges for Europe. Building the knowledge society and leveraging knowledge for growth is probably the best, and maybe the only, way to sustain our European model of society. However, we have to realise that the European Community is investing too little in research (2% of our GDP). At the European level, Community research funding has a strong leverage and multiplier effect, both on public research budgets and on private R&D investments. The Communication “More Research and Innovation – Investing for Growth and Employment” adopted by the Commission in October 2005 takes a systemic approach by addressing all factors affecting directly and indirectly the performance of research and innovation systems. The recently developed Regions of Knowledge scheme aims to help all European regions - whatever their level of development – move into the knowledge economy by investing effectively and more in R&D. European regions need expertise in finding the routes to the knowledge economy. This report on “Constructing Regional Advantage”, written by a group of independent experts, provides valuable guidance to the regions for developing their research and innovation capacity and performance and to boost their knowledge-based competitiveness.
Isi SARAGOSSI Director DG RTD-M
Investment in research and links with other policies
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TTAABBLLEE OOFF CCOONNTTEENNTTSS
PPrreesseennttaattiioonn ooff tthhee CCRRAA EExxppeerrtt GGrroouupp –– TTrroommbbiinnoossccooppee 33
LLiisstt ooff AAccrroonnyymmss 88
EExxeeccuuttiivvee SSuummmmaarryy aanndd RReeccoommmmeennddaattiioonnss 1100 .. TThhee mmaannddaattee ooff tthhee ‘‘EExxppeerrtt GGrroouupp’’ oonn ‘‘CCoonnssttrruuccttiinngg RReeggiioonnaall AAddvvaannttaaggee’’ 1111
.. CCoonnssttrruuccttiinngg RReeggiioonnaall AAddvvaannttaaggee ((CCRRAA)) 1122
.. PPeerrssppeeccttiivveess aanndd mmeetthhooddoollooggiieess ffoorr ppoolliicciieess ooff CCRRAA 1133
.. CCoonntteenntt ooff ppoolliicciieess ffoorr ccoonnssttrruuccttiinngg rreeggiioonnaall aaddvvaannttaaggee 1144
.. ‘‘CCaarrrriieerrss’’ ooff ppoolliicciieess ffoorr ccoonnssttrruuccttiinngg rreeggiioonnaall aaddvvaannttaaggee 1166
.. RReeccoommmmeennddaattiioonnss 1199
.. CCoonncclluussiioonn 2233
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WWhhyy rreeggiioonnss?? 2299 .. DDeeffiinniittiioonn aanndd rraattiioonnaallee 2299
.. RReeggiioonnaalliissaattiioonn ooff IInnnnoovvaattiioonn PPoolliiccyy 3300
.. CCoonnssttrruuccttiinngg RReeggiioonnaall AAddvvaannttaaggee ((CCRRAA)) 3311
.. PPeerrssppeeccttiivvee aanndd mmeetthhooddoollooggiieess ffoorr ppoolliicciieess ooff CCRRAA 3322
BBaacckkggrroouunndd aanndd pprree--ccoonnddiittiioonnss ooff ccoonnssttrruuccttiinngg rreeggiioonnaall aaddvvaannttaaggee 3355 .. RReeggiioonnaall eennddoowwmmeennttss 3355
.. BBooxx 22:: HHooww ttoo ttrraannssffoorrmm aann iinndduussttrriiaall ddiissttrriicctt iinn ccrriissiiss iinn tthhee ppeerriipphheerryy ooff EEuurrooppee?? --
TThhee ccaassee ooff tthhee BBaarrlleettttaa ffoooottwweeaarr ddiissttrriicctt 3366 .. BBooxx 33:: EEmmeerrggiinngg nneeww mmuullttiicceennttrree ––
VViieennnnaa--BBrraattiissllaavvaa mmeettrrooppoolliittaann aarreeaa ((VVBBMMAA)) 3377 .. BBooxx 44:: CChhaalllleennggeerr ffoorr rreeggiioonnss lleessss ssuucccceessssffuull iinn iinnnnoovvaattiioonnss ––
TThhee ccaassee ooff PPrraagguuee 3388 .. BBooxx 55:: PPrroommoottiinngg IInnnnoovvaattiioonn iinn LLeessss FFaavvoouurreedd RReeggiioonnss ––
TThhee eexxppeerriieennccee ooff NNoorrtthh AAeeggeeaann 4411 .. EEvvoolluuttiioonnaarryy ppeerrssppeeccttiivvee 4422
.. BBooxx 66:: TThhee eexxppeerriieennccee ooff FFiinnnniisshh SScciieennccee 4433
.. BBooxx 77:: GGrreennoobbllee:: BBuuiillddiinngg aa wwoorrlldd ccllaassss ““ppoollee”” 4433
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CCoonntteenntt ooff ppoolliicciieess ffoorr ccoonnssttrruuccttiinngg rreeggiioonnaall aaddvvaannttaaggee 4455 .. RReellaatteedd vvaarriieettyy 4466
.. BBooxx 88:: TThhee iimmppoorrttaannccee ooff aa ggeenneerriicc kknnoowwlleeddggee bbaassee –– TThhee ccaassee ooff tthhee EEmmiilliiaa--RRoommaaggnnaa rreeggiioonn 4477
.. DDiiffffeerreennttiiaatteedd kknnoowwlleeddggee bbaasseess 4488
.. DDiissttrriibbuutteedd kknnoowwlleeddggee nneettwwoorrkkss 5500
PPllaattffoorrmm vvss.. SSeeccttoorriiaall ppoolliicciieess 5511 .. BBooxx 99:: AAnn eexxaammppllee ooff ppllaattffoorrmm ssttrraatteeggiieess 5522
.. BBooxx 1100:: SShhaappiinngg aa wwoorrlldd ccllaassss hhuubb –– TThhee eevvoollvviinngg hheeaalltthhccaarree cclluusstteerr iinn SShhaanngghhaaii 5533
‘‘CCaarrrriieerrss’’ ooff ppoolliicciieess ffoorr ccoonnssttrruuccttiinngg rreeggiioonnaall aaddvvaannttaaggee 5555 .. TTeerrrriittoorriiaall ccoommppeetteennccee bbaasseess 5555
.. BBuussiinneessss cclliimmaattee aanndd PPeeooppllee cclliimmaattee 5555
.. RReeggiioonnaall kknnoowwlleeddggee iinnffrraassttrruuccttuurree 5577
.. BBooxx 1111:: HHuubb--cciittiieess aanndd tthheeiirr rreeggiioonnss –– SSuucccceessssffuull llooccaall cclluusstteerrss aarree gglloobbaallllyy ccoonnnneecctteedd 5588
.. SSMMEE aanndd eennttrreepprreenneeuurrsshhiipp ppoolliicciieess 5599
.. BBooxx 1122:: AAuussttiinn,, TTeexxaass –– AAddvvaannttaaggee ccoonnssttrruucctteedd oonn aa ccrreeaattiivvee ‘‘SScceennee’’ 6611
.. BBooxx 1133:: KKnnoowwlleeddggee--bbaasseedd eennttrreepprreenneeuurrsshhiipp –– TThhee ccaassee ooff tteecchhnnoollooggyy--bbaasseedd nneeww ffiirrmmss 6633
.. UUppggrraaddiinngg aanndd bbuuiillddiinngg rreeggiioonnaall iinnnnoovvaattiioonn ssyysstteemmss 6655
.. BBooxx 1144:: TThhiirrdd GGeenneerraattiioonn IInnnnoovvaattiioonn EEnnvviirroonnmmeennttss -- 6666
.. BBooxx 1155:: BBuuiillddiinngg RReeggiioonnaall IInnnnoovvaattiioonn SSyysstteemmss -- VVIINNNNOOVVAA’’ss VVIINNNNVVAAXXTT--iinniittiiaattiivvee 6677
.. RReeggiioonnaall IInnnnoovvaattiioonn SSyysstteemmss aass ccrreeaattiivvee kknnoowwlleeddggee eennvviirroonnmmeennttss 6699
AAppppeennddiixx 11:: CCoonncceeppttuuaall aanndd TThheeoorreettiiccaall bbaacckkggrroouunndd 7711 .. CCoonnssttrruucctteedd aaddvvaannttaaggee:: DDeeffiinniittiioonn aanndd ccoonncceeppttss 7711
AAppppeennddiixx 22:: HHooww ttoo cchhaarraacctteerriissee rreeggiioonnss –– TThhee tthhrreeee iinndduussttrriiaall kknnoowwlleeddggee bbaasseess 7755 .. AAnnaallyyttiiccaall kknnoowwlleeddggee bbaassee 7755
.. SSyynntthheettiiccaall kknnoowwlleeddggee bbaassee 7755
.. SSyymmbboolliicc kknnoowwlleeddggee bbaassee 7766
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.. RReeggiioonnaall IInnnnoovvaattiioonn SSyysstteemmss ((RRIISS)) 7799
.. VVaarriieettiieess ooff RReeggiioonnaall IInnnnoovvaattiioonn SSyysstteemmss 8800
.. CCaann RReeggiioonnaall IInnnnoovvaattiioonn SSyysstteemmss eexxiisstt?? 8822
.. CClluusstteerrss 8833
.. KKnnoowwlleeddggee bbaassee aanndd iinnssttiittuuttiioonnaall ffrraammeewwoorrkk:: CCoonnnneeccttiinngg cclluusstteerrss aanndd rreeggiioonnaall iinnnnoovvaattiioonn ssyysstteemmss 8855 .. LLeeaarrnniinngg RReeggiioonnss 8866
.. TThhee bbuuiillddiinngg bblloocckkss ooff tthhee ccoonncceepptt ooff LLeeaarrnniinngg RReeggiioonnss 8877
.. TThhee TTrriippllee HHeelliixx 8888
RReeffeerreenncceess 9900
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TTaabblleess aanndd FFiigguurreess
TTaabbllee 11 –– MMeeaanniinngg ooff rreeggiioonnaalliissaattiioonn 3300
FFiigguurree 11 –– AA ssyysstteemmiicc rreepprreesseennttaattiioonn ooff ddyynnaammiissmm iinn rreeggiioonnaall ssyysstteemmss 3399
TTaabbllee 22 –– KKnnoowwlleeddggee EEccoonnoommiieess –– IInnddeexx NNuummbbeerrss,, EEuurrooppeeaann UUnniioonn ((1155)) 4400
TTaabbllee 33 –– TThhee tthhrreeee kknnoowwlleeddggee bbaasseess 4499
Figure 2 Knowledge bases and industries: an illustration 49 Figure 3 – Platform policies 52 Figure 4 – Two dimensional classification of main innovation policy 60
TTaabbllee 44 –– CChhaarraacctteerriissttiiccss ooff iinnssttiittuuttiioonnaall aanndd eennttrreepprreenneeuurriiaall ttyyppeess ooff RRIISS 6600
TTaabbllee 55 –– CClloosseedd aanndd ooppeenn iinnnnoovvaattiioonn 6622
Figure 5 – Types of regional Innovation systems and knowledge bases 68
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ACRONYMS
BRIS – Bohemian Regional Innovation Strategy
CEA – Centre d’Energie Atomique
CRA – Constructing Regional Advantage
CSF - Community Support Framework (Structural Funds)
EC – European Commission
ERA– European Research Area ERIS – Entrepreneurial Regional Innovation System
ESRF - European synchrotron research facility
EU – European Union
FDI – Foreign Direct Investments
GDP – Gross Domestic Product
GSM - Global System for Mobile
IBIT – Technology Park of the Balearic Islands (Illes Balears Innovació Tecnológica)
ICT – Information and Communication Technologies
INA – Innovation in North Aegean
INPG - Institut National Polytechnique de Grenoble
IRIS – Institutional Regional Innovation System
ITT – Innovation and Technology Transfer
JAVA-Platform (easy-way computer language for animation and other multimedia possibilities)
KIBS – Knowledge Intensive Business Services
LETI - Laboratoire d'étude des technologies de l'information
MINERVA Programme - Mobilizácia Inovácií v Národnej Ekonomike a Rozvoj Vedecko-Vzdelávacích Aktivít (Mobilisation of Innovation in National Economy and Development of Scientific-Educational Activities) - Slovakia
MINATEC - Micro et Nano Technologies
MNC – Multi National Companies
OLI – Ownership-Location-Investor
PRIME - Network of excellence on Policies for Research and Innovation in the Move towards the ERA
R&D – Research and Development
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RDTI – Research Development and Technological Innovation
R&T – Research and Technology
RIS – Regional Innovation Systems
RITTS – Regional Innovation and Technology Transfer Strategy
ROP – Regional Operational Programme
SME – Small and Medium Sized Enterprise
SMEPOL – SME policy and the Regional Dimension of Innovation (Research project under the Targeted Socio-Economic Research programme – 4th Framework Programme – financed by the European Commission – DG Research
TNC – Trans National Companies
UFJ - Université Joseph Fourier
VBMA – Vienna-Bratislava Metropolitan Area
ZIRS - Zone Industrielle et de Recherche S&T
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CCoonnssttrruuccttiinngg RReeggiioonnaall AAddvvaannttaaggee EExxeeccuuttiivvee SSuummmmaarryy aanndd RReeccoommmmeennddaattiioonnss
Developing the regional dimension of the European Research Area implies developing the endogenous capacity of the regions to innovate and to capitalise on their strengths to create wealth and jobs. This approach can be described by the concept of creating a new competitive advantage in a globalised world. Devising ways to valorise specific knowledge-assets at regional level proves to be a crucial task and allows regions to achieve “constructed regional advantage”.
European Commission’s DG Research has taken an initiative to set up an Expert Group chaired by Professor Phil Cooke (University of Wales, Cardiff), specifically devoted to this task. On behalf of the Commission services, the Expert Group has been managed by Unit M3 (Sector on Regional Aspects of Research Policy) under the responsibility of Dr. Dimitri Corpakis (Head of Sector) and Mr Jean-Marie Rousseau (Policy Officer) who also set the Terms of Reference for the Group’s work. The Group met eight times from September 2004 to December 2005.
The Expert group on Constructing Regional Advantage devised a methodology as a flexible tool providing a variety of approaches for delivering guidance and workable approaches to regional policy makers faced with the challenge of the knowledge based economy rather than a one-size-fits-all solution. In this respect, the Expert Group had to define a flexible, yet rigorous and focused process to allow tools and methods to be transferred to the wider community of European regions. The Expert Group outlined guidance to help regions help themselves to build their own attractive regional image while reinforcing the ability of business and research communities to quickly respond to new scientific and technological opportunities.
The mandate of the ‘Expert Group’ on ‘Constructing Regional Advantage’
In the relevant Terms of Reference, it is stated that: ‘the work of this Expert Group is to be seen fully against the context of the Barcelona objective, namely achieving average investment in Research and Development of 3% of the Union’s GDP by 2010. The 3% Action Plan identified the need for regions to become more efficient in using their resources for investing in R&D. It also pointed to the need for setting up learning initiatives for the regions. The EU needs expertise in finding routes to the knowledge economy and the contribution of the Expert Group on ‘Constructing Regional Advantage’ may be instrumental in this respect.’
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Constructing Regional Advantage (CRA)
Taking this as a point of departure, the aim of this report is to proceed further in strengthening this approach by asking how the capacity for knowledge creation and exploitation in the context of regional innovation systems can be developed as a means of constructing regional advantage.
This is the result of the increasing global competition from newly industrialised countries such as Taiwan, South Korea, Singapore, and rapidly catching up countries such as China and India. The new economic landscape has emphasised the need for firms in Europe to enhance their competitiveness by combining a focus on product and service differentiation/innovation with cost efficiency.
Subsequently firms may apply an open innovation model and thus, rely on sourcing – sometimes globally – for the best talents. Simultaneously, outsourcing or off-shoring of standardised labour-intensive activities to low-cost countries is increasing. In this vein we concur that constructed advantage is regarded as the next evolutionary step in regional economic development.
While the theory of comparative advantage is criticised for ignoring the role of technological change and innovation, the theory of competitive advantage is also considered too narrowly market focused.
The theory of constructed advantage allows for more attention to the role and impact of the public sector in the economy. It also highlights policy support, preferably in public-private partnerships, by acknowledging to a greater extent the importance of institutional and economic complementarities in knowledge economies than do theories of comparative and competitive advantage.
Instead of market failure, the rationale for policy intervention is the reduction of interaction or connectivity deficits. A regional innovation systems approach, which is key to constructed advantage, sees such deficits as the core problem of innovation in the EU.
Therefore, it is an important question whether firms can take up this challenge of strengthening their knowledge bases by themselves. Evidence suggests that rarely on their own initiative do firms start co-operating with neighbouring firms or co-located knowledge creating and diffusing organisations.
Accordingly, while changing their behaviour to become more innovative is one option, another involves more planned and systemic approaches to innovation in a globalising knowledge economy. In this way, regional advantage may be consciously and pro-actively constructed. This involves a new and more dynamic role for the public sector, for example universities, and the wider economic governance system, specifically in interaction with the private sector.
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Perspectives and methodologies for policies of CRA
Today, social scientists and policy makers highlight regions as key sites of innovation and competitiveness in the globalising economy. Thus, regional innovation systems (RIS) are seen as an increasingly important policy framework for implementing long-term, innovation based regional development strategies, including clusters.
Research shows that the majority of theoretical as well as empirical analyses of innovation systems have a regional focus. In more and more countries, innovation policies take place at the regional level.
The regionalisation of innovation policy holds the potential for improved ‘on-the-ground’ policy by developing know-how about specific economy conditions at the regional action level. Measures can be formulated, implemented and monitored in a more targeted way, and thus be capable of addressing more precisely what are particular regional firms’ needs. Foremost among these, are deficits concerning innovation, regional proximity and communicative interaction.
Given the complexity of the challenge, the report offers not ‘one-size-fits-all’ recipes but rather a policy methodology and perspective. This is appropriate in a Europe characterised by large scale and developmental diversity.
Past experiences, concrete cases, theories and models represent the background which policy makers should work with in order to find their own (regional) solution, rather than the exact replication or ‘cloning’ of more or less successful examples of regional policies from elsewhere, often from places with very different economic and socio-institutional environments.
Copying of best practices is almost impossible when it comes to intangible regional assets (such as particular knowledge bases or institutional settings) that are the results of long histories in particular regional contexts. Policy makers should therefore reflect on this and be wary to simply imitate successful models.
Nonetheless, some general perspectives do exist which can be taken into account as supporting methodologies that policy makers can use to formulate and implement innovative regional policies. Policy makers are thus responsible for tailoring region-specific policy. They will seek to support regional strengths through better aligning knowledge exploration and knowledge exploitation capabilities.
Regional policy in a diversified, globalising economy increasingly works in this way as a mosaic which has to be built with pieces which are not pre-determined. The mosaic is composed of elements related to producing coherent policy and development pictures.
Of key importance in this context is the recognition of institutional and governance capabilities in regions. This should take into account variation in the quali ty of regional communication infrastructures, understanding the knowledge base advantages of the
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region, and presuming that true regional innovation system connectivity is not complete in most regions.
Moreover, regional development must be understood as an evolutionary process, based on path dependent technological trajectories. According to evolutionary thinking, the historical trajectory of a region sets serious limits to the windows of opportunity with regard to relevant policy options as well as to copying an external model that owed its success to its deep roots in a distinctive environment.
Furthermore, an evolutionary perspective also implies that changes in industrial structure, capacity to innovate and competitiveness take time. An important aspect of this perspective is also the lock-in problematic in the context of, for example, old industrial regions.
Content of policies for constructing regional advantage
A focus on constructing regional advantage requires an ‘unpacking’ of key elements of the regional economic and governance mosaic. Much has been discovered recently about what makes, for example, territorial agglomerations important for innovation and growth. These include better understanding of distinctive modes in which regional knowledge creation, innovation and entrepreneurship occur. In the report, such unpacking is conducted according to the following dimensions:
• related variety,
• differentiated knowledge bases,
• distributed knowledge networks,
• trans-sectorial platform policies.
These ‘unpacking’ efforts improve the capacity of policy makers at different geographical levels to formulate dedicated and specific innovation support customised to different regions and sectors. These will be in increasing demand if regions in high-cost countries are to compete and survive in a globalising knowledge economy. Especially important is the formation of necessary capabilities in regions to construct regional advantage.
Firstly, the theoretical disagreement between adherents of the opposed views that sectoral specialisation or differentiation are best for nurturing innovation is resolved by evidence that growth occurs in contexts of related variety economic platforms. Related variety allows higher absorptive capacity and more rapid diffusion of innovations among related user-producer communities. Think of the many, rapid innovative spill-over adaptations of sensors, software and digital content. Related variety thus combines the strength of the specialisation of ‘localisation’ economies and the diversity of ‘urbanisation’ economies.
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Secondly, differentiating between industrial knowledge bases represents another dimension of the ‘unpacking’ strategy. The innovation process of firms and industries is strongly shaped by their specific knowledge base. In this report, we distinguish between three types of knowledge base: ‘analytical’, ‘synthetic’ and ‘symbolic’. These types indicate different mixes of tacit and codified knowledge, codification possibilities and limits, qualifications and skills required by organisations and institutions involved, as well as specific innovation challenges and pressures. Crossing such boundaries is the heart of the connectivity problem.
Thirdly, it is important in the discussion of preconditions for constructing regional advantage to shed light on how knowledge bases of different sectors are changing as a consequence of globalisation. In order fully to grasp the dynamics of these changes, a globalisation perspective must explicitly be taken into consideration to modify the endogenous perspective by introducing a distributed knowledge network perspective, which more and more are manifested in global value chains organised by Trans National Companies (TNCs).
Finally, taken together, these three dimensions provide the base for formulating sectoral transcending platform oriented policies. As noted, a narrow sector perspective is redundant for constructing regional advantage in a globalising knowledge economy. The platform concept has so far mostly been used either to describe generic technologies such as software and biotechnology, that have potential applications across a wide range of industries, or modular developments in automotives, where a limited number of platforms can be used to build a large variety of car models.
One of the consequences of the very fast pace of current technological change is that innovations are often in general purpose technologies with applications over a range of services, products and industries. This is the current creative advantage of advanced economies, since the innovative skill lies not in imitation but innovative adaptation, including disruptive innovation such as on-line banking, budget airlines, and digital electronics.
Platform policies articulate support for related variety by integrating differentiated supports ranging from talent formation to economic aids and environmental enhancement.
Thus rigid sectoral policies at regional level can be a risk for the following reasons:
First and foremost, there are no policies which are sufficient for the survival of sectors which have moved to low-cost countries.
Second, if sectors are identified in a too rigid way, scientific and technological opportunities can emerge at regional levels which cannot be exploited, leading to inventions being exploited by companies located in other regions.
Third, sectors are in fact a statistical fiction and even more so, frequently an outdated statistical description, slow to catch up with the emergence of new platform fields. For example, it is still impossible in many national statistical systems effortlessly to find biotechnology statistics.
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This recognises the complexity in contemporary interactions and systems of knowledge, technologies, and economies, and offers a more effective and efficient way of dealing with it. Platform policies create more scope and flexibility on the one hand, and the need for connectivity and the creation of systems on the other.
A platform approach generates a context better equipped to exploit multipurpose and generic technologies. Therefore, the notion of policy platforms highlights the articulation of an array of instruments including and integrating key components from several policy domains.
‘Carriers’ of policies for constructing regional advantage
In order for platform policies to be initiated, innovated and implemented, various actors, agencies and structures must exist and be engaged as ‘carriers’ of policies for constructing regional advantage. This highlights the importance of territorial competence bases (including people and business climate as well as the regional knowledge infrastructure), SME and entrepreneurship policies (especially technology-based entrepreneurship), and governance dimensions of upgrading and building regional innovation systems as creative knowledge environments.
This emphasises the need for a more platform and system-oriented as well as a more pro-active innovation based regional policy in order to construct regional advantage. A re-orientation of what is called the target level of support, changing innovation policies from being firm-oriented to a (regional) system-oriented perspective has already received growing attention from researchers and policy makers. To some extent, this has emerged from experience of pursuing localised cluster building or broader regional innovation system policy.
However, the second part of the recommendation concerns the form and focus of support. This implies a change of focus from allocation of resources for innovation to focusing on innovative learning, aiming for behavioural value-added through pursuing a platform-oriented perspective. Hitherto, this has not been implemented to the same degree. Of strategic importance in shaping the conditions for constructing regional advantage is precisely a need for a more conscious and thoroughly systemic approach to developing the endogenous capacity of firms and regions to innovate.
To repeat, this focuses especially on the role of knowledge creation, absorption and diffusion generally, with R&D and Symbolic Creativity more specifically in a well-structured and well-designed interplay of local and global knowledge flows.
Regional innovation systems have played and will continue to play a strategic role in promoting the innovativeness and competitiveness of regions. To achieve this, the RIS approach has to be strengthened by attention being directed towards the need – perceived
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by policy makers both at EU and regional levels – of a broader basis of constructing regional advantage.
Therefore, theoretical and practical advice must be developed partly with respect to how collaboration between the actors of the so-called Triple-Helix, i.e. the industry, university and government, should be externally organised. Partly also with respect to how knowledge creation and innovation oriented work should be organised internally among the different actors, thus turning the macro-, meso-, and micro-levels of the Triple-Helix into creative knowledge environments.
Creative knowledge environments in which new knowledge is produced can be found at macro- (e.g. national or regional innovation systems), meso- (e.g. research institutions and corporations) as well as micro-levels (i.e. research groups or work teams), and contain physical, social and cognitive characteristics.
This new focus on creative knowledge environments covers a void in the majority of innovation studies - primarily focusing on how knowledge is exploited through innovation and entrepreneurship – by analysing how creation of new knowledge actually occurs as well as what characterises the environments in which creative knowledge-producing activities are carried out.
Thus the approach puts clearer focus on actors, agencies and governance forms as well as their respective environments relevant for constructing regional advantage in a triple-helix as well as a multi-level perspective.
Today, a major opportunity exists for European public authorities to boost the Lisbon agenda for competitiveness, while simultaneously improving services and attractiveness. However, achieving these goals requires changes in the mindset in terms of knowledge valorisation and specific regional advantages.
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RECOMMENDATIONS
According to the above reflections and witnesses, set out below are key CRA Commission recommendations:
Recommendation
1
In accordance with the 3% action plan of the Barcelona objective, the report recommends that regions must become more efficient in using their resources for investing in R&D as well as developing their capacity for knowledge creation and exploitation as a means to constructing regional advantage.
Recommendation
2
In order for EU regions to be more competitive, changing firms’ behaviour to become more innovative is one option. This suggests a new and more dynamic role for the public sector (including universities) generally and government in interaction with the private sector.
Recommendation
3
In order to accomplish constructed regional advantage further theoretical and practical advice requires development:
1) partly with respect to how collaboration between the actors of the triple-helix (industry, university and government) should be externally organised, and
2) partly with respect to how knowledge creation and innovation oriented work should be organised internally among the different actors, thus turning the macro-, meso-, and micro-levels of RIS into creative knowledge environments.
Recommendation
4
Since various actors, agencies and structures are required to be engaged as ‘carriers’ of policies for constructing regional advantage, we must highlight: 1) the importance of territorial competence bases, including people and business climate as well as the regional knowledge infrastructure,
2) SME and entrepreneurship policies, especially technology-based entrepreneurship, and 3) governance dimensions of upgrading and building regional innovation systems as creative knowledge environments.
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Recommendation
5
The idea that it is possible to design ‘one-size-fits-all’ regional policies is no longer valid or viable. Copying of best practices is almost impossible when it comes to intangible regional assets that are the results of long histories in particular regional contexts. Policy makers are advised to be wary to simply imitate successful models. Therefore, local solutions have to be inspired by endogenous capacity which needs to evolve rather than selecting from a portfolio of specific models or recipes.
Recommendation
6
According to evolutionary thinking the historical trajectory of a region sets serious limits to the windows of opportunity with regard to relevant policy options. Regional policy in a diversified, globalising economy must be understood as a mosaic that has to be built with pieces which are not pre-determined. Of key importance in this context is the quality of regional communication infrastructures, understanding the knowledge base strengths of the region, as well as evolutionary processes, i.e. based on path dependent technological trajectories.
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Recommendation
7
Since focusing on learning aiming for behavioural value-added through a platform-oriented perspective is of strategic importance, it is worth focusing especially on the role of knowledge creation, absorption and diffusion generally with R&D. A well-structured and well-designed interplay of local and global knowledge flows focused on regions as ‘knowledge hubs’ is advocated.
Recommendation
8
Constructing regional advantage requires an identification of the basic building blocks for developing this approach, by using the following dimensions:
(1) related variety accounting for spill-over effects, and combining the strength of the specialisation of localisation economies and the diversity of urbanisation economies;
(2) differentiated knowledge bases (synthetic, analytical, symbolic), referring to different mixes of tacit and codified knowledge, codification possibilities and limits, qualifications and skills as well as specific innovation challenges and pressures;
(3) distributed knowledge networks, taking into account how knowledge bases of different sectors are changing as a consequence of globalisation;
(4) Taken together these provide the foundation for formulating trans-sectoral platform policies for potential applications across a wide range of industries.
Recommendation
9
While rigid sectoral policies at regional levels can be at risk in a globalised competition, a platform approach offers a context better equipped to exploit multipurpose and generic technologies. Therefore, policy platforms, which help articulate an array of instruments from several policy domains, will facilitate the formation of necessary capabilities in regions without existing capabilities to construct regional advantage.
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Conclusion
Globalisation is forcing European regions to differentiate and search for activities that cannot be done cheaper somewhere else. Simultaneously, the effort towards creating an increasingly knowledge-based competitive advantage may become the principal force driving globalisation. As demonstrated in this report, genuine comparisons of case studies may allow provide a strategic guidance with reference to evolutionary problems faced by:
• Peripheral regions with less R&D intensity and less developed knowledge infrastructure;
• Old industrial regions characterised by negative lock-in (heavy dependence and specialisation on mature industrial sectors);
• Fragmented metropolitan regions unable to connect knowledge and business bodies;
• Regions with cutting technological edge which, so long for granted, may be slipping and gradually losing ground, due to serious challenge coming from emergent countries;
For the European regions to become or stay competitive requires a series of key factors, but creativity and knowledge exploitation capacity are probably among the most critical. Both affect the regions' capacity to sustain global competition as active players and influence their capacity for delivering innovative products or services. To achieve this and reach a stage of sustainable wealth, dramatic improvements are needed in the effectiveness and the commitment of regional policies.
The Expert Group has come up with nine key recommendations to policy makers. However, it has to be stressed that simple imitation of foreign successful models is highly risky. Therefore, local solutions have always to be inspired by endogenous capacity which needs to evolve rather than selecting from a portfolio of specific models or recipes.
The bottom line and the single most critical message of this report is about people: People essentially matter within the territories and make the difference among the territories. The way regions cultivate and nurture their policy on attracting, treating and maintaining creative people generates innovative, knowledge-based economic activities, and can engender Constructed Advantage to Regions.
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Policy challenges in a globalising economy
Globalisation represents serious challenges for the advanced economies of highly developed countries. Outsourcing/offshoring, delocalisation, FDIs and globally distributed knowledge bases orchestrated by TNCs often imply dramatic restructuring of workplaces and employment in traditionally strong sectors and central regions as well as in peripheral regions. Rapidly growing third world economies do not only represent strong competition in the production of standardised, labour intensive and low-skilled production of goods and services based on cost efficiency (i.e. low wages), but increasingly also within more knowledge intensive production of both manufacturing goods and services. The most viable alternative open to high cost nations is to strengthen their innovation capacity by increasing their knowledge creation (including R&D), absorptive and diffusion capacity on the one hand as well knowledge-based entrepreneurship and talent attraction on the other. There are two paradoxical characteristics of the contemporary global economy. First, innovative activity is not uniformly or randomly distributed across the geographical landscape. Indeed, the more knowledge-intensive the economic activity, the more geographically clustered it tends to be. The best examples include industries such as biotechnology or financial services, which have become ever more tightly clustered in a small number of major centres, despite the attempts of many other places to attract or generate their own activities in these sectors. Second, this tendency toward spatial concentration has become more marked over time, not less. This reality contradicts longstanding predictions that the increasing use of information and communication technologies would lead to the dispersal of innovative activity over time. Given these rather striking stylised facts, it would appear that the process of knowledge production exhibits a very distinctive geography. Innovation and creative capacity are essential determinants of economic prosperity in a globalising learning economy, where knowledge has become the most important production factor. This implies that the capacity for knowledge creation and exploitation by means of innovation and entrepreneurship will be of utmost importance for promoting economic growth, job generation and social cohesion in the EU in the future. Recent work on innovation systems indicates that the region is a key level at which innovative capacity is shaped and economic processes coordinated and governed. This has among other things led to governments and agencies at various geographical levels looking at regional innovation systems (RIS) as key elements of their innovation policy. However, knowledge and innovation should not simply be equated with R&D. Innovative activities have a much broader knowledge base than just R&D, and there are many examples of nations and regions demonstrating a rapid economic growth and a high level of living standard with and industry competing on the bases of non-R&D based, incremental innovations (e.g. Denmark and parts of The Third Italy). Thus, a region’s knowledge base is larger than its science base, implying that maintaining that we experience a process of the globalising economy becoming increasingly more knowledge
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intensive does not necessarily mean that innovation and competitiveness will only depend on R&D. In this context it is important to be reminded of Porter’s view on competitive advantage of firms and regions being based on the exploitation of unique resources and competencies, which must be reproduced through continuous innovation, and, furthermore, that such unique resources and competencies need not be R&D-based precisely because knowledge intensity and innovation is more than just R&D. On the other hand, globalization and codification processes also means a broadening of R&D activities to encompass activities that earlier was artisan based (e.g. design) or in sectors which never earlier have acquired input from R&D institutions (e.g. the tourist sector upgrading to more value-added forms of tourism (e.g. health, food or activity based, see box 1)).
BBooxx 11 STRENGTHENING INNOVATION IN A TRADITIONAL SECTOR THE CASE OF TOURISM IN THE BALEARIC ISLANDS REGION
In many regions in Southern Europe, tourism is one of the most important economic activities with regard to the generation of added value and employment. However, tourism hardly ever has been one of the priority sectors for regional competitiveness and innovation policies.
This situation presented an important challenge in the case of the Balearic Islands in Spain, where the tourism sector is especially relevant to the regional economy, with linkages to many other productive and service sectors. And this was the reason to focus the Regional Innovation Strategy on tourism and on this peculiar economic reality.
The first difficulty to be faced was the lack of relevant theoretical references regarding innovation in the tourism sector or in a tourism-based economy. This could be attributed to the fact that the development of innovation strategies and policies has been related from the beginning to industrial activities and, more recently, to advanced services, but not to (apparently) traditional service sectors like tourism.
The second challenge was the lack of statistical indicators adapted to the area of innovation in services. So, for example, the Balearic Islands were the least developed Spanish region with regard to research and development expenditure as part of the regional GDP, however being the home region of some of the most innovative and international business groups in the Spanish economy, especially in the area of tourism and hotel business. One of the reasons of this obvious contradiction is the lacking consideration which is given in traditional surveys on business innovation and RTDI expenditure to service companies and new emergent sectors.
Once defined the Regional Innovation Strategy placed a specific focus on the tourism sector and the need to exploit the demand for innovating, technology-based solutions in the Balearic Region. The same approach has then been applied during the Innovative Action’s Programme of the European Commission.
The activities in the framework of the Innovative Action were based in the first place on the promotion of web-based booking systems and tools for small and medium-sized business in the hotel and lodging sector. A new reservation system technology called AvantHotel was developed and launched. The technology was developed by the Balearic Foundation for Technology IBIT on the base of a JAVA-Platform for the intelligent on-line management, booking and information offer of accommodation places and related leisure activities, services and other opportunities. With the collaboration of the hotel business associations of
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each of the Balearic Islands, the system was promoted and integrated, so that especially small hotels, apartments, pensions and camping sites could use this tool and compete with the larger hotel groups and their corporate web sites and reservation systems.
This project was positively received by the regional tourism businesses and presents a good example for a successful regional public-private partnership. At the same time, it has been possible to involve and strengthen the regional technology centre IBIT, focussed on the development of technological and ICT solutions for the tourism sector. Knowledge was transferred also to other regional companies while using an open-source technology and a licensing approach for the marketing of the booking system. The experience of AvantHotel was a rather positive one for the region, because it allowed to integrate a new technology and to open new markets and forms of promotion for local small and medium-sized enterprises, without the need to use intermediaries, creating therefore an important added value.
In another action line of the Innovative Action of the Balearic Islands Region, the promotion of tourism clusters was promoted. In the area of nautical sports and ports, the enterprises of Mallorca in cooperation with the local Chamber of Commerce started the initiative to co-operate in common innovating projects and to promote themselves as one business cluster within the internal market and at international level. Moreover, the clustering of regional aeronautical firms has been supported. The aeronautical sector becomes more and more important due to the increasing air traffic and relevance of the airport of Palma de Mallorca, which is already the third Spanish airport in relation to passenger figures.
Other tourism and leisure-related services sectors which have been promoted within the Innovative Action are the traditional furniture industry, the plants and gardening sector, as well as the fitness and wellness sector. These sectors are especially demanded by tourists and foreign residents on the islands and present important business opportunities. Finally, a business incubator has been set up in the Technology Park of the Balearic Islands on the island of Mallorca. The incubator will serve in particular entrepreneurs and new businesses in the field of ICT and technology-related sectors. Many of the new initiatives are directly linked to new and arising business needs of tourism and service enterprises.
To sum up, the innovation-oriented policy in the Balearic Islands Region helps not only to create new added value for existing firms and in “traditional” service sectors, but tries also to promote new and emergent sectors which are directly or indirectly linked to the tourism and leisure industry on the Islands. All this helps to improve the competitive capacity of the regional enterprises and to respond to the increasing international challenges of the tourism industry and to new competitors from the Mediterranean region and other destinations. The research reported in Berg Jensen et al. 2005 documents that firms that have not been using R&D intensively may benefit the most from giving more attention to R&D, while firms that use R&D intensively may benefit the most from focusing more on non-R&D forms of learning and competence building (e.g. learning by doing, using and interacting) (Berg Jensen et al., 2005, 22). The distinction between these two modes of innovation helps on the one hand to avoid a too one-sided focus on promoting science-based innovation of high-technology firms at the expense of the role of learning-based innovation. On the other hand it also indicates limits of experience-based innovation strategies by giving more attention to ‘policies that serve to strengthen linkages to sources of codified knowledge for firms operating in traditional manufacturing sectors and services more generally’ (Berg Jensen et al., 2005, 23). Furthermore, as important as research in engineering, medicine and the natural sciences may be as a basis for many innovations, it is only when such
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new knowledge is used, exploited and diffused that employment and economic growth is created. Knowledge that stays unused in the ivory towers of large firms and universities has practically no effects on welfare, jobs and other socio-economic variables. It is only through application, diffusion and commercialization (i.e. innovations) that society can reap the benefits of inventions and other kinds of knowledge. And these are basically socio-economic and political processes, which have to be studied from a social science perspective. In such processes entrepreneurship, social capital and institutional settings play key roles.
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Why regions? Definition and rationale
The concept of ‘region’ has its origin in the Latin region from regere meaning ‘to govern’. In the field of regional development, this is precisely the sense of ‘region’ intended, namely governance of policies to assist processes of economic development. So, here, the concept ‘region’ as administratively defined is of primary importance. Moreover, taking the administrative dimension as prior means in definitional terms, region is an administrative dimension of a country. The final remaining qualifier is to specify ‘regional’ as nested territorially beneath the level of the country, but above the local or municipal level (Cooke, 2005). Over the past two decades social scientists and policy makes have been paying more and more attention to regions as designated sites of innovation and competitiveness in the globalising economy. Thus, regional innovation systems, learning regions and clusters have been looked upon as policy frameworks for implementing long-term, innovation based regional development strategies. In a recent study Carlsson (2005) shows that the majority of theoretical as well as empirical analyses of innovation systems have a regional focus. However, what is the added value of a regionalization of innovation policy? Even two typical proponents of the national innovation systems approach ‘admit’ that “the region is increasingly the level at which innovation is produced through regional networks of innovators, local clusters and the cross-fertilizing effects of research institutions” (Lundvall and Borràs, 1998, 39). Various other empirical studies across a range of industries and regions observe that both local and distant networks are often needed for successful cooperative innovation projects (e.g. Cooke et al., 2000; Gertler and Levitte, 2005; Isaksen, 2005). Thus, even if the strategic importance of the regional level for constructing regional advantages is underlined, it is still necessary to imply a multi-level approach to innovation and governance. As such, regional innovation systems are open, socially constructed and linked to global, national and other regional systems of innovation within a multilevel governance perspective (Cooke et al., 2000). In a globalising economy characterised by vertical disintegration and distributed knowledge bases, the important perspective must be the interdependences between regions and nations, i.e. implying that non-local relations can be of equal importance to local conditions and relations, especially with respect to creating new knowledge to transcend path dependency and avoid negative lock-in. From a regional perspective what is important is to keep the location of core activities (and not the whole value chain as such) within the region, and to promote this activity through building up systemic relationships with government/governance and the knowledge infrastructure.
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Regionalisation of Innovation Policy In more and more countries innovation policies take place at the regional level. The regionalisation of innovation policy holds the potential for improved ‘on-the-ground’ policy by know-how about the specific conditions of the regional action level. Measures can be formulated, implemented and monitored in a more targeted way, and, thus, be able of addressing more precisely what a particular region or firm needs, or what is lacking concerning innovation, regional proximity and communicative interaction. According to Fritsch and Stephan (2005), regionalisation of innovation policy can imply a variety of things, and, thus, it may be productive to distinguish between different elements of a policy that could be regionalised in some ways (Table 1).
Table 1
Policy element Meaning of regionalisation
Objectives Region-specific objectives vs. nation-wide
Operation In certain regions only vs. nation-wide Instruments Differentiated by region vs. identical in all regions
Administration Within the regions vs. at a central level Decision competencies Regional authorities vs. central body
Finance From within the region vs. from central level
(Source: Fritsch and Stephan, 2005, p. 1124)
However, in the context of explicit tendencies of regionalizing innovation policy it is of vital importance not to forget that in the globalising economy connectivity to distant networks is becoming more of a priority than it was a decade or so ago when the idea of regional innovation systems was in its infancy. Thus, innovation, talent-formation and entrepreneurship have to be considered in triplicate to construct regional advantage in ways that intersect profitable with regional, national and global innovation imperatives.
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Constructing Regional Advantage (CRA) Taking this as a point of departure the aim of this report is to proceed further in strengthening this approach by asking how the capacity for knowledge creation and exploitation in the context of regional innovation systems can be developed as a means to constructing regional advantage. This is the result of the increasing global competition from newly industrialised countries such as Taiwan, South Korea, Singapore, and rapidly catching up countries such as China and India. The new economic landscape has emphasised the need for firms in Europe to enhance their competitiveness by combining a focus on product differentiation/innovation with cost efficiency. Subsequently firms apply an open innovation model1 and thus rely on sourcing – sometimes globally – for the best talents while at the same time outsourcing or offshoring standardised labour-intensive activities to low-cost countries. In this vein we concur that constructed advantage is regarded as the next evolutionary step in regional economic development (Cooke and Leydesdorff, 2006). While the theory of comparative advantage is criticised for dismissing the role of technological change and innovation altogether, the theory of competitive advantage is also considered too narrowly market focused. The theory of constructed advantage allows for more attention to the role and impact of the public sector and policy support, preferably in public-private partnerships, by acknowledging to a greater extent the importance of institutional and economic complementarities in knowledge economies than theories of comparative and competitive advantage do. Institutional specificities constitute the context within which different organisational forms with different mechanisms for learning, knowledge accumulation and knowledge appropriation evolve. Instead of market failure, the rationale for policy intervention is the reduction of interaction or connectivity deficits which lies at the core of a networked regional innovation systems approach. However, after years of influential research on the importance of territorial agglomerations for economic growth there is a need for an ‘unpacking’ strategy to disclose and reveal the contingencies, particularities and specificities of the various contexts and environments where knowledge creation, innovation and entrepreneurship take place in order to obtain a better understanding of factors enabling or impeding these processes, as a preface for constructing regional advantage. So far, all the way from Marshall’s writing on industrial districts, it has been assumed that business interactions (from exploiting localisation economies) and knowledge flows were co-occurring (and co-located) phenomena (Asheim, 2000). Furthermore, it has been maintained that local interactions and collective learning processes, or what is sometimes called ‘local buzz’, largely take care of themselves by just ‘being there’, while building ‘global pipelines’ to knowledge providers located outside the local milieu requires institutional and infrastructure support, as one cannot expect that it occur spontaneously (Bathelt et al., 2004).
1 The central idea behind open innovation is that in a world of widely distributed knowledge, companies cannot afford to rely entirely on their own research, but should instead source knowledge ideas from other companies or research organisations (Chesborough, 2003).
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It is this idea of an almost automatic shaping of endogenous learning and innovation capacity by just being co-located in an agglomerated environment, which also lies behind Porter’s understanding of how competitive advantage is created (Porter, 1990). However, lately it has been shown empirically that there exists an uneven distribution of knowledge and selective inter-firm learning due to the heterogeneity of firms’ knowledge bases, which cannot be fully compensated by regional universities or other parts of a region’s ‘collective absorptive capacity’ (Giuliani and Bell, 2005). Therefore, it is an important question if firms can take up this challenge of strengthening their knowledge bases by themselves. Can they just on their own initiative start cooperating with neighbouring firms and knowledge creating and diffusing organizations co-located in clusters? Accordingly, changing their behaviour to become more innovative is one option, but more planned and systemic approaches are another in a globalising knowledge economy in order for regional advantage to be deliberately constructed. This argument is grounded in the observations that in the contemporary globalising economy simply leaving the question of how competitive advantage is achieved just to the market or the ‘territory’ in the Marshallian way is not enough. The idea, then, that in the future it will not be sufficient to rely on competitive advantage just to be created but that it needs consciously and pro-actively to be constructed, has the understanding of the challenge the EU faces in a globalising economy as the point of departure. This point to a new and more dynamic role for the public sector (including universities) generally and government and governance specifically in interaction with the private sector (see appendix for a more elaborated discussion).
Perspectives and methodologies for policies of CRA Given this context as well as challenges it is not the aim of this report to offer precise or specific recipes for the process of planning and implementation of regional policies for R&D and innovation. More precisely, a wide variety of case studies are available about (mostly) successful and (more rarely) unsuccessful regional cases (see text boxes). Also several theoretical and empirical contributions exist, which aim at providing insights, guidelines and/or indicators to policy makers (see appendix). Most of these contributions are surely useful, but it is the view of this report that the planning and implementation of regional policies for R&D and innovation is an activity which should be based on a more general framework of perspectives and methodologies rather than on precise and rigid technical schemes. The idea that it is possible to design ‘one size fits all’ regional policies is neither supported by theory nor by empirical analyses, and is, thus, rather difficult to entertain in a Europe characterised by large scale and developmental diversity. Past experiences, concrete cases, theories and models represent the background which policy makers should work with in order to find their own (regional) solution, rather than the exact replication or ‘cloning’ of more or less successful examples of regional policies from elsewhere, often from places with very different economic and socio-institutional environments. Copying of best practices is almost impossible when it comes to intangible regional assets (such as particular knowledge bases or institutional settings) that are the results of long histories in particular regional contexts. Policy
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makers should therefore be reflective upon this and reluctant to simply imitate successful models.2 Nonetheless, some general perspectives do exist which should be taken into account as supporting substantiation of methodologies that policy makers can make use of to formulate and implement the new type of regional policies as well as to influence their outcome. There is no widespread knowledge and absorption of such a general framework of perspectives and methodologies, and it is therefore the intention and aim of this report to make a contribution to policy makers by identifying and describing these ideas rather than trying to provide specific and elaborated recipes. On the contrary, we would rather make policy maker’s job more challenging by making them responsible for finding their own way, rather than asking them to choose from a portfolio of specific models or recipes. Regional policy in a diversified, globalising economy does not work in this way; it is rather a mosaic which has to be built with pieces which are not pre-determined. Of key importance in this context is the recognition of institutional and governance capabilities in regions, taking into account variation in the quality of regional communication infrastructures, understanding the knowledge base strengths of the region, and presuming that true regional innovation system connectivity is not complete in most regions.
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2 By this we of course do not mean that studying and benchmarking other regions have no value in a policy making process.
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Background and pre-conditions for constructing regional advantage
Regional endowments The reference to regional endowments covers the historical and geographical background as well as contemporary economic and socio-institutional and political conditions, which taken together represent important factors explaining regional diversity among EU regions today. A region’s access to natural resources, the degree of centrality and connectiveness with respect to its geographical location and the size of its population represent important pre-conditions for economic and social development. However, without historically and culturally conducive structures as well as a stable socio-political environment and sufficient developed knowledge infrastructures and institutional density or thickness, a consistent and progressive development process will not appear. Thus, any regional development process can be considered as a combined outcome of interrelations of new spatial structures, as a result of technological development and intensified competition, with the accumulated results of the old and existing regional structures, with each side of the process affecting the other. Such development processes produce regions with varied and diversified characteristics, which can be described using the following typology (based on Tödtling and Trippl, 2005):
• Peripheral regions are characterised by being less innovative in comparison to more central and agglomerated regions; they have less R&D intensity and innovation, and have a less developed knowledge infrastructure (universities and R&D institutions) as well as suffer from organizational thinness (see box 2);
• Old industrial regions represent another type of problem region characterised by negative lock-in due to a heavy dependence and specialisation on mature industrial sectors. If knowledge infrastructure exists, it is often also strongly specialized in training and research activities in support of the dominating industrial structure. The innovative activity of these regions is primarily concentrated on process innovations, and there is a lack of product innovations as well as entrepreneurship;
• Fragmented metropolitan regions. Metropolitan regions are normally regarded as centres of innovation with the presence of R&D organizations and universities, business services, as well as headquarters of international firms. As a consequence, R&D activities are usually above average. However, some metropolitan regions are lacking dynamic clusters of innovative firms due to the problem of fragmentation, i.e. the lack of innovative networks and interaction between universities-firms as well as among local companies. Such regions display an industrial structure characterised by so called ‘unrelated variety’, i.e. by having a diversity of sectors which do not complement each other, and, thus, do not produce knowledge spillovers. This may represent an important innovation barrier in such
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regions resulting in the development of new technologies and the formation of new firms often being below expectations.
• Innovative regions. Regions with cutting edge technologies and a high level of R&D which, however, in increasing degree are exposed to challenges and competition from emergent economies (especially from Asia). Such regions have the best conditions for constructing regional advantage, but in order to do this efficiently they will have to diversify into new but related sectors as well as avoid negative lock-in in existing sectors by securing their competitiveness through continuous innovation supported by clusters and regional innovation systems.
BBooxx 22
How to transform an industrial district in crisis in the periphery of Europe?
The case of the Barletta footwear district The evolution of the footwear district of Barletta tells a story of an industrial district in crisis in one of the most peripheral parts of Europe. Located north of the city of Bari in the South of Italy, the heydays of this district were in the 1970-1990 period, during which employment growth rates were sky-rocketing. Since the 1990s, it has been hit hard by a long and deep economic crisis. As other districts, the Barletta district, which is one of the very few districts in the South of Italy, has been confronted with increasing competition from low-cost countries like China. Till now, it has been unable to respond to the crisis, and its future prospects are dim.
The structure of the local knowledge network in the Barletta region is extremely weak, and many local firms are not connected (Boschma and Ter Wal, 2005). Firms tend to operate on their own, and they regard their own internal knowledge base as the most important source of knowledge. Firm-specific features like their absorptive capacity contributed to the innovative performance of the Barletta footwear firms, in contrast to external sources of knowledge. This dependence on internal sources of knowledge and the presence of quite weak local knowledge relationships may have something to do with a lack of social capital that is often found in the South of Italy (Evangelista et al., 2002). In practice, it has proved difficult in many cases to tackle this fundamental institutional problem in the South of Italy. This is certainly not something that can be solved in the short-term. That may already be too late anyhow for the majority of footwear firms in the Barletta district. It is expected that only a few large firms will survive, and these firms can only do so through the adoption of an international strategy in which at least footwear production will move out of the area. The example of the Barletta district suggests how difficult it may be to construct regional advantage in such circumstances, and how unrealistic it might be to expect that the district model that worked well in other more favourable parts of Italy is a panacea for the development of the South of Italy. However, this example also shows the strong need of intelligent policies in specialized regions that aim at broadening their regional economic base.
Sources: Boschma, R.A. and A.L.J. ter Wal (2005); Evangelista, R., Iammarino, S., Mastrostefano, V. and Silvani, A. (2002).
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Often combinations of the above categories of regions will exist, e.g. that old industrial regions end up as peripheral regions and that fragmented metropolitan regions basically are old industrial regions. However, the point here is that these types of regions represent different problems and challenges, and, thus, require specific and individual approaches to innovation policies in order to correct problems and promote economic and social development (see boxes 3 and 4). (For an illustration of dynamism in different regional systems see figure 1).
BBooxx 33 Emerging new multicentre
Vienna-Bratislava metropolitan area (VBMA) Creating regional advantage had for a long time not been any urgent policy issue in Slovakia. Starting reforms after 1989 and increasing competition in pre-accession period has gradually attracted attention of politicians to look at more complex economic issues. This relates to economic competitiveness at national, regional and corporate levels. After a decade of transition reforms focused on privatisation, employment, macroeconomic stability and enterprise restructuring, more importance has started to be given to building of regional identity and competitiveness and fostering cross-border cooperation.
Nowadays Slovakia represents a country with high regional economic and social disparities. Therefore, only limited opportunities exist to equally develop each region. So far it is evident that the country’s conditions favour its asymmetric development. Thus more dynamic development is reported in the Western part of Slovakia, especially around capital Bratislava. However, the government try to implement and develop nation-wide policy aimed at improvement of innovative capacity of business/non-business actors through, e.g., MINERVA programme, which represents a national form of Lisbon programme.
As it involves a higher concentration of business/non-business actors, activities and competition, Bratislava has begun to cooperate within a two country area (Vienna - Bratislava metropolitan area –VBMA). This generates both potential challenges as well as threats. Such changes can bring numerous opportunities for future progress (more innovative activities), but on the other hand the cross-border metropolitan area actors have a problem, how to effectively govern and formulate joint strategies and how to balance competitive and cooperative elements of their activities. It requires intensive and complex negotiations between different international actors.
Twin city Vienna-Bratislava is clearly at the start of emergence of such changes. To be successful in its way to CRA, it requires from policymakers to use R&T policies to generate: (a) critical mass of institutional density (as an additional factor to the OLI factors); (b) critical mass of institutional flexibility; (c) critical mass of technical infrastructure; (d) critical mass of educated workforce with tacit knowledge.
To increase dynamics of structural changes, however, the economy needs to generate these competitive features permanently to attract high-technology firms. In this context, the economy should act as a hub for coordinating research activities; initiate and develop leading edge research facilities; increase public investment in education; and continue to change regulation to meet international competitive criteria. The government has to ensure that managing of such changes is efficient, rapid and flexible. It can encounter many problems in their implementation but need to be successful for VBMA to be able to compete/cooperate with others. In this process parameters of national economy/policy play only limited role and the process should be put in a more open and flexible context.
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With EU integration, competition may bring about greater pressure for innovativeness and flexibility. In this situation networking and clustering is currently presented as a way for improvement of R&T and knowledge capability in Slovakia/VBMA. Without changes of their reluctance to intensive cooperation, also the position of Slovak firms can worsen and lead to the position of a supplier of simple parts with low value added. Abroad, such firms operate in specialized clusters of SMEs, which governmental and regional programs support. A failure to enhance new approach to innovation and governance can increase the probability that firms would not innovate enough to become competitive.
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BBooxx 44 Challenges for regions less successful in innovations
The case of Prague Prague is a city-region which concentrates about half of the potential of R&D and innovation of the Czech Republic, but this potential is not fully exploited. In 2005, the first innovation strategy of this city called “Bohemian Regional Innovation Strategy” (BRIS) has been adopted. The key weaknesses and challenges of Prague in this sphere will be elaborated.
The key problems that have until recently hindered the development of coherent innovation policy at the regional level are: (i) Lack of sufficiently strong regional actors competent and qualified to design and deliver innovation policy; (ii) Lack of genuine partnership in defining development priorities that should be based on mutual respect among the key players and should reflect longer term development ambitions and needs of the business sector; (iii) Lack of awareness on the side of policy makers of the importance of research and innovation for long-term development of the region. General obstacle to enhancing innovation culture at the regional level is a wide-spread lack of trust, co-operation and a weak application of the principle of partnership. Moreover, the culture of efficient usage of strategic/programming documents for steering the development of Czech regions is still in its infancy and strategic documents are still often considered by many actors as a mere exercise without practical relevance.
The key challenges for enhancing innovation potential in Prague can be structured into two groups according to the level from which they should be predominately addressed (i.e. national versus regional level). The main themes to be addressed from the national level are the general legislative environment for business, an introduction of sound evaluation criteria for public research institutes with implications for their financing, marketing of innovations, patents but also of National Innovation Policy itself, strengthening the financial mechanisms for innovations (“seed” capital, venture capital etc.) and elimination/moderation of current de-motivating working conditions for R&D employees, especially the young ones.
At the regional level, the key challenges are: an establishment of the links between innovating multinationals located in Prague and the endogenous firms as 60% of R&D private expenditures are provided by foreign firms in the Czech Republic; strengthening of the links between the public research institutions, private firms and other actors relevant for innovations; shifting of a focus of public support from the institutions to the projects aiming at delivering of needed changes (the existing policies and strategies are often mixing up the objectives and tools. Public support is often oriented to institutions with ‘correct’ name such as ‘Science and Technology Park’ or ‘SMEs incubator’ instead of on support of desirable activities leading to measurable changes). Finally, there is need to more active marketing of
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both BRIS and innovations created in Prague.
When assessing the document “Bohemian Regional Innovation Strategy”, several key weaknesses can be identified: 1) analytical part is rather of traditional nature without focusing on softer issues like analysis of interactions among the subjects including their types and ways of measurements, identification of potential leaders, why some existing bodies are not functioning properly, what are the routines that prevent standard support mechanism from functioning effectively etc.), 2) not sufficient effort to identify sectors with the largest innovation potential, 3) missing clear priorities, the strategy is “to improve everything”, 4) missing link to budget of City of Prague, 5) missing clear responsibility (and time-schedule) for implementation of actions, 6) insufficient political backing and commitment from the elected regional representatives.
A major recent positive development is an effort to integrate BRIS into city Strategic Plan. If BRIS is incorporated into Strategic Plan as envisaged, several of the above mentioned weaknesses would be eliminated as issues of innovation would be put into the mainstream policy and as such regularly monitored. However, the real impacts of these emerging activities are inevitably of medium- or even of a long-term nature and require a steady political commitment without disturbances related to political cycle. (For more see www.bris.cz)
Figure 1: A synthetic representation of dynamism in regional systems Source: Lazzeroni, M. (2001)
Such differences in regional endowments also become manifest as variations in regional knowledge economies (which is most relevant for the focus of this report, and measured as share of employees in high-tech industries and knowledge intensive business services (KIBS)). Regions in EU span from top ranking metropolitan areas such as Stockholm and London with an index around 170 (EU average is 100) to peripheral regions in Greece slightly above 35, based on EU 15 (see Table 2):
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High Index Low Index
Stockholm (S) 169.5 Notio Aigaio (Gr) 36.7
London (UK) 166.8 Sterea Ellada (Gr) 38.4 West Sweden (S) 155.2 Peloponnissos (Gr) 43.9
Surrey & Sussex (UK) 153.6 Anat-Maked-Thraki (Gr) 46.4 Brabant Wallonie (BE) 152.4 Norte (P) 50.2
London O. (UK) 151.6 Dytiki Ellada (Gr) 50.9 Piemonte (I) 150.7 Kriti (Gr) 50.9
Ostra Mellan Sweden (S) 150.0 Centro (P) 51.1 Berkshire-Oxford (UK) 149.0 Dytiki Makedonia(Gr) 51.6
Bedford-Hertford (UK) 148.9 Alentejo (P) 53.8 Uusima (Helsinki) (Fi) 148.8 Ionia Nissia (Gr) 53.9
Ovre Norrland (S) 148.4 Algarve (P) 54.7 South Sweden (S) 148.1 Thessalia (Gr) 55.2
Mellan Norrland (S) 147.6 Ipeiros (Gr) 59.6 Brussels (BE) 145.0 Castilla la Mancha (ES) 60.6
Paris (F) 144.9 Voreio Aigaio (Gr) 62.3 Norra Mellan (S) 143.3 Kentriki Makedonia (Gr) 62.7
Hampshire (UK) 141.6 Murcia (ES) 64.1 Stuttgart (G) 141.1 Estremadura (ES) 64.9
West Midlands (UK) 140.1 Balearics (ES) 65.3 EU 100.0
Table 2: Knowledge Economies Index Numbers, European Union (15)
(Source: Cooke and De Laurentis, 2002)
According to Cooke and De Laurentis (2002) cities on average are twice as advantaged by their knowledge intensity over towns and rural areas compared to their already existing advantages from agglomeration economies. Thus if a city scores 50% above the mean in GDP per capita it is likely to score 100% above it in terms of its knowledge-based industry. Thus there is more chance of knowledge economy employment in the city than the country, a major contributory factor in the renewed migration of young people from rural to urban areas in many European countries, making the knowledge economy uneven geographically distributed and knowledge poverty a new kind of locational disadvantage (Cooke and De Laurentis, 2002) (see box 5).
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BBooxx 55 Promoting Innovation in Less Favoured Regions
The experience of North Aegean The region of North Aegean, despite significant progress made during the 90s, was still one of the poorest regions in EU-15 at the end of the century (with regional GDP per head amounting to 92% of the national and 60% of the European average). The physical infrastructure had improved considerably during the 1994-99 planning period (as for the majority of all Greek regions), whereas intangible (soft actions) and environmental protection was significantly lagging behind. The region’s geomorphology (big islands distant from the mainland as well as one from the other) and subsequent administrative organisation (one main administrative centre with insufficient communication throughout the islands) leaves limited room for the design of a successful development strategy for the region as a whole and an innovation strategy in particular. The lack of a Regional Innovation System and the size of the SMEs of the region (normally quite small–staff average of 4 persons) that suffer from its insular and double (both national and European) border character, with high transport and communication costs and limited access to information as main disadvantages, had discouraged innovative behaviour and had not created the necessary environment for the effective offer of technology services.
The Region of North Aegean (Regional Authority) took the initiative (in the framework of the RITTS Programme) to assess the available technology transfer support infrastructure and promote the development of an Innovation and Technology Transfer (ITT) strategy in the region, aiming to find out what type of innovation support the region’s enterprises need, gain a better insight in the economic structure of the region and focus regional innovation policy in targeted areas (e.g. waste management of olive oil production, an important economic activity of the region).
The RITTS – Innovation in North Aegean (INA) Programme, through systematic publicity actions and a series of technical meetings, reached a sufficient level of consensus and concluded with the formulation of the Region’s Innovation Technology Transfer Strategy & Action Plan. In its framework, significant involvement of local actors was achieved that led to the establishment of a network of effective partnership among key regional stakeholders.
What is most important, the RITTS – INA Programme did not result simply to regional innovation strategy formulation, but managed to incorporate its Action Plan into the main strategic and financial tool of the region for the current programming period, the Regional Operational Programme (ROP) of the Region of North Aegean 2000-2006 (3rd CSF), addressing a broad range of issues, which include, among others, SMEs support actions, innovation promotion, human resources, protection of the environment, telematic applications as well as research and production linkage.
Although this exercise could be considered successful and the leading role of the regional government was found critical for its success, the challenge of continuity of the above effort still remains, both for the regional authority (dependent to the central Government on policy issues, as applies for all regions in Greece) to prove its ability to support innovative behaviour and facilitate the increase of the absorptive capacity of the region as well as for the regional stakeholders to show commitment in adopting innovative approaches in their organizational /entrepreneurial operations and eventually taking investment decisions to innovate. Source: Cyclotron Ltd, Consulting Engineers, www.cyclotron.gr
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Evolutionary perspectives Regional development must be understood as an evolutionary process, i.e. as being based on path dependent technological trajectories: Boschma and Lambooy (1999); Boschma (2004; 2005a); and Boschma and Frenken (2006). According to evolutionary thinking the historical trajectory of a region sets serious limits to the windows of opportunity with regard to relevant policy options as well as to copying an external model that owed its success to its deep roots in an alien environment. Furthermore, an evolutionary perspective also implies that changes in industrial structure, innovativeness and competitiveness take time. An important aspect of this perspective is also the lock-in problematic, which was discussed in the context of old industrial regions. If the scope is widened to take into account the formation of broader socio-institutional factors, such as the building of social capital and similar institutions such as trust, conducive to the promotion of innovativeness in an economy, the time perspective is even more emphasised. Social capital refers to various ‘soft’ but fundamental features of the organisation of firms and regions such as shared norms and values that facilitate coordination and co-operation among individuals, firms and sectors to their mutual advantage. When innovation is understood as based on interactive learning, organisational innovations on different levels in society (micro, meso and macro) that promotes cooperation, will potentially contribute to more interaction and, consequently, more innovation. The presence of social capital is seen as an important facilitator of implementing such organisational innovations leading to increased cooperation and interaction. Social capital can either be of the ‘bonding’ type, rooted in the civil society, or of the ‘bridging’ type, which refers to social capital being created or built as a consequence of collective social and political actions resulting in organisational and institutional innovations. Examples of such ‘building’ processes is various networks programmes directed towards SMEs on the meso level, and collaboration between trade unions and confederation of industries on the macro level, which e.g. underpins the well-functioning Nordic labour markets. In the context of constructing regional advantage the latter type of social capital is most relevant, as it can be created or achieved, while the former type only can be built on if it already exists in a region. However, building such social capital is indeed a time-consuming process, which has to be deeply contextualised in the individual region, and cannot rely on straight forward recipes. An illustrating example of the evolutionary aspects of a successful innovation policy is the Finnish example. Another example of an evolutionary development process could be Grenoble (see boxes 6 and 7).
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BBooxx 66 The experience of Finnish science and innovation policy
In the last decade, the Finnish economy has shown an unprecedented recovery, after being hit by a deep crisis in the early 1990s. This is attributable to a considerable degree to a rapid development in the ICT sector. What makes Finland an interesting case from a policy point of view is that it has been able to break out to a new path and dissociate itself from its previous path, from its strong dependence upon raw-material driven production and export.
Although the rapid pace of the restructuring of the Finnish economy might suggest a break with the past, this remarkable recovery was firmly rooted in its economic history. The foundations for the emergence of the ICT sector were laid down throughout the last century. Early and strong competition (including from foreign companies like Ericsson and Siemens), demanding customers (especially network operators), early standardization (such as the Nordic Mobile Telephone Standard and the GSM system), and a culture open to the adoption of new technologies contributed significantly to the growth of the ICT industries.
In addition, Finnish public policy played its role in turning Finland into a knowledge economy. Although a master plan for the Finnish economy was lacking, many policies worked out quite well together over an extended period. Public involvement started already many decades ago. Since the 1960s, education policy was already focused on securing a sufficient supply of specialized skills in ICT. Building on education, research and technology policy initiatives were taken in the 1970s and 1980s: national technology programs, among other things, were set up, and technology transfer and commercialization of research became key objectives. Finally, the deep economic crisis in the early 1990s paved the way for new policy directions, with its focus on network and cluster-facilitating innovation policies. The concept of national innovation system was introduced as a framework for science and technology policies to accentuate the systemic nature of innovation.
What the Finnish case has demonstrated is that policies should be firmly embedded in national and regional strengths, rather than being swayed by wishful thinking and popular world-wide buzzword chase. It is also clear that innovation policy ought to have a long-term strategic perspective. Hence, policies must be consistent in the long run, and should not be dictated by short-term cyclical or political considerations. The chances of being successful most likely increase when policies aimed at stimulating new growth paths build on economic and institutional structures laid down in the past. For the remaining, a bit of luck is needed.
Source: Boschma, R.A. and M. Sotarauta (forthcoming).
BBooxx 77 Grenoble: Building a world class “pole”
Grenoble has a long history of industry, training and research associated to the development of electricity. It benefited after the second world war of the development in high energy physics with the location of large instruments culminating with the ESRF synchrotron radiation facility. Grenoble was also the location of the microelectronics labs developed by the French Atomic Energy Commission (CEA), LETI. It generated one of the first start-ups in the 1970s, now at the heart of ST-Microelectronics. The creation and development of high technology firms was boosted by the first French “technopole” (the ZIRST de Meylan was developed before the name was created). All this made the area very attractive for students (with both one of the French largest engineering ‘schools’, INPG, and with a well known research university, UJF) and it turned into one of the biggest agglomeration of start-up
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firms mostly focused on ICT, with incubating facilities, large presence of seed and venture capital and very active support from the local development agency.
Though it was very successful, some local actors felt that it was endangered by both the changing world landscape and the advent of nanoelectronics. Three aspects were put on the forefront: the size of facilities needed, the breadth of competences required (far broader than engineering and computer sciences) and the changing innovation process (with the need of new types of research and new types of centres). As early as 2000, two major public actors (LETI and INPG) proposed a radical shift gathering into one new space their teaching and research facilities while including in the same space, facilities for industry research labs as well as a “house for micro and nanotechnologies”. The concept of MINATEC was born. Within two years, the city, the district, the department and the region allied to support the project and provide 90% of required support driving to a 142 million euro investment (the new facilities will be fully operational in September 2006 and should house 3500 students and researchers).
This triggered the credibility of the area in term of world level public capabilities and was critical in the development of the “alliance” between ST-Microelectronics, Philips and Flextronics around the Crolle 2 “lab-fab”, a 2.8 billion euros investment over a 6 year period. Here national policies were instrumental in accompanying the location of research facilities of world players.
The third layer of initiatives dealt with “related variety”, and the articulation of nanoelectronics with telecommunications, energy, multimedia and biotechnology. The nanobio platform articulates all the public facilities from Grenoble, it is also the home of one of the two nanobio EC “networks of excellence”, Nanotolife.
All these initiatives are now articulated in the new Minalogic pole which gathers local authorities with firms and public research and teaching capabilities. This was an answer to the new approach proposed by the French national government about “Poles de compétitivité”, a competition launched in 2005 open to all areas and sectors with selection criteria based upon the articulation of actors for the promotion of the international competitiveness of firms.
For further information, see research work developed by the Nanodistrict project within the PRIME Network of excellence (www.prime-noe.org and www.nanodistrict.org)
The history of Grenoble in the making highlights three major aspects: (1) the importance of multiple levels of intervention and their articulation. It is not only a story of regional, national and European public policies, it is also, and probably even more important, a story of coordinated public local interventions (here 4 layers from the city to the region). (2) It also shows that crystallisation might be short (here just over 5 years) but that this was achieved on 30 years of previous policies and a well developed infrastructure where tools to support entrepreneurship have been long rooted in the landscape. (3) This is also a story on policies that to a limited extent has addressed the citizens and their questions about ethics and risks, leaving room for very strong (even if marginal) opposition. Promoting a creative and receptive space also requires addressing these issues, at least in European societies.
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Content of policies for constructing regional advantage
Proactive and system/platform oriented policies: Requirements for constructing regional advantage A focus on constructing regional advantage requires an ‘unpacking’ of what makes territorial agglomerations important for innovation and growth by disclosing and revealing the various contexts and environments where knowledge creation, innovation and entrepreneurship take place. In this report we propose to carry out such unpacking along the following three dimensions: (1) related variety, (2) differentiated knowledge bases, and (3) distributed knowledge networks, which taken together provides the fundament for formulating sectoral transcending platform oriented policies. Moreover, in order to have an improved understanding of how different regions and sectors are coping with globalisation the institutional framework also needs to be taken into consideration. Lam (2000) underlines that learning and innovation cannot be separated from broader supporting institutional and regulatory framework. However, as the focus of this report is on regions, and such frameworks typically are national and/or supra national, they are not explicitly dealt with in the report (see Asheim and Coenen, 2006, for such an analysis). First, the traditional dichotomy between specialised localisation economies and diversified urbanisation economies ought to be further developed by introducing a distinction between related variety (accounting for spill-over effects) and unrelated variety (covering the portfolio effect), because they mean different things, and they have impacts on different performance indicators. Related variety in many ways combines the strength of the specialisation of localisation economies and the diversity of urbanisation economies. Secondly, differentiating between industrial knowledge bases represents another dimension of such an ‘unpacking’ strategy (Asheim and Gertler, 2005; Asheim and Coenen, 2005). We argue that the innovation process of firms and industries is strongly shaped by their specific knowledge base. In this report, we distinguish between three types of knowledge base: ‘analytical’, ‘synthetic’ and ‘symbolic’. These types indicate different mixes of tacit and codified knowledge, codification possibilities and limits, qualifications and skills required by organisations and institutions involved, as well as specific innovation challenges and pressures (Laestadius, 1998). Thirdly, it is important in the discussion of preconditions for constructing regional advantage to shed light on how knowledge bases of different sectors are changing as a consequence of globalisation. In order to fully grasp the dynamics of these changes a globalisation perspective must explicitly be taken into consideration to modify the endogenous perspective, which has dominated the research on clusters and RIS so far, by introducing a
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distributed knowledge network perspective, which more and more are manifested in global value chains organised by TNCs. These ‘unpacking’ efforts will provide a better basis for - and, thus, improve the capacity of - policy makers on different geographical levels to formulate dedicated and specific innovation support customised to different regions and sectors, which will be in increasing demand if regions in high-cost countries shall be able to compete and survive in a globalising learning economy. Especially important is, of course, to be able to formulate and pursue the formation of necessary capabilities in regions without existing capabilities to construct regional advantage.
Related variety Since Jane Jacobs diversity in urban or regional economies is regarded as one of the driving forces of economic growth. It stimulates new ideas and creativity, it gives access to complementary resources that might be essential for innovation processes, and it reduces the risk for a sector specific shock harming the whole of local economies. However, a distinction can be made between related variety (accounting for spill-over effects) and unrelated variety (covering the portfolio effect), because they mean different things, and they have impacts on different performance indicators. Unrelated variety is defined as a diversity of sectors in a region that do not complement each other. As such, it is expected to protect a region from an external shock (e.g. fall in demand in one particular sector). This risk-spreading effect (or portfolio effect) of regional diversity dampens regional unemployment. Instead, related variety is expected to have a positive effect on regional development, because knowledge is likely to spill over between complementary sectors. That is, their co-location may provide an extra source of knowledge spillovers and innovation, and thus, cause additional economic growth. When constructing regional advantage a policy framework that is based on a related variety approach may be highly relevant. Firstly, studies (Frenken, Van Oort, Verburg and Boschma, 2004) have demonstrated that it is actually one of the driving forces behind urban and regional growth. Secondly, the risk of selecting wrong activities is reduced when the region-specific context is taken as a point of departure. This would mean that regional competences are used as building blocks for the purpose of broadening the economic base of a region. Thirdly, such policies acknowledge the fact that generic technologies (like ICT) may have a huge and pervasive impact on economic development, due to the many potential fields of application, such as giving birth to many new sectors (creating new related variety). In other words, constructing regional advantage based on related variety may combine the advantages of regional specialization in complementary sectors (including knowledge spillovers) with the advantages of regional diversity, dampening the risk of sector-specific shocks (see box 8): Boschma (2005b).
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BBooxx 88 The importance of a generic knowledge base
The case of the Emilia Romagna region The Emilia Romagna region in Italy is one of the wealthiest places in Europe, and it is home of many successful industrial districts. Its recent economic history tends to give witness to the economic significance of related variety at the regional level. Already for many decades, Emilia Romagna is endowed with a diffuse knowledge base in engineering. After the Second World War, new sectors emerged out of this pervasive knowledge base one after the other. An expanding ceramic tile sector in the Sassuolo area mushroomed on its foundations, which was soon followed by the rise of specialized producers of machinery for ceramic tile production that employed about 7.000 people alone in the 1990s. Luxury car manufacturers (like Maserati and Ferrari) built on it, robotics became a successful new application in the region, and the packaging industry in Bologna drew heavily on it, as producers in agricultural machinery, among other sectors. These new sectors not only built on this extensive regional knowledge base, they also renewed and extended it, further broadening the regional structure.
The Emilia Romagna experience tends to suggest how a generic knowledge base may have a huge and pervasive impact on economic development, due to the many potential fields of application, such as the giving birth to many new sectors. Although in the Emilia Romagna case, policy making was certainly not the driver of this process (for sure, there was no master plan and no top-down policy model involved), its experience may shed light on how policies aimed at creating new ‘related variety’ may work in practice. Constructing regional advantage based on related variety may lead to more sustainable regional development. For instance, it combines the advantages of regional specialisation in complementary sectors, which induces inter-sectoral knowledge spillovers at the regional level, with the advantages of regional diversity that may dampen the economic consequences of a sector-specific crisis in the region. Another advantage of such policy objective is that the region-specific context is taken as a point of departure. This means that regional competences are used as building blocks for the purpose of broadening the economic base of a region.
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Differentiated knowledge bases Regions in EU display, as seen above, a large diversity when it comes to industrial structure, innovative capacity, competitiveness and economic growth with severe consequences for the level of living standard of their population as well as impact on social cohesion. One way of analysing regional diversity with regard to its implication for regional economic development is to apply an industrial knowledge base approach. The knowledge creation and innovation processes have become increasingly complex in recent years. There is a larger variety of knowledge sources and inputs to be used by organisations and firms and there is more interdependence and division of labour among actors (individuals, companies, and other organisations). Following Archibugi and Lundvall, (2001) we recognise the increased importance of knowledge creation in all segments of society and economy, including traditional industries, services, and emerging sectors such as creative industries. But this does not mean that R&D and the level of technological complexity are the only indicators of knowledge intensity and innovativeness. All economic activities are based on knowledge and learning, also the ones commonly referred to as low-tech (Smith, 2005). Nonaka and Takeuchi (1995) as well as Lundvall and Borrás (1998) have pointed out that the process of knowledge generation and exploitation requires a dynamic interplay and transformation of tacit and codified forms of knowledge as well as a strong interaction of people within organisations and among them. Thus, the knowledge creation process becomes increasingly inserted into various forms of networks (at regional, national and international levels). Gibbons et al. (1994) have been arguing that the process of knowledge production is moving from the traditional disciplinary and Newtonian model (Mode 1) towards a new mode (Mode 2) which is described as knowledge production in the context of application, marked by transdisciplinarity and heterogeneity. Despite the generic trend towards increased diversity and interdependence in the knowledge process, we argue that the innovation process of firms and industries differ substantially between various sectors, whose activities require specific ‘knowledge bases’ (Asheim and Gertler, 2005). In this study we distinguish between three knowledge bases (and related activities): ‘analytical’, ‘synthetic’ and ‘symbolic’. This typology encompasses and acknowledges the diversity of professional and occupational groups and competences involved in the production of various types of knowledge. As an ideal type, a synthetic knowledge base is critical for activities where innovation takes place through the novel combination of existing knowledge. Therefore a common social and institutional context is considered as a prerequisite for interactive learning processes. The main rationale for knowledge creation is the construction and improvement of a functional system that works as a solution to a practical problem. An analytical knowledge base is critical for activities where knowledge creation is based on formal and codified scientific models. The main rationale for knowledge creation is to understand and explain features of the universe. Activities that draw on a symbolic knowledge base are more directly dependent on informal interpersonal interaction in the professional community. Main rationale of these activities is creation of alternative realities and expression of cultural
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meaning by provoking reactions in the minds of consumers through transmission in an affecting sensuous medium (see appendix for more detailed explanations). Table 3 provides a summary of the main differences between the knowledge bases. But as this threefold distinction refers to ideal-types, most industries are in practice comprised of all three types of knowledge creating activit ies. The degree to which certain activities dominate, is however different and contingent on the characteristics of the industry (see figure 1 for an illustration).
Table 3: The three knowledge bases
Figure 2: Knowledge bases and industries: an illustration
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Distributed knowledge networks Another policy challenge is represented by the transition from an internal knowledge base of firms to (more and more) open and globally ‘distributed knowledge networks’ (e.g. as part of global value chains organised by Transnational Companies (TNCs) or globally dispersed epistemic communities of scientists (Amin and Cohendet, 2003)). This is accompanying the characteristic feature of the globalising, post-Fordist economy of outsourcing and offshoring the production of goods and services to subcontractors and suppliers as a result of the development from vertical integration to vertical disintegration in the organisation of production. The concept of globally distributed knowledge networks is understood as “a systemically coherent set of knowledges, maintained across an economically and/or socially integrated set of agents and institutions” (Smith, 2000, p. 19). Much of the knowledge intensity enters as embodied knowledge incorporated into machinery and equipment, or as intermediate inputs (components and materials) into production processes. More importantly, knowledge flows can take place between industries with very different degrees of R&D-intensity and different knowledge base characteristics, e.g. when food and beverages firms (predominantly drawing on a synthetic knowledge base) produce functional food based on inputs from biotech firms (predominantly drawing on an analytical knowledge base). This also weakens the importance of the distinction between high-tech and low-tech industries, which may have strong implications for constructing regional advantage and, thus, for regional innovation policies, and demonstrates that “the relevant knowledge base for many industries is not internal to the industry, but is distributed across a range of technologies, actors and industries” (Smith, 2000, p.19). The importance of distributed knowledge networks hints at the tendency that especially codified knowledge is becoming a more and more ubiquitous resource. However, it is still worth making a distinction between locally/regionally versus globally distributed knowledge networks. Access to tacit, experience based as well as disembodied codified knowledge is still important in case production is based on historical, technological trajectories, especially in sectors of high-quality and high-value added (luxury) products (e.g. production of highly sophisticated hi-fi equipment in Germany). Similarly, when products and services are customised and proximity to markets and customers (and thus logistics) matters, knowledge exchange can be facilitated by face-to-face co-ordination (e.g. customised business solutions where user-producer relationships are required versus general software development which can be supplied by order). This makes such production relatively more sticky and dependent on localised knowledge and learning and, thus, it will tend to draw more on local and regional distributed knowledge networks and to a lesser extent on global.
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Platform vs. Sectoral policies The previous sections on related variety, differentiated knowledge bases and distributed knowledge networks clearly suggest that a traditional, narrow sector perspective has to be transcended when constructing regional advantage in a globalising knowledge economy. The platform concept has so far mostly been used either to describe generic technologies such as software and biotech, that have potential applications across a wide range of industries, or the new developments in the automotive industries, where a limited number of platforms can be used to build a large variety of car models. One of the consequences of the very fast pace of current technological change is that innovations often generate multipurpose technologies which can lead to applications in a number of products and industries. Therefore, rigid sectoral policies at regional levels can be at risk for several reasons. First, unfortunately, in certain cases there are no policies which are sufficient for the survival of sectors which have moved to low-cost countries. Second, if sectors are identified in a too rigid way, scientific and technological opportunities can emerge at regional levels which cannot be exploited, leading to inventions being exploited by companies located in other regions. The platform concept is now also used by the American writer Thomas Friedman in his new book on the contemporary globalised world (The world is flat: A brief history of the globalised world in the 21st Century), when describing the impact of the rapid development of new and cheaper technology on everything from companies, foreign policy and terrorism: ‘What is the new platform that foreign policy is on? To understand that platform, you’ve got to understand the technology of it, you’ve got to understand the economics of it and you also have to understand who is driving it forward, because it’s not static’ (Financial Times, November 29th 2005). All these different uses point in a direction of more complicated and complex interactions and systems of knowledge, technologies, and economies, which create more scope and flexibility on the one hand, and are in more need for connectivity and systemicness on the other. A platform approach rather then a sectoral one might generate a context better equipped to exploit multipurpose and generic technologies. Therefore, the notion of policy platforms that builds on an array of instruments including and integrating key components from several policy domains - appropriate to constructing regional advantage by enabling firms to be highly knowledgeable and with global connectivity - is unavoidable. Thus, the approach for constructing regional advantage must include a variety of ingredients making up a regional platform policy (see boxes on Japan (box 9) and China (Shanghai) (box 10)).
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BBooxx 99 An example of platform strategies
An example of platform strategies being implemented can be found in Japan’s ‘New industry promotion strategy’ which is part of the National basic plan for S&T. The strategy is part of Japan’s catching-up attempts of correcting the flaws in Japan’s industrial model of a strong focus on perfection, on refining and mass-producing other people’s inventions, and on a teamwork approach to steady incremental innovations in manufacturing processes, leading to a neglect of product breakthroughs. It was just these qualities that powered the industry’s ascent, but also led to its downfall. The new strategy aims to realize a competitive and sustainable industrial structure for the next 20-30 years by:
• Revitalize strong manufacturing industries
• Develop the service industries that meet the arising needs of the society
• Form industrial clusters to end the regional economic stagnation
In the evolution of cross-sectional priority policies (or a platform based policy) the focus has been on innovative S&T (Life science, IT, environmental science, nanotech/materials) as well as on human resources, IP management etc.
In the updated version of the new industry promotion strategy from June 2005, specific attention is paid on policies for advanced components/materials industries. The figure below describes the content of this policy, and also provides an excellent illustration of what could be understood with platform policies (Figure 3):
Figure 3: Platform policies
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BBooxx 1100 Shaping a world-class hub
The evolving healthcare cluster in Shanghai In healthcare, modern China faces two critical challenges: 1. A system capable of providing healthcare to the more than 1000 million currently un-served citizens; 2. Exponential growth of the urban population and related problems of life-styles and the environment. Healthcare supply of such monumental proportions requires radical change in organization and technology, which offers sizeable market opportunities to drive innovation. The city-region of Shanghai tries to address both challenges in an unusually inventive mode of combining old and constructing new capabilities.
In early 2004, the city-region of Shanghai decided to construct a nationally significant biomedical centre in the Fenglin area (within the historic Xuhui district) and to enlarge its capabilities into a resource-rich health cluster of some ten hospitals, the medical faculties of two universities, facilities of the Chinese Academy of Sciences, Institut Pasteur and Max-Planck Gesellschaft. Within 5-7 years, the resources of some thirty already locally operating institutions and many more business firms are to be combined into one of the world’s leading clusters of biomedical R&D, medical drugs and devices, medical care and related service provision. With the available resources well connected, Fenglin is considered a very resourceful healthcare cluster.
Scientific discovery is part of Fenglin’s comprehensive value-chain. A prime objective is to move fast from scientific advancements to bed-side products, calling for unusually close institutional collaboration, instigated by new economic and organisational means. For example, seamless mobility of specialists between scientific laboratories, hospital clinics and business incubators is enabled by a range of means and incentives. Business incubators, linked to R&D as well as to the clinical environments, provide the expertise necessary to initiate and manage the processes of commercialisation of technology and related know-how.
An inclusive, visionary governance model is tailored to build confidence among local and national institutions, potential investors and those international partners who can offer locally unavailable world-class competences.
An urban upgrade, extended throughout Fenglin, should enforce the emerging socio-economic opportunities. Already branded as Shanghai’s Healthy District, Fenglin should serve as an environmentally sustainable model for metropolitan living and working in all city-regions of China, attracting foreign talent and investments.
In October 2004 European experts facilitated a roundtable on the Fenglin design and strategy, involving 17 internationally leading healthcare businesses and biomedical institutions. It was a proposition attractive to both sides: local decision-makers gained validation of plans by potential investors; international leaders valued the early opportunity to shape their future investment environment.
The Fenglin implementation strategy is based, in part, on comparative studies of 20 biomedical clusters in city-regions of Europe, Asia and North America. In a few years time only, Shanghai may be well-known as a significant healthcare hub because of its well-orchestrated biomedical and related competences and its fully-fledged urban integration, complemented by internationally networked regional resources.
Source: Interlace-Invent, a European research-based consultancy. www.interlace-invent.com
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‘Carriers’ of policies for constructing regional advantage
In order for platform policies to be initiated, innovated and implemented various actors, agencies and structures must exist and be engaged as ‘carriers’ of policies for constructing regional advantage. In the following we will highlight the importance of territorial competence bases (including people and business climate as well as the regional knowledge infrastructure), SME and entrepreneurship policies, and governance dimensions of upgrading and building regional innovation systems as creative knowledge environments.
Territorial competence bases There is a need to take a closer look at the importance of territorial competence bases both with respect to the presence of human capital and talents in a region (Florida, 2002) and the region’s knowledge infrastructure (universities and public R&D institutes). Giuliani and Bell (2005) have shown that the absorptive capacity with respect to the acquisition of exogenous or extra-cluster knowledge as well as the diffusion of this knowledge within a cluster is dependent on the level of knowledge of the firms. Thus, the knowledge and competence bases of firms and regions are important determining factors for the distribution of knowledge as well as for inter-firm learning in the region. A region’s level of absorptive capacity is of strategic importance for creating and sustaining a knowledge economy, especially with respect to appropriation of non-local knowledge. The building-up of absorptive capacity is highly dependent on the stock of human capital in the region, thus, underlining the role of local universities of producing human capital.
Business climate and people climate In a knowledge-based economy, the ability to produce, attract and retain highly skilled labour is crucial to the current and future prosperity of city-regions as well as entire nations. Thus, the people who play the lead role in knowledge-intensive production and innovation – who provide the ideas, know-how, creativity and imagination, are becoming a distinct advantage for economic success. Because value creation in many sectors of the economy rests increasingly on non-tangible assets, the locational constraints of earlier eras – for example, the access to good natural harbours or proximity to raw materials and cheap energy sources – no longer exert the same pull they once did. Instead, what matters most now are those attributes and characteristics of particular places that make them attractive to potentially mobile, much sought-after talent. A key reason for believing that a significant shift has occurred taking us into a knowledge economy is that data suggest this to be true. Thus the book value of intangible assets compared to raw materials has shifted from 20:80 in the 1950s to 70:30 in the 1990s (Cooke and De Laurentis, 2002). Consequently, the distribution of talent, or human capital, is an important factor in economic geography, as talent is a key intermediate variable in attracting high-technology industries and generating higher regional incomes. This makes it an important research task to explore
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factors that attract talent and its effects on high-technology industry and regional incomes (Florida, 2002). The replacement of raw materials or natural harbours with human capital and creativity as the crucial wellspring of economic growth means that in order to be successfully in the emerging creative age of the knowledge economy, regions must develop, attract and retain talented and creative people who generate innovations, develop technology intensive industries and power economic growth. Such talented people are not spread equally across nations or places, but tend to concentrate within particular city-regions. The most successful city-regions are the ones that have a social environment that is open to creativity of all sorts. This, together with other factors such as labour markets characterised by high demand for qualified personnel, cultural diversity and tolerance, low entry barriers and high levels of urban service, largely determine the economic geography of talent and of creativity. The ability to attract creative people in arts and culture fields and to be open to diverse groups of people of different ethnicity, race and lifestyles provides distinct advantages to regions in generating innovations, growing and attracting high-technology industries, and spurring economic growth. Thus, it is not enough to attract firms: the ‘right’ people also need to be attracted. Richard Florida calls for complementing policies for attracting firms with policies for attracting people, which means addressing issues of ‘people’s climate’ as well as of ‘business climate’ (Florida 2002). Indeed, the former is seen as basic to the latter, in that the presence of human capital and talent is essential for attracting and developing high-tech industries and consequently for the economic growth of cities, a diversification relationship, exploiting urbanization economies, pointed out by Jacobs (1969) decades ago. This suggests that the attention of politicians and planners should be directed towards people, not companies, i.e. away for business attraction to talent attraction and quality of place (Florida, 2002). While we concur with the need for paying more attention to the role of talents as a source of developing innovative industries and regions, there is a need for unpacking Florida’s general claims and contextualise them to the particularities of the knowledge bases which different industries draw upon. Unless this activity is undertaken, causal mechanisms and hence regional policy recommendations are likely to be misleading. Thus we suggest that the creative class approach could gain from adding a distinction between knowledge bases - acknowledging that different knowledge bases ask for different political actions and depend on different types of talent in different parts of the innovation process (Kalsø Hansen et al., 2005). When the creative class, as defined by Florida, in most developed OECD countries contains between 30-40% of the employment, these talents are employed in industries drawing on all the three knowledge bases. These various groups of talents will clearly have different preferences and trade-offs between firms, occupations, life-styles and place. An engineer working in an industry making packaging machines or automotives based on a synthetic knowledge base will normally have different preferences than an art director in an advertisement agency (based on a symbolic knowledge base) or a researcher in a biotech firm (based on an analytical knowledge base).
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Innovation policies for constructing regional advantage must, thus, reflect the particularities of requirements of industries based on different knowledge bases for talents, institutional support, and so forth when promoting the business climate of regions, as well as recognising the varying preferences of the creative class or talents depending on the knowledge bases of the industries they are employed in when improving the people climate.
Regional knowledge infrastructure In addition to the presence of human capital in a region, highly affected by the people climate and the quality of place, the territorial competence base is also constituted by the region’s knowledge infrastructure. As the learning economy becomes increasingly prevalent, tertiary education becomes essential as it gives access to codified knowledge that is needed to obtain various skills to be competitive on labour markets and in work life. However, the role of human capital as a contribution of universities to regional development appears to be understudied (Hommen and Doloreux, 2004; Lawton Smith, 2003). Nonetheless, providing for local highly-skilled labour markets and keeping the skills of the local workforce of firms up-to-date through education and training programs can be considered as a critical contribution in enhancing the regional innovative capacity (Hortz-Hart, 2000). Concrete examples of human capital inputs are placing and connecting students within local companies and programs of continuative professional development to enhance the skills of local managers. Traditionally, universities have been mainly concerned with delivering graduates for a national labour market dominated by large employers. Little attention was paid to graduate retention in local labour markets but this situation seems to be changing not the least through a strong regional policy push (Chatterton and Goddard, 2003; Charles, 2003). Nowadays various universities have responded increasingly to signals within the regional economy and are working with industry to establish degree courses dedicated to providing specialist skills (Lawton Smith, 2003). In addition universities play an important role as actors in the knowledge generation subsystem of the RIS. This refers traditionally to processes of technology transfer, creation of knowledge-intensive spin-off companies, and the establishment of science parks and incubators (Jones-Evans et al., 2001). Access to knowledge produced through research at the regional university thus serves as a locational advantage for firms in the region, especially in the context of SMEs. When constructing regional advantage, regional innovation performance may thus be strengthened by regional firms tapping into the knowledge reservoir of the local university against relatively few costs (see box 11).
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BBooxx 1111 Hub-cities and their regions
Successful local clusters are globally connected Most definitions of ‘clusters of competencies’ recognise the spatial limitations to the cluster. Clusters are seen as regional or local. Yet, evidence is increasing that the knowledge-base of specialized agglomerations of business firms and supporting institutions will never remain exclusively local. Technologically advanced clusters seem to be more successful, when they are linked functionally across wider spaces through firms and institutions. Mega-clusters - such as Silicon Valley’s concentration of electronics and IT industries – reach out to similarly specialised clusters in Europe, Japan, India and China as nodes in transcontinental innovation networks. Booming city-regions seem to operate less as self-contained units and more as nodes in global networks.
Many of Europe’s large corporations – and some of its small and medium-sized enterprises – are embedded in specialised ‘clusters of competencies’ in city-regions across Europe and even around the globe. More importantly, both types of firms can benefit also from being present not just in one, but in several city-regions to access specialised bodies of knowledge, created by the local R&D institutions, or to tap into particular skill-sets or unique blends of technical know-how among cluster-related firms.
For example, Europe’s medical device industry is a highly-competitive global business and, yet, an industry that relies on only a limited number of advanced, highly-specialised hub-cities, known for their original designs of world-class hospital and health care products and related services.
Europe’s design hubs for textiles and garment, furniture and household equipment tend to operate as ‘coupled innovation environments'. Similar hub-city patterns appear in industries like pharmaceuticals, autos, aero-space, advanced business services, etc. Such cross-border patterns of city-regional specialisation is sometime enforced by institutions: Cities with well-developed training programs for young designers and with effective branding through design fairs, exhibitions and other similar events, will attract more design professionals, design studios as well as companies looking for design services. It tends to be a cumulative effect due to such visibility and ‘clustering of competencies’.
Advanced hub-cities serve companies and institutions both locally and by helping to bridge the local innovation environments and the global economic marketplace. Accordingly, specialised hub-cities tend to have the best-in-class institutional setups for knowledge-intensive innovation aimed also at the global marketplace. In addition, by place branding initiatives, these city-regions can position themselves more strategically as Design Hubs, Biomedical Hubs, Financial Services Hubs, Multimedia Hubs, etc., thereby creating virtual circles that positively influence their global visibility, improve communications and attract investors.
Source: Annerstedt, J. (2006) .
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SME and entrepreneurship policies The distinction between businesses vs. people climate could also be used to highlight the difference between policy in support of SMEs and entrepreneurship policy. While the SME innovation policy is a question of improving the business climate through financial support, use of brokers, mobility schemes, establishment of technology centres as well as clusters and RIS policies, entrepreneurship policy – especially directed towards technology-based entrepreneurship – must in addition contain strategies to improve the people climate, as this indirectly will create an environment conducive for creativity and risk taking by increasing the level of tolerance and reducing threshold levels for taking various initiatives as well as lowering entry barriers facing newcomers, which imply that people from different backgrounds can easily fit in. Concerning policy towards SMEs recent research carried out in the SMEPOL project - SME policy and the regional dimension of innovation (Asheim et al. 2003) - demonstrated the need for a more system-oriented as well as a more pro-active innovation based regional policy. In the project, SME innovation policy tools were classified in two dimensions, resulting in a four quadrants table (Figure 4). The table distinguishes between two main aims of the support tools. Some tools aim at giving firms access to resources that they lack to carry out innovation projects, i.e. to increase the innovation capacity of firms by making the necessary resource inputs available, such as financial support for product development, help to contact relevant knowledge organisations or assistance in solving specific technological problems. The other type of instruments have a larger focus on learning, trying to change behavioural aspects, such as the innovation strategy, management, mentality or the level of awareness in firms. An appropriate way to design and implement an instrument aimed at assigning lacking resources to firms (following an evolutionary approach to policy) is, thus, to do it according to a learning-to-innovate framework. In line with this perspective the objective of policy instruments is not solely to provide scarce resources (such as financial assistance) to innovating firms per se but also to promote learning about R&D and innovation and the acquisition of new routines within firms. Lack of demand is often a bottleneck for financial incentives to innovation activity, i.e. that firms initially do not see the need to innovate, or alternatively, that firms do not have the capability to articulate their need for innovation. Some policy instruments should, therefore, also attempt to enhance demand for initial innovation activity of firms (i.e. apply a learning perspective), and, thus, must include an explicit behavioural aspect with an ultimate policy target of promoting the indogenisation of innovation activity of enterprises. The other dimension includes the target group of instruments. Some tools focus on innovation and learning within firms, to lower the innovation barriers of firms, such as lack of capital or technological competence. Other instruments to a larger extent have regional production and innovation systems as their target group, aiming at achieving externalities or synergies from complementarities within the regions. The barriers may for example be
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lack of user-producer interaction or lack of relevant competence in the regional knowledge organisations to support innovation projects.
Figure 4: Two-dimensional classification of main innovation policy instruments (from Asheim et al., 2003)
According to Cooke (2001) the new type of regional innovation systems, which he calls ERIS (Entrepreneurial Regional Innovation Systems), move, in contrast to the old type of regional innovation systems, IRIS (Institutional Regional Innovation System), from knowledge scale to scope, from closed to open innovation, and from reliance on corporate hierarchies to entrepreneurship (see box 12). _________________________________________________________________
Institutional RIS (IRIS) Entrepreneurial RIS (ERIS) ___________________________________________________________________
Research & Development Driven Venture Capital Driven User-Producer Relations Serial Start-ups
Technology-Focused Market-Focused Incremental Innovation Incremental & Disruptive
Bank Borrowing Initial Public Offerings External Supply-Chain Networks Internal EcoNets*
Science Park Incubators ___________________________________________________________________ Table 4: Characteristics of institutional and entrepreneurial types of RIS (from Cooke, 2001) * Venture capital cross-holdings in portfolio firms among whom outsourcing is promoted.
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The key point regarding the (somewhat artificially opposed) sides of Table 4 is that ERIS is rooted in entrepreneurship and talent formation that is largely outside the corporate hierarchies presumed to be the drivers of innovation in (some) IRIS set-ups (what are called the ‘dirigiste’ type, while the ‘grassroot’ type is dominated by SMEs). Such large institutions showed during the 1990s that they experienced difficulties in many sectors in bringing forth innovations. Essentially, these large corporations have outsourced R&D almost completely to ‘problem-solving’ companies like Halliburton and Schlumberger who, in turn, operate their own knowledge supply chains. It is inside such supply chains among entrepreneurial firms that R&D is principally conducted.
BBooxx 1122 Austin, Texas
Advantage Constructed on a Creative 'Scene' When the system into which a learning and change disposition is to be integrated is an externalised inter-organisational one rather than a corporation, the task is more difficult. Some attention is therefore devoted first to US practices in building 'economic communities'. Henton et al. (1997) argue for strong leadership to maximise, for profit, social capital effects and cite cases like the latest revival in Silicon Valley's fortunes through the association called Joint Venture Silicon Valley, the revival of Cleveland and the transformation of Austin, Texas. Austin's evolution from sleepy campus and government town to one of America's leading New Economy clusters is presented, as are the others, as cases of learning clusters based on cooperative advantage. The New York Times eulogised the place in January 1999 as:
at once the least Texan and the most Texan of cities, with a burgeoning hi-tech industry, a University population of over 50,000, the endless carnival of Texas statehouse politics, and a music and restaurant scene that would be envied by a city twice Austin's size. Austin is one of those cities like Seattle and Santa Fe that gets so much praise you wish you could hate it.
Economic growth was running at 9-10 per cent annually in the 1990s and 30,000 new jobs were being added each year, some 200 start-up technology companies were founded there each year and it had a relatively recently established specialist business support system, largely private in origin. This was propelled forward by the actions of community entrepreneurs, particularly George Kozmetsky, founder of the Austin economic model, known subsequently as the 'triple helix' of government, industry and university interaction (Etzkowitz and Leydesdorff, 1997). This led to a successful cluster policy in which all three actors connected also to entrepreneurs, sources of technology, venture capital and an innovation infrastructure of lawyers, accountants and business incubators. The policy key is leadership on each part of a strategy to retain and attract existing business and to grow new ones, and each leader is drawn from the 'economic community'. Luck plays a part, but even bad luck can be parlayed into future benefits. Thus the University of Texas at Austin is the second richest after Harvard in the USA, hence the world. But it started with a handicap in that it could not be a federal land grant university as Texas contained no federal land in the 1870s when it was established. Instead it received 5,000 acres of cotton and forest property, plus building plots. So successful was the cotton crop in the first year that the South Texas legislature re-appropriated the land and gave the university in perpetuity 2.2 million acres of wasteland in exchange. Not very auspicious starts,
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except that beneath the wasteland were discovered enormous resources of oil. Now the University of Texas' endowment stands at $7 billion. Some of this windfall was used to attract 'anchor' projects like the semiconductor research consortia Sematech and MCC, which gave Austin a local high technology edge. This attracted 3M, Dell, IBM and Motorola to set up applied research facilities. Dell's just-in-time production system means that, as well as its 20,000 Austin employees, it sustains an equivalent number in its co-located supply chain. But New Economy clusters are not immunized against economic downturns as Dell's cut of 1,500 jobs in 2000, and lower rates of city job growth 2000-2002, down to 3.7 per cent from 5.2 per cent signify.
Source: Cooke, P. (2002), pp. 14-15.
In other industries, notably pharmaceuticals, which have a globally high expenditure on R&D at some 18% of revenue, much of this (up to 50%) is outsourced to knowledgeable biotechnology and pharmaceuticals knowledge suppliers, and universities and other research institutes. Chesbrough (2003) shows this to be common also in the ICT and electronics industries (e.g. in Philips). Hence this large scale of externalisation of knowledge exploration, examination and exploitation to knowledge entrepreneurs of a public or private kind, including in universities sometimes both, creates a new knowledge and innovation landscape for regional governances to grapple with. In Table 5 the firm-level shifts towards management of open innovation compared to the tradition of more ‘closed innovation’ are summarised. ___________________________________________________________
Closed innovation Open innovation ____________________________________________________________ Strategic R&D – core business strategy Firms select desired technologies
Firms perform R&D in-house Technology acquisition
Firms put technologies in products Firms market products
Product revenues fund additional R&D R&D Outsourcing
Globalisation (1) adjusts Globalisation (2) taps products to markets global talent pools ______________________________________________________________
Table 5: Closed and Open Innovation (from Chesbrough, 2003)
The latter was conducted in-house by dedicated R&D departments of the kind that firms like General Electric, Dupont and AT&T pioneered, but which the last two at least have largely divested, decentralised or externalised. It is evident that, to the extent such R&D, along with other, outsourcing has progressed to the point where the likes of Indian and Chinese knowledge and services suppliers are well-integrated in the knowledge value chains of Western companies. Globalisation itself is in transition to a new economic geography in which the ‘constructed advantage’ of possessing regional talent pools of global significance now dictates locational decision-making of multinationals in ways that were not so determinate when largely ubiquitous cheap manufacturing labour was available in many global locations, as it still is.
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We term this a transition from Globalisation (1) and the quest for cheap routine labour to Globalisation (2) and the magnet of regional talent pools of global significance (Cooke, 2005). Technology-based entrepreneurship is a phenomenon that has become increasingly important during the last decades. One of the most important reasons for this is the role played for industrial renewal and economic growth. While many traditional, heavy industrial sectors have witnessed a declining importance, new emerging creative and knowledge-based technological sectors have instead been expanding rapidly (see box 13).
BBooxx 1133 Knowledge-based entrepreneurship
The case of technology-based new firms Technology-based new firms are a special category of knowledge-based firms. Knowledge-based entrepreneurship – as well as technology-based entrepreneurship - is a phenomenon that is growing in importance. The transformation from heavy industry to creative and knowledge-based activities is sometimes argued to be as great as the industrial revolution.
The location of new technology-based industries depends greatly on access to knowledge and different learning processes. Entrepreneurs tend to set up new technology-based firms where they have a personal network of contacts, mostly where they already live and work. Thus, new technology-based firms tend to spin-off from and cluster around universities, research organisations and existing firms. Small and new firms are also often depending on externalities, and for technology-based entrepreneurial firms it is usually critical to have access to, for example: skilled labour, specialised inputs, capital, knowledge spillovers, and local customers. As a result, there is a natural tendency towards a substantial and probably growing disparity between regions that already possess indigenous high-technology activities, and those that do not. This means that substantial regional disparities are to be expected.
The two main sources of new technology-based firms are universities and existing private companies; few new technology-based firms are based on independent inventions. It is common that the main share of knowledge workers are employed in private industry, and, thus, that a large part of the new technology-based firms is created as spin-offs from the existing industry. In the university-sector, creating and exploiting new commercial ideas are not part of the traditional core operations. Even so, a substantial part of the new technology-based firms is linked to university activities. A small share of the new technology-based firms are created by university researchers themselves, i.e. direct university spin-offs, others by external entrepreneurs exploiting university research made by others. Also some new firms are created as indirect university spin-offs in that they are based on university research, but not established until the founder(s) have gained additional working experience in a private employment. Thus, existing organisations and corporations have a critical role to fulfil as a training ground for future technology entrepreneurs within a regional innovation system. Thus, even though large corporations recruit a substantial part of the university graduates, these graduates may very well in the future continue to contribute to the technology-based entrepreneurship in a region.
To construct regional advantage from knowledge-based entrepreneurship will – at least – require a combination of entrepreneurship-, SME- innovation-, university- and regional policies. While, for example, SME policies are often developed to help and assist the growth of small firms, entrepreneurship policies are instead often focusing individuals and their entrepreneurial capacity (skills and motivation). University policy is important since universities are responsible for both the education of a large part of future key personnel, and
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for a substantial part of the advancement of science, technology and innovation. Thus, the technological/knowledge profile and responsiveness of a (strong) university will influence the technological entrepreneurship and profile of a dynamic region. Innovation policy must, of course, include aspects linked to universities, but it must also deal with the interdependence between large and new/small firms. The recipe for constructing regional advantage must include a variety of ingredients making up a regional platform policy.
In the perspective of the rise of the creative class it is important to consider the interaction of stocks of talent, entrepreneurship, and networking in regional development. As argued by Cooke (2005, p. 6) ‘innovation and entrepreneurship requires ‘talent’ and crucially the means for producing talent’. What is meant by talent is not always clear. Talking about technology-based entrepreneurship it is usually assumed that some technical-, marketing-, and business knowledge is normally required in connection with certain entrepreneurial characteristics. Often education and work experience are pointed out as means to acquire different kinds of knowledge. Lawton Smith et al. (2005) argues that it should not be overlooked that the quality of the social networks of entrepreneurship and innovation ‘is dependent on the quality or talent of individuals who have initiated particular developments’ (Lawton Smith et al., 2005, 1). Using Oxfordshire as a case study she demonstrates ‘how the expertise of talented individuals has been translated in the fastest growing high-tech economy in the UK’ (Lawton Smith et al., 2005, 1). It can be argued that many European countries have a relatively high share of technology-based entrepreneurship, both as spin-offs from private industry and from universities. However, it is less clear whether this technology-based entrepreneurship is of a magnitude large enough to make an important contribution to economic growth. To fulfil this role, it is important that the entrepreneurial activities of a region or nation are big enough. With a low entrepreneurial activity, it might not be enough to have a high share of knowledge- and or technology-based entrepreneurship. To design a policy encouraging knowledge- and/or technology-based entrepreneurship, as well as creating new high growth technology-based firms (i.e. sometimes called a ‘picking-the-winners’ SME policy) might also prove problematic if the intention is to encourage economic development and growth. However, these dilemmas underline the need of seeing modern knowledge-based entrepreneurship in an innovation system perspective. As an outcome of the regionalisation of innovation policy we might find that within a country with a dominating type of capitalism (either a coordinated or a liberal market economy (Hall and Soskice, 2001)) it will be more common to find a ‘US/European blend’ when it comes to types of innovation support pursued. This could on the one hand be the result of the specific industry to be supported, i.e. if the aim is to upgrade an existing, traditional industry based on a synthetic knowledge base an IRIS-type of policy would be most relevant, in contrast to stimulating the commercialisation of new knowledge drawing on an analytical knowledge base, which might be more efficient if pursuing an ERIS-type of policy. On the other hand, in cases with industries drawing on the same knowledge base, it might be an outcome of the ideological and political platform of the regional government, i.e. the regional authorities in Veneto would tend to prefer an ERIS-strategy, while in Emilia-Romagna an IRIS-strategy would tend to be supported.
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Upgrading and building regional innovation systems As already emphasised, regional innovation systems have played and will continue to play a strategic role in promoting the innovativeness and competitiveness of regions. To achieve this, the RIS approach has to be strengthened by attention being directed towards the need – perceived by policy makers both at EU and regional levels – of constructing regional advantage. The regional innovation system can be thought of as the knowledge infrastructure supporting innovation in interaction with the production structure of a region. Thus, when the following two subsystems of actors are systematically engaged in interactive learning (Cooke et al., 1998) it can be argued that a regional innovation system is in place: (1) The regional production structure or knowledge exploitation subsystem which consists mainly of firms, often displaying clustering tendencies, and (2) The regional supportive infrastructure or knowledge generation subsystem which consists of public and private research laboratories, universities and colleges, technology transfer agencies, vocational training organisations, etc. The interacting knowledge generation and exploitation subsystems of a RIS is, moreover, linked to global, national and other regional systems (Cooke, 2004). From this follows that clusters and RIS can (and often do) co-exist in the same territory. But whereas the regional innovation system by definition hosts several clusters, a cluster is not part and parcel of a RIS. Furthermore, Cooke et al. (1998) emphasise the role of the informal institutional context (i.e. norms, trust and routines) in which such interactive learning takes place. This dynamic and complex interaction constitutes what is commonly labelled systems of innovation (Lundvall, 1997; Edquist, 1997), i.e. systems understood as interaction networks (Kaufmann and Tödtling, 2001). The ‘innovation system’ concept can be understood in both a narrow as well as a broad sense. A narrow definition of the innovation system primarily incorporates the R&D functions of universities, public and private research institutes and corporations, reflecting a top-down model of innovation. Such constellations traditionally resulted in regionalised national innovation systems, which constitute a supply (science push) driven model (see box 14). A broader conception of the innovation systems includes ‘all parts and aspects of the economic structure and the institutional set-up affecting learning as well as searching and exploring’ (Lundvall, 1992, 12), and, thus, has a weaker system character. This broad definition incorporates the elements of a bottom-up, interactive innovation model which is referred to as territorially embedded regional innovation systems (or learning regions). This type basically represents a market-driven model, where demand factors determine the rate and direction of innovation. A combination of these two types of RIS is called regionally networked innovation system (Asheim and Isaksen, 2002). The networked system is commonly regarded as the ideal-type of RIS: a regional cluster of firms surrounded by a regional supporting institutional infrastructure. These systems have a more planned character than the territorially embedded systems involving public-private co-operation, and a stronger, more developed role for regionally based R&D institutes, vocational training organisations and other local organisations involved in firms’ innovation processes (see box 15). (For a more elaborated description, see appendix).
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BBooxx 1144 Third Generation Innovation Environments
The ‘urbanised’ science park In its modern form, the science park experience has a history of some 50 years. Without major exceptions, all European city-regions have science parks or, as they are called, Technology Parks, High-Tech Centres, Research Parks or Technopoles. Science Park is the generic term for “an organisation managed by specialised professionals, whose main aim is to increase the wealth of its community by promoting the culture of innovation and the competitiveness of its associated businesses and knowledge-based institutions.” (International Association of Science Parks, 2002.) Other science park definitions emphasise the link to a university or R&D facility.
The first wave of investments into science parks and high-tech business areas reached European regions in the early 1960s. Science parks were still conceived as suburban high-tech zones and it would take 30 years before science parks would start to ‘go urban’ and move closer to the socio-economic fabric of city-regions, while developing new varieties of innovation support services. The European versions of the US Science Park model were first tested in the UK. The most recognised European pioneer is Sophia-Antipolis of France (1969). Sophia remains Europe’s biggest science park (2,300 hectares) with 24,500 persons employed in its companies and institutions.
The innovation philosophy of a First Generation Science Park is ‘science push’. Scientific findings are simply raw material for academic entrepreneurship or innovative business activities. It is a ‘linear approach’ to innovation.
Second Generation Science Parks typically remain an extension of a university (or other R&D facility) into a dedicated high-tech zone. Nonetheless, the park could also be a separate entity, located far from an R&D centre. The drive and the decisive energy come from business firms, interested in innovative products and services. The innovation philosophy is more of ‘market pull’. A study in 2004 of Germany’s 440 municipalities showed that they are home to 362 science and technology parks (broadly defined). Yet, for the majority of these parks the research base is very limited. They are driven by business or by public-private partnerships.
The innovation philosophy of a Third Generation Science Park is both ‘science push’ and ‘market pull'. It departs from the ‘linear model’ of innovation into ‘interactive’ innovation. Embedded in the urban environment with ever-changing varieties of demand, innovations appear as continuous outcomes of more functional interactions.
Third Generation Science Parks are more complicated to govern. The blurring of borders between activities that take place inside and outside of a park, which is well-integrated into the city-region, will cause complexities for the park's management. Involving new stakeholders and recognising wider stakeholder communities (such as pioneering user groups) require new methods of leadership and a broader culture of entrepreneurship in order to foster the growth of knowledge-intensive business firms. However, constructing and facilitating such comprehensive capabilities in support of innovation could become very rewarding for the business firms involved as well as for the wider society.
Source: Interlace-Invent, a European research-based consultancy. www.interlace-invent.com
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BBooxx 1155 Building Regional Innovation Systems
VINNOVA’s VINNVÄXT-initiative
‘Innovation i Gränsland’ (Food Innovation at Interfaces) has been granted funding as a VINNVÄXT program in 2003. The application was written by the network organization ‘Skånes Livsmedelsakademi’ (Scania’s food and beverages academy) whose members are from the triple helix of business, research organisations and regional public administration. The application builds on the shared strategic vision to increase the added value of the region’s food industry’s products and services. It intends to do so through a focus on multi-disciplinary innovation projects in the borderland between different knowledge bases. The project builds on the recognition that the Swedish food industry as well as important related areas such as logistics and machinery is heavily concentrated in the country’s most Southern region Scania. The total growth of the cluster is however low as parts of the sector are dominated by typically Fordist bulk production aimed at price competition and economies of scale. The programme acknowledges that this is not an economically sustainable situation and, hence, aims to access new, more specialised and knowledge-intensive segments of the market such as high-quality niche products, convenience foods, ecological foods and functional foods (defined as artificially developed food with added ingredients that demonstrate scientific evidence of positive health-related effects). To make this shift, companies need to collaborate more actively with the existing knowledge infrastructure found in Scania. Both Lund University and the Swedish Agricultural University in Alnarp (located between Lund and Malmö) have indeed aligned parts of their education and research activities to the historical presence of the food industry in Scania. For example, already early in the 20th century firms and organisations in the regional farming community as well as the Swedish state supported and collaborated with scientists in plant breeding through the Svalöf Institute (which was part of Lund University) to develop better seeds for the agricultural conditions prevalent in Sweden. Within ‘Food Innovation at Interfaces’ triple helix collaboration is organised both on a strategic and operational level. The board of the program consists of representatives from the regional food industry, universities as well as regional government and serves as a reference group for the program as a whole. On an operational level, the program is divided in four main project areas: Food and Health - Functional Foods, International Consumer Marketing, Good and Convenient Food on a Large Scale, Innovations in Theory and Practice. These project areas reflect the broad scope of activities that the program aims to cover, targeting analytic knowledge-based innovation (e.g. in Food and Health - Functional Foods) as well as synthetic knowledge-based innovation (e.g. in Good and Convenient Food on a Large Scale). Within these project areas, various projects are carried out drawing on collaboration in a public-private or triple helix context coordinated by project managers which often are affiliated with organizations that have substantial previous experience with such collaboration.
However, there are different logics behind constructing regional innovation systems contingent on the knowledge base of the industry it addresses as well as on the regional knowledge infrastructure which is accessible. In a territorially embedded regional innovation system, the emphasis lies on the localised, path-dependent inter-firm learning processes often involving innovation based on synthetic knowledge. The role of the regional knowledge infrastructure is therefore mainly directed to industry-specific, hands-on services and concrete, short-term problem solving, i.e. ex-post support to the cluster. In a regionalised national innovation system, R&D and scientific
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research take a much more prominent position. Innovation builds primarily on analytic knowledge. Linkages between existing local industry and the knowledge infrastructure are however weakly developed. Instead it holds the potential to promote new industries at the start of their industrial and technological life cycle. In this, the role of the regional(ised) knowledge infrastructure is a very central one as it provides the cornerstone for cluster development (through the precarious task of commercialising science) and can thus be called ex-ante cluster support. Similar to the regionalised national innovation system, in the regionally networked innovation system the knowledge infrastructure plays an indispensable role, however more territorially embedded. But in contrast to it, the cluster is not wholly science-driven but represents a combination of a science and market-driven model. In comparison to the territorially embedded regional innovation system, the networked RIS often involves more advanced technologies combining analytic and synthetic knowledge as well as having better developed and more systemic linkages between universities and local industry. While territorially embedded RIS are often found in mature industries and regionalised national innovation systems found in emergent industries, networked regional innovation systems can typically support various types of industries in different life cycle phases. Firms and knowledge infrastructure form a dynamic ensemble, combining ex-post support for incremental problem-solving and ex-ante support to counter technological and cognitive lock-ins. Figure 5 shows combinations of different types of regional innovation systems and knowledge bases.
Figure 5: Types of regional innovation systems and knowledge bases
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Regional Innovation Systems as Creative Knowledge Environments
In this report we have emphasized the need for a more platform and system-oriented as well as a more pro-active innovation based regional policy in order to construct regional advantage. A re-orientation of what is called the target level of support, changing innovation policies from being firm-oriented to a (regional) system-oriented perspective has already gained a growing attention among researchers and policy makers by pursuing a cluster and regional innovation system based policy. However, the second part of the recommendation concerning the form and focus of support implying a change of focus from allocation of resources for innovation to focusing on learning aiming for behavioural value-added as well as pursuing a platform-oriented perspective has not been implemented to the same degree (Asheim et al., 2003). These recommendations, which is considered to be of strategic importance in shaping the conditions for constructing regional advantage, emphasise precisely a need for a more conscious and thorough systemic approach to developing the endogenous capacity of firms and regions to innovate, focusing especially on the role of knowledge creation, absorption and diffusion generally and R&D more specifically in a well-structured and well-designed interplay of local and non-local knowledge flows in an increasingly more knowledge intensive, globalising economy. This implies that the view that ‘local buzz’ in a cluster is generated by just ‘being there’ in an agglomerated environment is not any longer considered to be sufficient. On the contrary, it is argued that the promotion of ‘local buzz’, understood as the development of endogenous capacity of regions to innovate, requires as much proactive planning as the establishment of ‘global pipelines’ to generate non-local knowledge flows. Consequently, it has been argued that it is more likely to enhance clusters’ learning and innovation capacity by strengthening firms’ knowledge bases rather than by pooling firms together in the same agglomeration (Giuliani, 2005). One important type of connectivity in a regional economy is what potentially takes place when constructing RIS in a triple-helix context. In the terms of reference paper from DG Research for the work of this Expert group a Triple Helix approach is used to present what is considered to be the necessary background for constructing regional advantage, i.e. (i) the existence of a knowledge infrastructure (universities, public research centres etc.) producing human capital and new knowledge, (ii) industry, i.e. the regional economic sector and its non-local links, and (iii) governance, i.e. regional government and governance structures and their potentials for giving policy support to industry. The key point with this approach is, however, how to make a Triple Helix (or a RIS) constellation operate so that systematic interaction between the various partners constructs regional advantage. This perspective has been given an increased attention among policy makers as well as researchers within innovation research. However, so far this perspective has been applied in a rather static way, more like a heuristic device than as a basis for actual policy formulations. This is also the weakness of the approach, as it does not give much guidance concerning how a triple-helix based collaboration could be functional, operational and implemented in concrete policy settings in order to contribute to constructing regional
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advantage. In order to achieve this, theoretical and practical advice must be developed partly with respect to how collaboration between the three actors of the triple-helix, i.e. the industry, university and government, should be externally organised, and partly with respect to how knowledge creation and innovation oriented work should be organised internally among the different actors, thus turning the macro-, meso-, and micro-levels of the Triple Helix into creative knowledge environments. Creative knowledge environments are ‘environments in which new knowledge is produced by people, especially in their work settings’ (Hemlin et al., 2004, 2). Such creative knowledge environments can be found at macro- (e.g. national or regional innovation systems), meso- (e.g. research institutions and corporations) as well as micro-levels (i.e. research groups or work teams), and contain physical, social and cognitive characteristics. This new focus on creative knowledge environments covers a void in the majority of innovation studies - primarily focusing on how knowledge are exploited through innovations and entrepreneurship – by analyzing how creation of new knowledge actually occurs as well as what characterize the environments in which creative knowledge-producing activities are carried out. This approach, thus, put stronger focus on the actors, agencies and governance forms as well as their respective environments relevant for constructing regional advantage in a triple-helix as well as a multi-level perspective.
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Appendix 1: Conceptual and theoretical background
Constructed advantage: Definition and concepts ‘Constructed advantage’ has lately turned up in the literature discussing how to achieve and promote regional competitiveness. So far, this discussion has not clearly and convincingly been able to explain in what ways ‘constructed advantage’ differ from ‘competitive advantage’. Porter (1990) introduced the concept ‘competitive advantage’ as an answer to what he considered was shortcomings with the Ricardian concept of ‘comparative advantage’, which had dominated the discourse and informed policy concerning trade and competition for nearly one and a half century. According to the principle of comparative advantage goods were traded on the competitive bases of using the lowest relative input costs in the production, i.e. the ‘natural’ production factors (including labour) each country had the relative best and/or affluent access to and most efficient use of. In this 1990 book Porter argues strongly for the need to come up with a new theory of competitive advantage, as the old Ricardian approach was not fully able to explain trade patterns and firms’, regions’ and nations’ competitiveness in the contemporary globalising economy. First of all, a globalising economy needed a more dynamic principle of competitive advantage, resting on ‘making more productive use of inputs, which requires continual innovation’ (Porter, 1998, p. 78). This more dynamic perspective emphasised that competitive advantage can be influenced by innovation policies and supporting regulatory and institutional frameworks. In this way innovation plays a central role in attaining and sustaining competitive advantage, explaining partly why firms from particular nations choose better strategies than firms from other nations competing in the same industries, and partly why firms from certain nations gain competitive advantages beyond the limited scope of the factor-based comparative advantages to include competitive advantages based on innovations nurtured by segmented markets, differentiated products, technology differences etc. This linking of competitiveness and innovation is of strategic importance as it represents the high road to economic development and the strong way of competing (in contrast to the weak way or the low road based on squeezing costs -low wages). Secondly, Porter stressed the increased importance of the nation state as a home base for successful global competition in particular industries even in a globalising economy. He argued that ‘competitive advantage is created and sustained through a highly localised process. Differences in national economic structures, values, cultures, institutions, and histories contribute profoundly to competitive success’ (Porter, 1990, p. 19). This extension of the notion of competitiveness from firms to regions and nations is important as it incorporates the view of an economy as embedded in social structures as well as of the competitiveness and performance of an economy as being strongly interlinked with and dependent upon the broader societal and institutional framework of nations (Hall and Soskice, 2001).
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Then, what is new with ‘constructing’ advantages (CA) compared to Porter’s view of ‘creating’ such competitive advantages? In the terms of the reference paper for the Expert Group’s work the CA approach is presented in the following way: ‘Developing the regional dimension of the ERA (European Research Area), implies developing the endogenous capacity of the region to innovate, capitalising on their strengths to create wealth and jobs. This approach can be described by the concept of creating a ‘new competitive advantage’ that highlights (in terms of regional development economics), the benefits of a so-called ‘constructive advantage’’. However, this specification does not really provide any full disclosure of the differences between the concepts. The formulation ‘creating a ‘new competitive advantage’ is also used by Porter already in his 1990 book. Thus, there is an obvious need of reflecting over the differences between ‘creating’ and ‘constructing’ in order to understand what should be meant with constructing and constructed advantages. The key to solving this question has far older roots than Porter’s work. Once again going back to the writings of Alfred Marshall on industrial districts can be quite illuminating. In discussing how the exploitation of localisation economies of industrial districts can secure the competitiveness of SMEs against the internal economies of scale-based competitive strength of large firms he assumed that business interactions (from exploiting localisation economies) and knowledge flows were co-occurring phenomena (Giuliani, 2005) by arguing for a ‘fusion’ of the economy and society (Piore and Sabel, 1984) and introducing the concept of ‘Marshallian agglomeration economies’. In contrast to traditional regional economics, Marshall attaches a more independent role to agglomeration economies as the specific territorial aspects of a geographical agglomeration of industrial production. Marshall focuses on traditional socio-cultural factors, which concern the quality of the social milieu of industrial districts, and which only indirectly affect the profits of firms. Among such factors Marshall emphasizes in particular the mutual knowledge and trust that reduces transaction cost in the local production system; the industrial atmosphere which facilities the generation and transfer of skills and qualifications of the workforce required by local industry; and the effect of both these aspects in promoting (incremental) innovations and innovation diffusion among small firms in industrial districts (Asheim, 2000). The view of these territorial-based mechanisms as ‘favouring inter-firm diffusion of knowledge and collective learning, among them: the turn-over of skilled labour force, the intensive client-supplier interactions, the inter-firm transfer of knowledge and the proliferation of spin-off firms’ (Giuliani, 2005, p. 4) has in many years of research on clusters and innovation been considered nearly as a fact, and has been reproduced over and over again. Malmberg (2003, p. 157), for example, maintains that local interactions are characterised not just by being unstructured and unplanned, but also relatively broad and diffuse, sometimes unwanted and often seemingly of little immediate use’. In another paper looking at the relations between collective learning processes taking place in a community by just being there, which is called ‘local buzz’, and building ‘global pipelines’ to knowledge providers located outside the local milieu, it is argued that while ‘local buzz is certainly dependent on particular local institutional preconditions … the important point is that it largely takes
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care of itself. If a number of actors are placed within a region some sort of buzz will automatically result’, while ‘in contrast, it is especially the development of global pipelines which requires institutional and infrastructure support’ (Bathelt et al., 2004). It is this idea of an almost ‘automatic’ shaping of learning and innovation creating competitive advantages by just ‘being there’, co-located in an agglomerated environment, that also lies behind Porter’s understanding of how competitive advantage is created. He writes that ‘firms create competitive advantage by perceiving or discovering new and better ways to compete in an industry and bringing them to the market, which is ultimately an act of innovation’ (Porter, 1990, p. 45). However, in the context of Italian industrial districts I argued nearly 10 years (Asheim, 1996, repeated and developed in Asheim, 2000) that one of the constraining factors with respect to their innovative capacity (i.e. moving beyond the domination of incremental innovations) is the fierce competition between small subcontractors specializing in the same products or phases of production, and vertically linked to the commissioning firms. This promotes cost efficiency but do not represent a very innovative milieu. Also recently, several observers have questioned ‘the widely accepted view of cluster learning as being a pervasive and ‘collective’ process (Giuliani, 2005, p. 2) only conditioned by territorial agglomeration as such. Giuliani (2005) argues and shows empirically that ‘the structure of the knowledge network in a cluster is related with the heterogeneous distribution of firms’ ‘knowledge bases’ implying that this ‘heterogeneity of firms’ knowledge bases generates uneven distribution of knowledge and selective inter-firm learning’ (Giuliani, 2005, p. 1). She concludes by arguing that ‘cluster’s innovation is more likely to be enhanced by strengthening firms’ knowledge bases rather than by pooling firms together in the same geographical area’ (Giuliani, 2005, p. 17). However, it is an important question if firms can take up this challenge of strengthening their knowledge bases (or competence level, which is what Giuliani in facts refer to) by themselves and just on their own initiative start cooperating with neighbouring firms and knowledge creating and diffusing organizations co-located in clusters, thus, consequently, changing their behaviour to become more innovative, along with the view of Bathelt et al. and Porter referred to above, or if more planned and systemic approaches are needed in a globalising knowledge economy in order for regional advantages to be deliberately constructed. This argument is grounded in the observations that in the contemporary globalising economy characterised by outsourcing/offshoring, delocalization, FDIs, distributed knowledge bases, open innovation, dominating TNCs, and intensified competition from developing countries of which China and India are the ‘star’ examples, based on cost efficiency (i.e. low wages) as well as a rapid increasing knowledge intensity in the production of both manufacturing goods and services, simply leaving the question of how competitive advantages are achieved just to the market or the ‘territory’ in the Marshallian way, is not enough. The idea, then, that in the future it will not be sufficient to rely on competitive advantage just to be created but that they need consciously and pro-actively to be constructed has this understanding of the challenges EU faces in a globalising economy as its point of departure. This point to a new and more dynamic role of the
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public sector (including universities) generally and government and governance specifically. Typically, when Porter discusses if government should be viewed as the fifth determinant of competitive advantage, he concludes that the ‘most useful way to understand governments role … in national competitive advantage is in influencing the four determinants’ (Porter, 1990, pp. 126-27). On the other hand he underlines the importance of being able to explain ‘the role of the nation in the innovation process. … The question is how a nation provides an environment in which its firms are able to improve and innovate faster than foreign rivals in a particular industry’ (Porter, 1990, p. 20).
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Appendix 2: How to characterise regions
The three industrial knowledge bases In this section one of the dimensions discussed in section 2, industrial knowledge bases, will be further elaborated and developed in order to become useful in understanding the diversity of regions.
Analytical knowledge base This refers to industrial settings where scientific knowledge is highly important, and where knowledge creation is often based on cognitive and rational processes or on formal models. Examples are biotechnology and nanotechnology. Both basic and applied research as well as systematic development of products and processes is relevant activities. Companies typically have their own R&D departments but they also rely on the research results of universities and other research organisations in their innovation process. University-industry links and respective networks, thus, are important and more frequent than in the other types of knowledge base. Knowledge inputs and outputs are in this type of knowledge base more often codified than in the other types. This does not imply that tacit knowledge is irrelevant, since there are always both kinds of knowledge involved and needed in the process of knowledge creation and innovation (Nonaka et al., 2000, Johnson et al., 2002). The fact that codification is more frequent is due to several reasons: knowledge inputs are often based on reviews of existing studies, knowledge generation is based on the application of scientific principles and methods, knowledge processes are more formally organised (e.g. in R&D departments) and outcomes tend to be documented in reports, electronic files or patent descriptions. These activities require specific qualifications and capabilities of the people involved. In particular analytical skills, abstraction, theory building and testing are more often needed than in the other knowledge types. The work-force, as a consequence, needs more often some research experience or university training. Knowledge creation in the form of scientific discoveries and technological inventions is more important than in the other knowledge types. Partly these inventions lead to patents and licensing activities. Knowledge application is in the form of new products or processes, and there are more radical innovations than in the other knowledge types. An important route of knowledge application is new firms and spin-off companies which are occasionally formed on the basis of radically new inventions or products.
Synthetic knowledge base This refers to industrial settings, where the innovation takes place mainly through the application of existing knowledge or through the new combination of knowledge. Often this occurs in response to the need to solve specific problems coming up in the interaction with clients and suppliers. Industry examples include plant engineering, specialised advanced industrial
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machinery and production systems, and shipbuilding. Products are often ‘one-off’ or produced in small series. R&D is in general less important than in the first type. If so, it takes the form of applied research, but more often it is in the form of product or process development. University-industry links are relevant, but they are clearly more in the field of applied research and development than in basic research. Knowledge is created less in a deductive process or through abstraction, but more often in an inductive process of testing, experimentation, computer-based simulation or through practical work. Knowledge embodied in the respective technical solution or engineering work is at least partially codified. However, tacit knowledge seems to be more important than in the first type, in particular due to the fact that knowledge often results from experience gained at the workplace, and through learning by doing, using and interacting. Compared to the first knowledge type, there is more concrete know-how, craft and practical skill required in the knowledge production and circulation process. These are often provided by professional and polytechnic schools, or by on-the-job training. The innovation process is often oriented towards the efficiency and reliability of new solutions, or the practical utility and user-friendliness of products from the perspective of the customers. Overall, this leads to a rather incremental way of innovation, dominated by the modification of existing products and processes. Since these types of innovation are less disruptive to existing routines and organisations, most of them take place in existing firms, whereas spin-offs are relatively less frequent.
Symbolic knowledge base This knowledge is related to the aesthetic attributes of products, to the creation of designs and images and the economic use of various forms of cultural artefacts. The increasing significance of this type of knowledge is indicated by the dynamic development of cultural industries such as media (film making, publishing, and music), advertising, design or fashion (Scott 1997; 1998). These industries are innovation- and design-intensive since a crucial share of work is dedicated to the ‘creation’ of new ideas and images and less to the actual physical production process. Competition thus increasingly shifts from the ‘use-value’ of products to the ‘sign-value’ of brands (Lash and Urry 1994, p. 122). In the cultural industries in particular the input is aesthetic rather than cognitive in quality. This demands rather specialized abilities in symbol interpretation than mere information processing. Symptomatically, the knowledge involved is incorporated and transmitted in aesthetic symbols, images, (de)signs, artefacts, sounds and narratives. This type of knowledge is strongly tied to a deep understanding of the habits and norms and ‘everyday culture’ of specific social groupings. Due to the cultural embeddedness of interpretations this type of knowledge base is characterised by a strong tacit component. The acquisition of essential creative, imaginative and interpretive skills is less tied to formal qualifications and university degrees than to practice in various stages of the creative process. The process of socialisation (rather than formal education) in the trade is not only important with regard to training ‘know how’, but also for acquiring ‘know who’, that is knowledge of potential collaborators with complementary specialisation (Christopherson, 2002).
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The latter is essential since production quite typically is organised in temporary projects (Grabher, 2002). In fact, cultural industries, like film production, are emblematic project settings (see, for example, DeFillippi and Arthur, 1998; Starkey, Barnatt and Tempest, 2000; Sydow and Staber, 2002). More generally, the project provides an organisational arena in which a diverse spectrum of professional cultures that ranges from the artistic world to the commercial world of business services is brought together for a limited period of time. Projects in the symbolic knowledge base, however, are not necessarily aimed at bridging or minimising such diversity in a straightforward fashion. They also are seen as arenas of productive tensions and creative conflicts that trigger innovation.
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Appendix 3: Models for constructing regional advantage
Regional innovation systems (RIS) The regional innovation system can be thought of as the institutional infrastructure supporting innovation within the production structure of a region. Thus, in case the following two subsystems of actors are systematically engaged in interactive learning (Cooke et al., 1998) it can be argued that a regional innovation system is in place. (1) The regional production structure or knowledge exploitation subsystem which consists mainly of firms, often displaying clustering tendencies. (2) The regional supportive infrastructure or knowledge generation subsystem which consists of public and private research laboratories, universities and colleges, technology transfer agencies, vocational training organisations, etc. From this follows that clusters (see below in point d)) and RIS can (and often do) co-exist in the same territory. But whereas the regional innovation system by definition hosts several clusters, a cluster is not part and parcel of a RIS. Furthermore, Cooke et al. (1998) emphasise the mainly informal institutional context (i.e. norms, trust and routines) in which such interactive learning takes place. This dynamic and complex interaction constitutes what is commonly labelled systems of innovation (Edquist, 1997), i.e. systems understood as interaction networks (Kaufmann and Tödtling, 2001). Taking each element of the term in turn (Asheim and Cooke, 1999), the concept of region highlights an important level of governance of economic processes between the national level and the level above the local or municipal level (Cooke and Leydesdorff, 2006). Regions are important bases of economic coordination at the meso-level, although the level of regional administration can differ quite a lot across various countries. In varying degrees, regional governance is expressed in both private representative organisations such as branches of industry associations and chambers of commerce, and public organisations such as regional agencies with powers devolved from the national (or, within the European Union, supranational) level to promote enterprise and innovation support (Asheim et al., 2003; Cooke et al., 2000). The systemic dimension of the RIS derives in part from the associational character of innovation networks (Cooke and Morgan, 1998). Such relationships, to be systemic, must involve some degree of inter-dependence, though to varying degrees. Likewise, not all such systemic relations need to be regionally contained, but many are. As the interactive mode of innovation grows in importance, these relations are more likely to become regionally contained, for example in the case of specialised suppliers with a specific technology or knowledge base. Such suppliers often depend on tacit knowledge, face-to-face interaction and trust-based relations and, thus, benefit from co-operation with customers in regional clusters, while capacity subcontractors are increasingly sourced globally. Further reinforcing the systemic character of the RIS is the prevalence of a set of attitudes, values, norms, routines and expectations – described by some as a distinctive ‘regional culture’ – that influences the practices of firms in the region. It is this
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common regional culture – itself the product of commonly experienced institutional forces – that shapes the way that firms interact with one another in the regional economy.
Varieties of regional innovation systems The ‘innovation system’ concept can be understood in both a narrow as well as a broad sense. A narrow definition of the innovation system primarily incorporates the R&D functions of universities, public and private research institutes and corporations, reflecting a top-down model of innovation. A broader conception of the innovation systems includes ‘all parts and aspects of the economic structure and the institutional set-up affecting learning as well as searching and exploring’ (Lundvall, 1992, p. 12), and, thus, has a very weak system character. This broad definition incorporates the elements of a bottom-up, interactive innovation model which alternatively could be called ‘learning regions’ (Asheim, 2001). In order to reflect the conceptual variety and empirical richness of the relationships linking the production structure to the ‘institutional set-up’ in a region, Asheim (1998) distinguishes between three types of RISs (see also Cooke, 1998; Asheim and Isaksen, 2002). The first type may be denoted as territorially embedded regional innovation systems, where firms (primarily those employing synthetic knowledge) base their innovation activity mainly on localised, inter-firm learning processes stimulated by the conjunction of geographical and relational proximity without much direct interaction with knowledge generating organisations (i.e. R&D institutes and universities). This type represents basically a market-driven model, where demand factors determine the rate and direction of innovation, and implies the broad definition of innovation systems described by Lundvall (1992) above. Cooke (1998) calls this type ‘grassroots RIS’. The best examples of territorially embedded regional innovation systems are networks of SMEs in industrial districts. Thus in Italy’s Emilia-Romagna, for example, the innovation system can be described as territorially embedded within that particular region (Granovetter, 1985). These territorially embedded systems provide bottom-up, network-based support through, for example, technology centres, innovation networks, or centres for real service providing market research and intelligence services, to promote the ‘adaptive technological and organisational learning in territorial context’ (Storper and Scott, 1995, p. 513). Another type of RIS is the regionally networked innovation system. The firms and organisations are also embedded in a specific region and characterised by localised, interactive learning. However, through the intentional strengthening of the region’s institutional infrastructure – for example, through a stronger, more developed role for regionally based R&D institutes, vocational training organisations and other local organisations involved in firms’ innovation processes these systems have a more planned character involving public-private co-operation. The networked system is commonly regarded as the ideal-type of RIS: a regional cluster of firms surrounded by a regional ‘supporting’ institutional infrastructure. Cooke (1998) also calls this
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type ‘network RIS’. The network approach is most typical of Germany, Austria and the Nordic countries. The regionally networked innovation system is a result of policy intervention to increase innovation capacity and collaboration. SMEs, for example, may have to supplement their informal knowledge (characterised by a high tacit component) with competence arising from more systematic research and development in order to carry out more radical innovations. In the long run, most firms cannot rely exclusively on informal localised learning, but must also gain access to wider pools of both analytical and synthetic knowledge on a national and global basis. The creation of regionally networked innovation systems through increased cooperation with local universities and R&D institutes, or through the establishment of technology transfer agencies, may provide access to knowledge and competence that supplements firms’ locally derived competence. This not only increases their collective innovative capacity, but may also serve to counteract technological ‘lock-in’ (the inability to deviate from an established but outmoded technological trajectory) within regional clusters of firms. The third main type of RIS, the regionalised national innovation system, differs from the two preceding types in several ways. First, parts of industry and the institutional infrastructure are more functionally integrated into national or international innovation systems – i.e. innovation activity takes place primarily in cooperation with actors outside the region. Thus, this represents a development model in which exogenous actors and relationships play a larger role. Cooke (1998) describes this type as ‘dirigiste RIS’, reflecting a narrower definition of an innovation system incorporating mainly the R&D functions of universities, research institutes and corporations. Second, the collaboration between organisations within this type of RIS conforms more closely to the linear model, as the co-operation primarily involves specific projects to develop more radical innovations based on formal analytical-scientific knowledge. Within such systems, cooperation is most likely to arise between people with the same occupational or educational background (e.g. among scientists). This functional similarity facilitates the circulation and sharing of knowledge through ‘epistemic communities’, whose membership may cross inter-regional and even international boundaries (Amin and Cohendet, 2003; Coenen et al., forthcoming). One special example of a regionalised national innovation system is the clustering of R&D laboratories of large firms and/or governmental research institutes in planned ‘science parks’ and ‘technopoles’, normally located in close proximity to universities and technical colleges, but, according to evidence, typically having limited linkages to local industry (Asheim, 1995). Science parks are, thus, an example of a planned innovative milieu comprised of firms with a high level of internal resources and competence, situated within weak local cooperative environments. These parks have generally failed to develop innovative networks based on inter-firm cooperation and interactive learning within the science parks themselves (Asheim and Cooke, 1998; Henry et al., 1995). Technopoles, as developed in countries such as France, Japan, and Taiwan, are also characterised by a limited degree of innovative interaction between firms within the pole, and by vertical subcontracting relationships with non-local external firms. In those rare cases where local
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innovative networks arise, they have normally been orchestrated by deliberate public sector intervention at the national level. These characteristics imply a lack of local and regional embeddedness, and lead us to question the capability of science parks and technopoles to promote innovativeness and competitiveness more widely within local industries (especially SMEs) as a prerequisite for endogenous regional development (Asheim and Cooke, 1998; and Longhi and Quére, 1993).
Can regional innovation systems exist? Bathelt (2003) argues that ‘it seems questionable that region-specific innovation and production processes are typically associated with the existence of regional innovation systems. To assume that such small-scale systems exist bears the risk of underestimating the importance of those institutions which are negotiated and defined at the level of the nation state. In reality, however, regional and national innovation contexts are fundamentally different. Regional production configurations are often dependent on structures and developments which are shaped and take place outside the region (Bathelt, 2003, p. 797).3 The key to the disagreement lies in the application by Bathelt of social systems theory, which replaces the element/relation dichotomy of the innovation systems approach with a system/environment dichotomy (Kaufmann and Tödtling, 2001). This leads Bathelt to believe that one of the core problems of the regional innovation system is ‘that it portrays the region as an entity which hosts a large part of an economic value chain and has a governance structure of its own, independent from its environment’ (Bathelt, 2003, p. 796). Aside from the formal systems theoretical arguments, there is no substantial theory to corroborate this statement. Empirically it may be shown that regions can in fact contain large parts of a value chain (e.g. Italian industrial districts) as well as having a relative autonomous government structure (e.g. regions in federal countries such as Baden-Württemberg in Germany and Catalonia and the Basque country in Spain). Furthermore, in a globalising economy characterised by vertical disintegration and distributed knowledge bases, the important perspective ought to be the interdependences between regions and nations, where the deciding criteria must be the location of core activities (and not the whole value chain as such) and the relative importance of their connections to regional knowledge infrastructures. With the possibly exception of the US, the argument that ‘production configurations are often dependent on structures and developments which are shaped and take place outside’ of the actual territory could as easily apply to most small and medium-sized countries as to regions, especially if being members of supra-national organisations such as the EU, ‘in which ‘region formation’ has and continues to be evolved apace’ (Cooke, forthcoming). Cooke (forthcoming) refers to Bathelt’s position as Listian ‘writing that only nations (presumably meaning states since there are many 3 In a more recent article Bathelt (2005) once more underlines his position by arguing that ‘at this geographical level (i.e. a region, my addition), it is unlikely that a self-referential system can develop because regions are strongly dependent on national institutions and other external influences and lack important political decision-making competencies. … Regional production configurations hardly have the potential to gain and retain structural independence and reproduce their basic structure.’
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nations without full economic governance powers) have specificity and that they may also be closed systems’. Yet it is essential to recognise the, by inference, interlocked character of a region in a wider geographical context (Howells, 1999). But even if research has revealed that the regional level is neither always nor even normally sufficient for firms to stay innovative and competitive (Isaksen, 1999), and that the learning process becomes increasingly inserted into various forms of networks and innovation systems (at regional, national and international levels), the continuous importance of the regional level is confirmed by results from a European comparative cluster survey (Isaksen, 2005). This study shows that regional resources and collaboration are of major importance in stimulating economic activity in the clusters. However, the survey found an increased presence of MNCs in many clusters, and also that firms in the clusters increasingly source major components and perform assembly manufacturing outside of the clusters (Isaksen, 2005). Also Tödtling and Trippl (2005) found empirical support for clustering because of the importance of social interaction, trust and local institutions. Yet they also note that both local and distant networks are often needed for successful cooperative projects, in particular for projects of innovation and product development when it is usually necessary to combine both local and non-local skills and competences in order to go beyond the limits of the region (see also Asheim and Herstad, 2003; Bathelt et al., 2004; Cooke et al., 2000).
Clusters In recent years the cluster concept has become somewhat of a catchword in academic circles as well as in policy discussions on regional economic development. Thus, what is a cluster? In a recent article Porter defines clusters as ‘geographic concentrations of interconnected companies and institutions in a particular field. Clusters encompass an array of linked industries and other entities important to competition. They include, for example, suppliers of specialised inputs such as components, machinery, and services, and providers of specialized infrastructure. Clusters also often extend downstream to channels and customers and laterally to manufacturers of complementary products and to companies in industries related by skills, technologies, or common inputs. Finally, many clusters include governmental and other institutions – such as universities, standards-setting agencies, think tanks, vocational training providers, and trade associations – that provide specialised training, education, information, research, and technical support’ (Porter 1998, p. 78). As a contrast, Porter's original cluster concept was basically an economic concept indicating that ‘a nation's successful industries are usually linked through vertical (buyer/supplier) or horizontal (common customers, technology etc.) relationships’ (Porter 1990, p. 149). These ideas are more or less the same as the ones Perroux presented in the early 1950s. Perroux argued that it was possible to talk about ‘growth poles’ (or ‘development poles’ at a later stage in his writing) in ‘abstract economic spaces’ defined as the vertical relationships of a production system as well as the horizontal relationships of a branch, where firms were linked together by an innovative ‘key industry’ to
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form an industrial complex. According to Perroux, the growth potential and competitiveness of growth poles can be intensified by territorial agglomeration (Haraldsen, 1994; Perroux, 1970). However, even in 1990 Porter argued along the same lines as Perroux by emphasising that ‘the process of clustering, and the interchange among industries in the cluster, also works best when the industries involved are geographically concentrated’ (Porter 1990, p. 157). Porter has often been criticised for lack of academic rigour with regard to his approach to the study of as well as definition of clusters. Martin and Sunley (2003), for example, identify a major source of confusion in Porter´s work of defining and studying the existence of clusters and the effects of cluster dynamics. They identify two major definitional problems in the writings of Porters. The first major problem lies in the delimitation of the clusters, spatially as well as sectorially. Sectorially, it is a difficult question how to delimit the cluster with respect to the range of activities included and the links between them, as well as the requirements to the degree of sectoral specialisation. Spatially, it seems highly unclear within which boundaries ‘real’ cluster dynamics, for example spill-over effects, can arise and operate. Second, they point to the fact that the social dimension, considered so important in facilitating cluster dynamics, is insufficiently theoretically defined and developed in his cluster thinking. Malmberg (2003) attributes much of the conceptual confusion concerning clusters to the fact that clusters can be seen as both industrial and spatial phenomena, i.e. either confined to industrial systems defined from a functional (national) perspective, or defined by geographical (regional) boundaries. But instead of regarding these multiple definitions of clusters as problematical, Malmberg seems to accept the possibilities of using both definitions. Here I agree with Malmberg’s view of the need to operate with both conceptualisations of clusters, as it is a quite normal situation to find (geographical) clusters of specialised branches being part of a national (economic) cluster of the same branches. Porter (2000) argues that the existence of a cluster has positive effects on the competitive advantage of firms in a number of ways, one of them being a positive impact on the innovation capabilities of the cluster firms. According to Porter “untangling the paradox of location in a global economy reveals a number of key insights about how companies continually create competitive advantage. What happens inside companies is important, but clusters reveal that the immediate business environment outside companies play a vital role as well” (Porter 1998, p. 78). The pressure to innovate is promoted through local rivalry, increasing the necessity to be innovative among firms in the cluster. Moreover, co-location and proximity further facilitates learning through close collaboration and interaction with other firms stimulating innovative activities. The co-location within a cluster, thus, enables strong relationships between producers and suppliers, integrating local suppliers in the innovation process. Furthermore, the specialised labour market is one of the more important components in this respect, providing firms in the cluster with skilled labour, which is necessary in order to enhance the innovative performance of the cluster (see Porter, 2000). Thus, Porter consequently argues that “a vibrant cluster can help any company in any industry compete in the most
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sophisticated ways, using the most advanced, relevant skills and technologies” (Porter 1998, p. 86). What Porter’s extension of the definition of the cluster concept also to incorporate public agencies and knowledge infrastructures indicates is a deepening and widening of the degree and form of co-operation taking place in a cluster. The original and simplest form of co-operation within a cluster can often be described as a territorial integrated input-output (value chain) relations, which could be supported by informal, social networking, but which could also take the form of arms-length market transactions between a capacity subcontractor and the client firm. The next step of formally establishing inter-firm networks is represented by a purposeful, functional integration of value chain collaboration as well as building up a competence network between the collaborating firms. A distinction between clusters defined as input-output relations and networks is that proximity is the most important constituting variable in the first case, while networking represents a step towards more systemic (i.e. planned) forms of co-operation, as well as a development from vertical to horizontal forms of co-operation, which more efficiently promotes learning and innovation in the systems. The development towards more systemic forms of co-operation is taken a step forward by establishing systems in the form of production and innovation systems, which are characterised by system integration.
Knowledge base and institutional framework: Connecting clusters and regional innovation systems
An explicit conceptual clarification of the linkage between on the one hand clusters and on the other regional innovation systems has so far received relatively little attention in the literature. Notwithstanding Porter’s (2000) extension of the cluster concept which more or less eliminates the differences between clusters and regional innovation systems, by distinguishing between the cluster’s knowledge base and the extent of loose/tight linkage with the regional innovation system, the different industrial development paths of ‘pure’ clusters where regional innovation systems are build in order to support innovation in already established industries, and the formation of relations between clusters and regional innovation system from the emergence of the cluster, could be explained in a more systematic way. In traditional cluster-regional innovation system relations, based on industries with a synthetic knowledge base, the logic behind building regional innovation system is to support and strengthen localised learning of an existing industrial specialisation, i.e. to promote historical technological trajectories based on ‘sticky’ knowledge. In contexts of a regional innovation system as a necessary part of the cluster development, it is a question of promoting new economic activity based on industries with an analytical knowledge base, requiring close and systemic industry-university cooperation and interaction in the context of e.g. science parks, located in proximity of knowledge creating organisations (e.g. (technical) universities). In this case a narrow definition of regional innovation systems will normally be applied (i.e. incorporating relationships between R&D functions of universities, public and private research institutes and corporations), while in the first case it is more often a question of exploiting the resources and capabilities of a regional innovation system
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broadly defined. In both of these cases it is a question of regional clusters exploiting localisation economies (e.g. industrially specialised clusters). Regional innovation systems are also found in regions exploiting urbanisation economies. In such regions, which by definition, are constituted by an urban agglomeration, the regional innovation system is normally characterised by a diversified industrial base in contrast to the specialised base of typical regional clusters (e.g. industrial districts), and where different historical and emerging technological trajectories co-exist. Thus, within such urban agglomerations it is possible to identify the existence of relations between clusters and regional innovation systems as a necessary condition for cluster development as well as traditional clusters which established links with regional innovation systems at a later stage in their life cycle. It could, however, be argued that the diversity of urbanisation economies is especially important in the promotion of radical innovations, and, consequently, of great significance for industries based on an analytical knowledge base. The co-existence of many intra-regional clusters with various knowledge bases and different relations to the regional innovation system will require more developed governance structures in order to secure a planned and systematic co-ordination between industry and knowledge creating and diffusing organisations, which, consequently, may imply an innovation system of a ‘triple-helix’ character.
Learning regions Learning regions should be looked upon as a policy framework or strategy for formulations of long term partnership-based development strategies initiating learning-based processes of innovation, change and improvement. In the promotion of such innovation supportive regions the inter-linking of co-operative partnerships ranging from work organisations inside firms via inter-firm networks to different actors of the community, understood as “regional development coalitions”, will be of strategic importance. By the concept “development coalition” is meant a bottom-up, horizontally based co-operation between different actors in a local or regional setting, based on a socially broad mobilisation and participation of human agency. (Ennals and Gustavsen, 1999). The attractiveness of the concept of learning regions to planners and politicians is to be found in the fact that it at one and the same time promises economic growth and job generation as well as social cohesion. As such, learning regions must be analysed as an answer and challenge at the regional level especially for regions with weak territorial competence bases to contemporary changes in the global economy, underlining the strategic role played by social capital’s emphasis on the social and cultural aspects “encompassing the norms and networks facilitating collective action for mutual benefit” (Woolcock, 1998, p. 155).
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The building blocks of the concept of learning regions The concept of “learning regions” has been used in at least three different contexts. The concept was first introduced by economic geographers in 1995 (Florida 1995), when they used it to emphasise the role played by co-operation and collective learning in regional clusters and networks in order to promote the innovativeness and competitiveness of firms and regions in the globalising learning economy (Asheim 1996; 1997; Morgan 1997). This approach was clearly inspired by the rapid economic development in the “Third Italy”, which drew the attention towards the importance of co-operation between SMEs in industrial districts and between firms and local authorities at the regional level in achieving international competitiveness (Asheim 2000). The second approach expressing (more indirectly) the idea of learning regions originates from the writings of new evolutionary and institutional economics on the knowledge and learning based economy, where knowledge is considered the most fundamental resource and learning the most important process (Lundvall 1992), thus making the learning capacity of an economy of strategic importance to its innovativeness and competitiveness. Lundvall and Johnson use the concept of «learning economy» when referring to the contemporary post-Fordist economy dominated by the ICT-related (information, computer and telecommunication) techno-economic paradigm in combination with flexible production methods and reflexive work organisations (i.e. learning organisations and functional flexible workers) (Lundvall and Johnson 1994). In addition the learning economy is firmly based on «innovation as a crucial means of competition» (Lundvall and Johnson 1994, p. 26), where innovation is understood as interactive learning in contrast to the previous hegemonic linear model of innovation. The third approach, which conceptualises learning regions as regionally based development coalitions, has lately been applied by representatives of action oriented organisational research taking their knowledge of how to form intra- and inter-firm learning organisations based on broad participation out of the firm context and using it to establish learning organisations at the regional level (Ennals and Gustavsen 1999). This strategy builds on Scandinavian experiences,4 which have shown that flat and egalitarian organisations have the best prerequisi tes of being flexible and learning organisations, and that industrial relations characterised by strong involvement of functional flexible, central workers is important in order to have a working "learning organisation". Such organisations will also result in well functioning industrial relations, where all the employees (i.e. the (skil-led) workers as well as the managers) will have a certain degree of loyalty towards the firm. Also Lundvall and Johnson argue that "the firm's capability to learn reflects the way it is organised. There is a movement away from tall hierarchies with vertical flows of information towards more flat organisations with horizontal flows of information which is one aspect of the learning economy" (Lundvall and Johnson 1994, p. 39).
4 Referred to as, for example, "Kalmarism" in contrast to "Fordism", "Neo-Taylorism" and "Toyotism" in the international academic literature (Leborgne and Lipietz, 1992).
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The Triple Helix The Triple Helix perspective has achieved a big attention among policy makers as well as researchers within innovation research (Etzkowitz and Leydesdorff, 2000). It underscores the increased interaction and interdependence between universities – industry – government in modern, knowledge-based economies by acclaiming the transformation of the entrepreneurial university. However, so far this perspective has been applied in a rather static way, more like a heuristic device than as a basis for actual policy formulations. This is also the weakness of the approach, as it does not give much guidance concerning how a Triple Helix-based collaboration could be functional, operational and implemented in concrete policy settings. In order to achieve this, theoretical and practical advice must be developed partly with respect to how collaboration between the three actors of the Triple Helix should be externally organised, and partly how innovation oriented work should be organised internally among the different actors. The ‘Triple-Helix’ approach maintains that in a swiftly emerging knowledge economy those places with entrepreneurial universities would increasingly see growing demand for knowledge transfer to industry and, through government, to society. Moreover, the spread of universities is less asymmetric over space than R&D. In this perspective it is proposed that industry and government will be prepared to pay more for privileged access to knowledge-based growth opportunities by funding more research, stimulating closer interactions among the three institutional partners, subsidising infrastructure (e.g. incubators and science parks) and stimulating academic entrepreneurship skills and funding. The exemplar par excellence of this phenomenon is MIT, which is to say the least, a successful case. However, not surprisingly, research has found that a model design based on MIT worked poorly in different contexts with more average universities and regions (e.g. Australia and Sweden). This is a classic instance of the asymmetric knowledge problem that Triple Helix proponents overlook. Thus while the abstract principles of Triple Helix rapprochement hold in general among such distinct ‘epistemic communities’ as the three implied, the boundary-crossing effort required can in reality defeat the unwary (Cooke, 2005). As part of the specific triple-helix context policies have been formulated and implemented promoting SME’s contacts with R&D institutes and more frequent use of R&D, while universities at least in Finland and Sweden for some years have been given a so called ‘third role’, i.e. to cooperate externally with the surrounding society in addition to doing research and teaching. However, so far little or nothing has been done concerning changing behaviour of the third actor of the triple-helix, i.e. the government, as well as with the Triple Helix system as a whole. And as the Triple Helix perspective as already emphasised is extensively used in the construction of regional advantages an improved knowledge of how to make the system functional would be an efficient strategy of optimising private-public interaction. An important part of this is to develop a more innovation oriented public sector, which means focusing on learning aiming for behavioural value-added at both universities and government at different geographical levels (national, regional and local), in addition to doing the same with the private sector.
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However, so far Triple Helix thinking draws attention only to possible but weakly generalisable broad outlines of important contemporary innovation interactions.
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European Commission CONSTRUCTING REGIONAL ADVANTAGE – FULL REPORT principles – perspectives - policies Belgium: EC 2006 — 104 pp. — 21.0 x 29.7 cm
PRINTED by EC - DG RESEARCH
The current report has been prepared by an independent expert group throughout the year 2005. The work of this Expert Group is to be seen fully against the context of the Barcelona objective, namely achieving average investment in Research and Development of 3% of the Union’s GDP by 2010. The 3% Action Plan identified the need for regions to become more efficient in using their resources for investing in R&D. It also pointed to the need of setting up learning initiatives for the regions. EU needs expertise in finding their routes to the knowledge economy and the contribution of the Expert Group on ‘Constructing Regional Advantage’ has revealed important in this respect.