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innovatie
wetenschap
technologie
ST
UD
I E S
28The F lemish Innovation System : an external v iewpoint
VLAAMS INSTITUUT VOOR DE BEVORDERING VAN HET WETENSCHAPPELIJK-TECHNOLOGISCH ONDERZOEK IN DE INDUSTRIE
ST
UD
I E S
Henri CapronMichele C incera
IWT-Studies worden uitgegeven door het IWT in het kader vanhet werkprogramma van het IWT-Observatorium. De auteurszijn echter persoonlijk verantwoordelijk voor de standpunten dieworden ingenomen bij de uitwerking van deze Studies.
Redactie } Ann Van den Bremt (secretariaat)Jan Larosse (coördinatie)
Productie } Lemahieu & Partners
Copyright } reproductie en gebruik is toegestaan mits bronvermelding.
IWT-ObservatoriumJan Larosse, CoördinatorDonald Carchon, InformatiesysteemAnn Van den Bremt, SecretariaatVincent Duchêne, Beleidsanalyse
Bischoffsheimlaan 251000 Brussel
Tel.: 02/209 09 00Fax: 02/223 11 81E-mail: [email protected]: http://www.iwt.beDepotnummer: D/1999/7037/12Verschenen in april 1999
CC oo ll oo ff oo nnColofon
28The F lemish Innovation System : an external v iewpoint
Prof . Henr i Capron and Prof . Michele C inceraUniversité L ibre de Bruxel les
2
Empirical works in regional economics show that innova-tive activities tend to cluster spatially together, and thatlocation matters. Although it cannot be argued thatregional innovation profiles are conditioned by nationalcontingencies and European strategies, it is also right thatlarge differences in regional profiles within a country canonly be explained by regional factors. Although the histor-ical roots of regional S&T policies are the same inBelgium, regional S&T policies have evolved in radicallydifferent directions, which can be explained by cultural,historical, economic and political factors.
The present study analyses the Flemish Innovation System(VINS) by looking at the profile of its governance structurecompared with that of the other Belgian regions as well assome of the most dynamic European regions. Morespecifically, the stress is put on the analysis of the fivemajor components of any innovation system: a compar-ative analysis of the regional distribution of the mainactors of the Belgian Innovation System and its implica-tions for the VINS, the role played by the education andtraining system, the regional differences in R&D expendi-tures and the technological position of regions at aEuropean level, the performance of regions as partners inEuropean research networks and the regional innovationoutputs as measured by patents.
Flemish firms account for around two thirds of BelgianR&D investments against a quarter in Wallonia and therest in the Brussels region. The quality of humanresources is a main factor of economic growth and com-petitiveness. Data show that Flemish students obtain bet-ter results than those of the French Community. Althoughthe Flemish region has a slight disadvantage with respectto its Southern counterpart in higher education, it has amore balanced distribution of students among educationcategories. The Belgian distribution of the active popula-tion differs significantly from the European average and ischaracterised by a dual working force. Furthermore, with-in Europe, Belgium is one of the countries with the lowestemployment rates.
The GDP per capita indexes show that Flanders andBrussels have been able to efficiently exploit their eco-nomic advantages while the economic base of the
Walloon region has been largely affected by the decline ofindustrial activities. At a European level, regional R&D dis-parities appear really deeper than wealth ones. A cluster-ing analysis of European regions shows that the clusterwhich contains Flanders is characterised by a high cre-ative capacity and degree of innovativeness compared tothe European average. The regions included in this clus-ter present a high potential of endogenous development.
The high Belgian participation in European R&D pro-grammes is characterised by a particularly importantnumber of collaborations with neighbouring countries. Ata regional level, the participation of Flanders and theFrench Community are balanced. At the infra-regionallevel, five districts concentrate three quarters of participa-tions. The Belgian participation in EUREKA projects ishighly concentrated in a few districts, mainly located inthe Flemish region, especially in the districts of Ghent andLeuven. In addition to the higher participation of Flandersin European networks, infra-regional links are stronger inFlanders than in other regions. A question mark is cer-tainly the lesser propensity of both Flemish and Walloonteams to collaborate together. Except for Brussels, intra-regional collaborations are more important than inter-regional ones. Besides the European projects, enterprisescan decide to enter into alliances on a private base. Thedata available on technological co-operation betweenenterprises in the world indicate that the alliances in whichBelgian enterprises are active, are limited.
The regional distribution of Belgian patents shows anincrease over the period 1978-1997. Yet this increase hasbeen markedly higher in Flanders, in particular since themid eighties. Furthermore, the returns of technologicalactivities in terms of patents with respect to R&D activitiesappear to be higher in the Flemish region. At the geo-graphic level, the district of Antwerp accounts for morethan one quarter of the patents. Belgium, with a high pro-portion of its inventors working for extra-national firms orforeign firms with subsidiaries located in Belgium but thatdo not patent as Belgian firms, is one of the Europeancountries the most concerned by the ‘knowledge drain’phenomenon. This raises the question of whether theR&D outcomes of some of these multinationals are effec-tively exploited in Belgium or simply brought back to the
SS uu mm mm aa rr yySummary
3
foreign mother company. The comparison of regionaltechnological specialisation patterns suggests thatFlanders holds a higher share of its patent distribution ininstruments and Wallonia and Brussels in chemicals andpharmaceuticals. The indexes of technological proximitysuggest asymmetric spillover effects across regions sinceBrussels appears to be «technologically» closer toWallonia than Flanders and Flanders is closer to Walloniathan Brussels.
In the framework of the emerging VINS, the policy focusshould be put on strengthening the knowledge infrastruc-ture. Three main types of actions deserve special atten-tion: the strenghtening of the knowledge base, the designand the implementation of S&T policy and the enhance-ment of the knowledge distribution power.
5
CC oo nn tt ee nn tt ss
Summary
Forword
1. Introduction
2. Regional or National Innovation Systems: which matters?2.1. Theoretical foundations of Regional Innovation Systems2.2. The Belgian Innovation System
3. The Education & Training challenge
4. Regional R&D intensities and technological bases4.1. Characteristics of regional R&D systems4.2. The European regional R&D disparities
5. Technological collaborations5.1. Pre-competitive research collaborations5.2. Near-market research collaborations5.3. Strategic alliances
6. Technological output6.1. Regional evolution of the patenting activity6.2. Explaining regional differences in patenting profiles6.3. Regional specialisation patterns
7. S&T policy perspectives7.1. S&T lessons from the VINS 7.2. Improving regional S&T policy
References
Appendices
Contents
2
7
8
11
16
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30
44
57
64
67
7
Het IWT-Observatorium heeft in de voorbije twee jaar eenimpuls gegeven aan het verzamelen van innovatie-indica-toren en aan de analyse van het Vlaams Innovatiesysteemmet een reeks onderzoeksopdrachten die resulteerden inbijna dertig verschillende Studies. Het moment is dusaangebroken voor een eerste synthese. Daarvoor hebbenwe een beroep gedaan op een 'buitenstaander', voor eenmeer afstandelijke evaluatie van het Vlaams innovatiesys-teem aan de hand van de beschikbare indicatoren. HenriCapron en Michele Cincera (ULB) zijn niet alleen expertenop het vlak van innovatiestudies maar ook gespecialiseerdin regionale economie wat hen uitermate deskundig maaktvoor het uitvoeren van deze opdracht. Bovendien konden zijhiervoor voortbouwen op het extensief onderzoek over het'Belgisch innovatiesysteem', uitgevoerd in samenwerkingmet de onderzoeksploeg van Wim Meeusen, dat door deDWTC werd gesteund in het kader van het project 'nation-al innovation systems' van de OESO*.
Deze achtergrond verklaart ook de specifieke focus vandeze Studie. Het Vlaams Innovatiesysteem wordt geanaly-seerd als een 'emerging innovation system' met historischewortels in een Belgisch Innovatiesysteem. Vanaf welk sta-dium een bepaalde institutionele configuratie voldoendesysteemautonomie heeft om als zelfstandig systeem teworden gepercipieerd is echter een kwestie van appreci-atie die puur wetenschappelijke criteria overstijgt. Hetinnovatiesysteem is dan ook een beleidsmodel dat vanuithet perspectief van de beleidsmaker wordt gedefinieerd,op elk niveau van beleidsvoering. In die zin is het inno-vatiegebeuren in Vlaanderen onderdeel van interactiesdie zowel op regionaal, nationaal, Europees en mondiaalvlak kunnen worden begrepen en gestuurd. Het 'VlaamsInnovatiesysteem' is dus het beleidskader voor de hetVlaams innovatiebeleid dat hiervoor de institutionele hef-bomen en socio-politieke krachten mobiliseert die hethiervoor ter beschikking heeft. Het 'subsidiariteitsbeginsel'ten overstaan van nationale en internationale beleid-sniveau's is daarbij een belangrijke randvoorwaarde.Maar het recente Innovatiedecreet toont aan in welkemate het Vlaams beleid zijn autonome beleidsmarge kanbenutten om vooruit te gaan in het efficiënt uitbouwenvan het innovatiesysteem. Zij bekroont dan ook de vol-wassenwording van het Vlaams Innovatiesysteem in dejaren negentig als een systeem met een eigen identiteit.
De systeembenadering houdt voor het innovatiebeleid deboodschap in dat naar het samenspel van respectievelijkactoren, activiteiten en indicatoren moet gekeken wor-den. De auteurs rapporteren gunstig over de relatieveprestaties van de Vlaamse bedrijven en onderzoeksin-stellingen in federaal en Europees verband, maar moetenhiervoor nog veel teruggrijpen op de traditionele input- enoutputindicatoren (O&O en octrooien) van de kennispro-ductie. Er zijn nog maar weinig procesindicatoren terwijljuist de frequentie en de kwaliteit van kennistromen vandoorslaggevend belang is voor de kenniscreatie en deomzetting van die kennis in economische en maatschap-pelijke waarde. In eerdere Studies is over het belang van samenwerking inO&O en innovatie reeds onderzoek gedaan. Wij hopendat hierrond, en rond andere thema's in verband met dekarakteristieken van het Vlaams Innovatiesysteem, meeronderzoek kan gebeuren binnen het luik longitudinaleinnovatiestudies van het Programma BeleidsgerichtOnderzoek dat de Vlaamse Regering dit jaar opstart.
Deze Studie verschijnt uitzonderlijk in het engels. IWT-Studies wou aan zijn gastauteurs niet de verplichtingopleggen om in het nederlands te schrijven. De auteurs,die dus franstalig zijn, hebben er zelf voor gekozen omdeze gastvrijheid te beantwoorden door het engels tegebruiken. Wij hopen dat hierdoor ook een ruimer, inter-nationaal publiek kennis kan nemen van deze interes-sante synthese.
Paul Zeeuwts Christine ClausVoorzitter Directeur-generaal
* H. Capron, W. Meeusen (Eds), The National Innovation System of Belgium,Springer Verlag, Berlin, 1999.
FF oo rr ee ww oo rr ddForeword
8
SS ee cc tt ii oo nn 116
The present focus on National Innovation Systems (NISs)leads one to consider that regional and local dimensionsare to a large extent determined by national contexts. Yet,Belgium is a counterexample of the limits of such arestricted viewpoint. Over the past fifteen years, regionaleconomics have shown that regional and local dimen-sions are vital elements of the innovation dynamics andthat innovation is in itself a geographic process. Theimportance of regional contexts has been particularlyunderlined by empirical works on industrial districts andinnovative milieus. They show that innovative activitiestend to cluster spatially and that location matters.Regional incubator centres, science and technologyparks, technopoles and technology centres have prolifer-ated in all the industrialised countries. This observationunderlines the present trend towards the regionalisationof research and development policy in all industrialisedcountries over the last decade. Furthermore, the conceptof regional innovation systems is emerging. So, on thebasis of some European case studies1 (Baden-Wurttemberg, Rhône-Alpes, Catalonia, Noord-Holland,Piemonte,…) some authors have identified different pro-files of regional innovation systems. Although it cannot becontested that regional innovation profiles are condi-tioned by national contingencies and European strategies,it is also true that large differences in regional profileswithin a state can only be explained by regional factors.Although the historical roots of regional Science andTechnology (S&T) policies are the same in Belgium,regional S&T policies have evolved in radically differentdirections, which can be explained by cultural, economicand political factors.
A recent study2 has attempted to analyse the characteris-tics of the Belgian innovation system. Although this studytakes the regional dimension into account, its nationalfocus has limited the study of the regional component toits links and incidences on the national innovation systemand, furthermore, has not deepened the regional implica-tions of observations. The present study analyses theFlemish Innovation System (VINS)3 along the lines devel-oped in the study of the Belgian innovation system andcompared with the two other regions. IWT-VTO workingpapers give sound analyses of the characteristics of theVINS. The object of the analysis is to complete and further
investigate some aspects examined in these studies bylooking at the profile of the regional governance structureof the VINS compared with that of the other Belgianregions as well as some of the most dynamic Europeanregions in terms of interdependencies, specificities andcomplementarities.
With reference to our contribution to the analysis of theBelgian innovation system, it is suggested to give toFlemish authorities an external and closer viewpoint ofstrengths and weaknesses of the VINS on the basis of acomparative analysis of Belgian regional profiles and,hopefully to open new opportunity windows for closerinter-regional cooperation. In the study, the stress is puton the analysis of the five following major components ofany innovation system:
• A comparative analysis of the regional distribution of themain actors of the NIS and their implications for theVINS: higher education institutions (HEIs), research andtechnology institutions (RTOs), bridging institutions andenterprises. In fact, there is an impressive contrastbetween the Belgian regions with respect to public insti-tutions engaged in S&T activities and private businessfirms known to be active in R&D activities.
• Needless to say, the human capital accumulated bynations is one of the main determinants of present andfuture economic prosperity. Indeed, the educationalattainment of the labour force has a positive impact notonly on skills and competencies but also as a result onproductivity of workers. It seems therefore interestingwhen analysing the BIS to look at the relative effective-ness of the Belgian education systems compared toother highly industrialised countries. From a policy per-spective, it is also useful to know whether there are anyregional differences in the activity rates of Belgiumactive and occupied population or in the level of quali-fication of the unemployed.
• The regional differences in R&D expenditures and R&Dcollaborations between Belgian firms and other actorsof the NIS suggest that regional profiles with regard tothe innovation process matter and call for specificregional policies adapted to the existing economic
Introduction
9
structure. In order to define their R&D objectives, firmscan collaborate with different types of bodies (cus-tomers, suppliers, universities, research centres,…).Data show that there are very distinct regional behav-iours of firms in this field. A main question is to know towhat extent it is a consequence of regional industrialspecialisation patterns or of S&T strategies implement-ed and supported by public authorities.
• If the three Belgian regions are very active partners inEuropean networks (Community framework pro-grammes as well as EUREKA projects), the distributionis not the same among regions. This could be seen asthe source of some regional complementarities in theinnovation process on the one hand, and as the originof some regional weaknesses to be corrected by appro-priate policy actions, on the other. In fact, the Belgianregions appear into be very differently integrated intothe European networks, which could be a consequenceof the structural differences of regional S&T systemsand/or of strategies implemented by regional publicauthorities. These issues are analysed with reference tothe information available in the CORDIS database aswell as that of EUREKA.
• Regarding the innovation output, data on patent appli-cations are presently one of the main sources of infor-mation which can be used to compare regional techno-logical productivities. In this field, significant regionaldifferences can also be observed from the analysis ofUSPTO (United States Patent Office) and EPO(European Patent Office) data when applicants are con-sidered. What is the orientation of regional R&D sys-tems (product versus process)? What are the regionaltechnological specialisations (revealed technologicaladvantages)? What are the most innovative districts andtheir fields of specialisation? To what extent are theycomplementary or substitutable?
The main object of the following sections is to identify,analyse and shed some light on policy implications of dif-ferences in Belgian regional innovation profiles. Althoughbased on a comparative analysis of Belgian regional pro-files, the policy implications that complete the diagnosiswill be naturally focussed on strategic challenges which
the Flemish region is or could be faced with. This researchis expected to give further useful pieces of information tothe Flemish region with regard to the main characteristicsof the VINS, its strenghts as well as its weaknesses. To alarge extent, any regional innovative capacity takes itsroots at the cultural level. Innovation is only possible if weare able to learn from each other and economic growthcan only be sustainable if a region is able to learn to avoidthe mistakes made by regions whose development ispresently challenged by new economic trends.
The plan of the study is as follows. Section 2 defines somekey concepts of national innovation systems and reviewsthe main approaches to analysing innovation systems. Inparticular, the stress is put on whether it is more relevantto perform such an analysis at national or at regionallevel. Yet, as technological capabilities of a country arethe combined result of local, regional and national con-texts and environments, no clear-cut answer can bebrought to the fore. Whatever the choice, one cannotavoid a simultaneous analysis of these three inter-twineddimensions. Some first elements of answers to this ques-tion are given by briefly describing the main componentsof the Belgian National Innovation System. Section 3investigates the question of the education and trainingchallenge induced by the emergence of techno-globalisa-tion and the new technological environment. The skillsand competencies of human capital are at the root of theeconomic prosperity and competitiveness of nations.Hence, it seems useful to assess the Belgian performancecompared to the European average in terms of the effec-tiveness of its education system and the qualification levelof its work force. Given the «communautarisation» of theeducational system in Belgium, it is also interesting to tryto explain the regional differences detected in terms of thescores obtained by the Belgian regions.
It is commonly acknowledged that there is an economicgap among Belgian regions. An immediate question thatarises when studying the Belgian innovation performanceis whether there are similar disparities among regions interms of technological activities and whether they are aresult of the economic gap. Section 4 explores this ques-tion at European scale by implementing a technology-based cluster approach of Belgian regions besides
1 0 1 . I n t r o d u c t i o n
European ones. The clustering is obtained by identifyingthe main sources of technological performances on thebasis of several constructed indexes that pick up theregional technological bases and intensities, productivityand competitiveness. Section 5 is concerned with techno-logical collaborations. Three kinds of collaborations, i.e.pre-competitive research, near-the-market research andstrategic alliances, are investigated in order to understandthe extent to which Belgian firms, research centres anduniversities are engaged in international research net-works. Besides the significant regional differences, theanalysis of collaborative links sheds some light on the spa-tial, institutional and technological specialisation patternsof Belgian regions as well as of their main actors. Section6 analyses the technological output of Belgian regionsand actors as measured by patenting activities. Theregional evolution of patent applications and grants givesevidence of important regional disparities which can befurther investigated by looking at the most dynamic firmsin terms of innovative performance, the composition ofresearch activities and the specialisation patterns in tech-nological fields. Section 7 offers some conclusions andpolicy perspectives following the main findings obtained inthe study.
1 See for instance the recent CORDIS initiative that focuses on research and inno-vation in the European regions. See also the compendium of analyses editedby Braczyk, Cooke and Heidenreich (1998).
2 Capron et al. (1998).3 In the study, use will be made of the acronym adopted by the Flemish region,
"Vlaams Innovatie System".1Over the past fifteen years, regional economics has
shown that regional and local dimensions are vital ele-ments of the innovation dynamics and that innovationis in itself a geographic process. The present studyaims to look at the strengths and weaknesses of theVINS on the basis of a comparative analysis of Belgianregional profiles. To a large extent, any regional inno-vative capacity takes its roots at the cultural level.Innovation is only possible if we are able to learn fromeach other and economic growth can only be sustain-able if a region is able to learn to avoid the mistakesmade by regions whose development is presentlyhardly challenged by new economic trends.S
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The systemic approach is now largely recognised as rele-vant from a policy-making point of view to analyse theinteraction between institutions that contribute to the per-formance of innovation processes. In the Belgian case, itmay be more appropriate to talk about regional innova-tion systems given that regions have become the naturalboundary of the institutional set-up. To a large extent, theconceptual and theoretical foundations of the systemicapproach have to be consolidated. Only some major con-cepts will be discussed here to grasp the practical scopeand consequences of the federalisation of the Belgianinnovation system.
2.1. THEORETICAL FOUNDATIONS OF REGIONAL
INNOVATION SYSTEMS
The recent stress on the systemic approach of innovationhas given rise to studies looking for national structuralcharacteristics that underlie NISs. According to Lundvall(1992), globalisation and regionalisation might be inter-preted as processes which weaken the coherence andimportance of national innovation systems. Yet, at anoperational level, a main question is to know to whatextent the institutional configuration of actors at nationallevel must be recognised as the masterpiece of innovationsystems and that the international downstream links aswell as the specifically regional upstream actions have tobe seen as directly conditioned by national patterns. Butperhaps a more vital question is to investigate what canbring the local and regional dimensions to the analysis ofinnovation systems.
A main question mark in the Belgian case is certainly toclarify at which level it is the most relevant to analyse theinnovation system: can we still speak about a nationalinnovation system or is the Belgian innovation system(BIS) nothing other than the simple juxtaposition (withonly very minor interregional technological intertwinings)of regional innovation systems (RISs) as it is mainly thecase at the European level in the present state-of-the-artof European integration.
In order to clarify this point it is worth defining what char-acterises a region and the components that could makethe region or even the local area, not the nation, the cen-
tral part of an innovation system. This point is not only aconceptual one but has very important pragmatic impli-cations on the way the analysis should be realised. As afirst step, it is important to enlighten what characterises aNIS.
Several definitions of a NIS have been given in the litera-ture [Freeman (1987), Lundvall (1992), Nelson (1993),Patel and Pavitt (1994), Metcalfe (1995)]. Fortunately,they overlap and the one suggested by Metcalfe will beretained as the most complete. Metcalfe (1995) definesthe national system of innovation as « the set of distinctinstitutions which jointly and individually contribute to thedevelopment and diffusion of new technologies and whichprovides the framework within which governments formand implement policies to influence the innovation sys-tem. As such it is a system of interconnected institutionsto create, store and transfer the knowledge, skills andartefacts which define new technologies ». A first questionhere is to know which government matters: the regionalgovernments or the Belgian one. If historically it is theBelgian government which has designed the S&T policy,in the last years, it is the regional governments which havegiven major specific inflexions to the S&T policy ofregions. Over the past two decades, regional S&T policieshave been designed with respect to regional industrial andscientific specialisation patterns as well as to specific pol-icy choices.
As pointed out by Cooke (1998), RISs can be viewed as acollective order based on microconstitutional regulationconditioned by trust, reliability, exchange and cooperativeinteraction. According to de Vet (1993), it is the institu-tional capacity to attract and animate competitive advan-tage that gives regions a strong conceptual and real iden-tity. In a wider sense of Johnson’s (1988) observationabout the importance of efficient institutional design forsmall countries, we can say that the need for an institu-tional system which stimulates technical innovation is rel-atively strong for regions. The possible benefits of such asystem are considerable, as are the potential costs of insti-tutional rigidity.
If the concept of RIS is a relatively new one, some foun-dations can be found in the regional science literature.
SS ee cc tt ii oo nn 22Regional or National Innovation Systems: which matters ?
1 2 2 . R e g i o n a l o r N a t i o n a l I n n o v a t i o n S y s t e m s : W h a t m a t t e r s ?
So, for example, the link between regional developmentand the innovation process has been implemented byAydalot (1986) around the concept of «innovativemilieux» which is clearly a systemic approach. The Italianrejuvenation [Beccatini (1989), Brusco (1990)] of theMarschallian concept of industrial districts, which are inte-grated areas composed of networks of small specialisedindigenous firms, also refers to the local production sys-tems to explain the success of this form of industrialorganisation. Another main concept put forward by theFrench school of regional science is the role of territory ininnovation dynamics. In order to appreciate the interac-tion between technological and territorial dynamics, Kirat(1993) proposes an approach in terms of territorialisedinnovation system (TIS). According to this, technologicalinnovation is a process based upon relations of proximi-ty. Bouabdallah, Kirat and Sierra (1998) define a TIS as acollective learning area where new knowledge emerges byinteractions. This supposes it has a double capacity of res-olution of problems and institutional learning. They referto a generic notion of proximity to understand the territo-rial anchoring of innovation processes. In fact, technolog-ical dynamics is not necessarily territorialised. It dependson the shapes of organisation of actors as well as thetypes of relations among them. A relation is said to be ter-ritorialised if, beside the geographic proximity, other prox-imity relations can be identified: institutional, technologi-cal, organisational, functional or temporal.
Establishing the link between both the regional and terri-torialised innovation systems and the national innovationsystem, Arcangeli (1993) defines a NIS as the «network ofnetworks» which is supporting the common needsexpressed by regional innovative environments (RIEs). Itsupplies the organisational and communications infra-structure for an efficient and connected system of RIEs.The RIE is the context created by local synergies betweenthe networks of cooperation, information exchange,labour mobility and other flows connecting institutionsinvolved at various stages of the innovation processeslocated in the regional poles of activity.
Pragmatically, regarding the Belgian RISs, they are stillstrongly under the sway of the institutional structure of theBIS [Larosse (1997a)]. On the one hand, their structure
cannot escape the historical factors that have shaped theBIS till federalisation. On the other hand, some importantcomponents of RISs are still under the control of the fed-eral state among which the fiscal policy in favour of inno-vation and the competition policy.
As a whole, innovation systems are characterised by theclose intertwinning between several sub-systems that putsthe stress on the following issues:
• institutional set-up,• education and training structure and performance,• S&T profile and base,• industrial pattern,• scope of interactions among institutions, and• degree of international integration of institutions.
In order to provide a basis for some policy recommenda-tions on how RISs, and in a same movement the BIS,could be improved to face the new technological chal-lenge these different issues will be developed in the nextsections. Despite the federalisation of the country, regionsshare a similar institutional heritage. It is true that thereare marked differences across regions regarding the tech-nology policy-making. To what extent policy makers couldnot take advantage of the confluence of two cultural pat-terns within a same federal structure by stimulating ade-quate and significant actions such as interregional coop-eration agreements that make RISs highly efficient to thebenefit of the different Communities?
2.2. THE BELGIAN INNOVATION SYSTEM
Over the past 25 years, Belgium has undergone severalinstitutional reforms that have transformed the countryinto a federal structure which consists of a federal state,regions and communities. Each of these entities has itsown legislative and executive bodies. At federal level, theChamber of Representatives and the Senate represent thelegislative organs while each region and community havetheir own parliament known as the Council. The federalState and the federated entities also have their own exec-utive organs which are the governments made up of min-isters. The transition into a federal structure has beencharacterised by an increasing power of decision devolved
1 3
to these entities. In particular, the authority of regions andcommunities in the field of S&T policy, i.e. design, imple-mentation and co-ordination of these policies, has beenconsiderably extended.
The ministries for Education falling within the compe-tence of the Flemish and French Communities, the activ-ities in the field of S&T policy assigned to these entitiesmainly concern the education and training system as wellas the scientific research. The «regionalisation» of thecountry having been largely raised by economic con-cerns, regions handle technology policies among whichgrants to enterprises, incentives to investment, economicexpansion and public industrial initiatives. The federalgovernment maintains competencies to manage andtake initiatives for scientific research in support of feder-al policies and international agreements or those topicsthat are beyond the concerns of a single region and com-munity. In a nutshell, the Belgian S&T policy is now main-ly outlined at both the regional and community levels.Both education and fundamental research policies areunder the responsibility of Communities while appliedresearch policy is granted to Regions.
Though a detailed analysis of the main components of theBelgian innovation system is beyond the scope of the pre-sent study4, it is worth examining some elements thatcharacterise or differentiate the institutional innovationprofiles of the federal and federated authorities. Such anexercise allows one to get a better appreciation as to whatextent the Belgian National Innovation System is still real-ly national or if it is becoming increasingly and irreversiblyregional. It follows from Figure 2.1 that both the federaland federated governments have their own administrativeorgans for the design, financing and co-ordination of S&Tactivities. These authorities allocate a significant part oftheir financial resources to promoting and supporting S&Tactivities. Yet, it should be noted that the contribution ofBelgium in terms of R&D subsidisation is relatively weak-er compared to other highly industrialised countries.Indeed, in 1995 the public R&D funding with respect toGDP is 1% in France, 0.9% in Germany, United Kingdomand The Netherlands against 0.5% in Belgium5.
The breakdown of public budget allocations to S&T activ-ities in 1996 indicates that the lion’s share of the federalcontribution goes to the financing of research and tech-nological organisations (RTOs) (among which the Centrefor Nuclear Energy and the Sectoral Collective ResearchCentres) as well as international actions, e.g. the partici-pation to the European Space Agency or the EuropeanOrganisation for Nuclear Research. The funding of theeducation system and the research carried out by univer-sities represent 58.5% of the Flemish Community alloca-tion. This share is markedly higher (70.7%) in the French-speaking side of the country which appears consequentlymore oriented towards education and fundamentalresearch. As far as the measures implemented to supportindustrial R&D, the total budgets of both the Flemish andFrench Communities and Walloon region are almost thesame, about 4 billions BEF. Hence, the intensity of publicR&D for the support of industrial production is higher inBrussels and in the Southern part of the country.Conversely, more public R&D funds are assigned to RTOsin Flanders. This can be explained by the presence oflarge research centres such as VIB, IMEC and VITO.
In terms of the set of S&T policy instruments implement-ed by the different authorities in order to support the busi-ness sector R&D, some complementarities can beobserved between the federal and the federated govern-ments. One major difference concerns the fiscal policy infavour of innovation which falls within the federal respon-sibility. The regions are mostly competent for direct sup-port of firms’ R&D activities through grants and subsidiesand/or refundable loans. The bottom part of Figure 2.1gives the evolution from 1989 to 1996 of the relative S&Tbudget contribution of the different authorities to the totalof Belgian expenses. The Flemish community with 38.8%appears to be the main contributor in 1996, which wasnot the case in 1989. This evolution illustrates the extentof the regionalisation of S&T competencies from the fed-eral toward the regional level.
Figure 2.1 also distinguishes between three kinds of actorsinvolved in S&T activities: the business enterprise sector,the RTOs and the Higher Education Institutions (HEIs) inparticular the universities. According to recent estimates,Belgian firms spent about 104 billion BEF in 19956 in
2 . R e g i o n a l o r N a t i o n a l I n n o v a t i o n S y s t e m s : W h a t m a t t e r s ?
FEDERAL STATE FLEMISH COMMUNITY BRUSSELS-CAPITAL WALLOON REGION / FRENCH-REGION SPEAKING COMMUNITY
1. INSTITUTIONAL PROFILE
GENERAL POLICY Council of Ministers Flemish Government Government of the Minister for ResearchFRAMEWORK Minister for Science Minister-president Brussels-Capital Region and Technological
Policy Minister for Scientific DevelopmentResearch Minister for Higher
Education andScientific Research
S&T POLICY, FORMULATION, OSTC ASI RIS DGTREFINANCING, CO-ORDINATION IWT DGNOERS
S&T PUBLIC BUDGET 18.2 Gbef 20.7 Gbef 0.4 Gbef 14 GbefALLOCATION (1996) • Education: 0.7 • Education: 9.5 • Education: - • Education: 8.1
• Universities: 0.5 • Universities: 2.6 • Universities: - • Universities: 1.8• RTO’s: 4.2 • RTO’s: 3.3 • RTO’s: 0 • RTO’s: 0.6• R&D support: 3 • R&D support: 4.4 • R&D support: 0.4 • R&D support: 3.5• Intern. Actions: 9.2 • Intern. Actions: 0.1 • Intern. Actions: 0 • Intern. Actions: 0• Other R&D credits: 0.7 • Other R&D credits: 0.9 • Other R&D credits: 0 • Other R&D credits: 0.3
R&D PERFORMERS• Corporate R&D Flemish firms Brussels firms Walloon firms
R&D exp. : 66.1 Gbef R&D exp. : 13.5 Gbef R&D exp. : 24.8 GbefR&D int. : 1.6% R&D int. : 1.3% R&D int. : 1.3%Agfa-Gevaert Solvay Smithkline Beecham
Janssen Pharmaceutica Fina ResearchAlcatel-Bell Shell Research
UCB• RTOs R&D centres R&D centres R&D centres
IRE : 37 VITO :645 ISSEP : 337CEN : 871 IMEC :981 CSRC : 140IBN : 26 VIB :1120
CSRC : 271 CSRC : 125• HEIs Dutch-speaking universities French-speaking universities
Flanders Brussels Brussels Walloonia# of students : 54.520 8.623 18.789 43.631
2. S&T POLICIES IN FAVOUR OF CORPORATE R&D
FINANCIAL INCENTIVES • Tax exemption • Grant/subsidies • Grant/subsidies • Grant/subsidies• Capital allowances • Refundable loans • Refundable loans • Refundable loans
MISSION ORIENTED • on themes and issues • on themes and issuesCONTRACTS & PROCUREMENTS of national/international of national/international
interest interestS&T INFRASTRUCTURE • Industrial research • Industrial research • Industrial research • Industrial research
centres centres centres centres• Assistance • Assistance • Assistance
3. EVOLUTION OF PUBLIC BUDGET ALLOCATIONS TO S&T ACTIVITIES
1989 - 39.0 Gbef 38.6% 32.8% 1.1% 27.5%1996 - 53.3 Gbef 34.2% 38.8% 0.7% 26.3%
Figure 2.1.Institutional profile, R&D performers and public budget allocation to S&T activities
1 4
Notes : OSTC = Office for Scientific, Technical and Cultural Affairs (SSTC-DWTC); ASI = Administration for Science and Innovation (AWI); RIS = Research and Innovation Service (SRI-DOI);DGTRE = Directorate-General for Technologies Research and Energy (DGTRE); DGNOERS = Directorate-General for Non-obligatory Education and Scientific Research (DGENORS). The
Councils and Governments of the Flemish Region and Community have merged, which is not the case for the other federated entities. Data source: CFS/STAT, 1996, UEST-DULBEA calculations.
2 . R e g i o n a l o r N a t i o n a l I n n o v a t i o n S y s t e m s : W h a t m a t t e r s ?
➮ ➮ ➮ ➮
1 52 . R e g i o n a l o r N a t i o n a l I n n o v a t i o n S y s t e m s : W h a t m a t t e r s ?
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2Although historically the Belgian government deter-
mined S&T policy, in the last years, it is the Flemishgovernment which has given major inflexions to theS&T policy of the region. Regional Innovation Systemscan be viewed as a collective order based on micro-constitutional regulation conditioned by trust, reliabil-ity, exchange and cooperative interaction. It is theinstitutional capacity to attract and animate competi-tive advantage that gives regions a strong conceptualand real identity. The analysis of territorialised innova-tion system shows technological innovation is aprocess based upon relations of proximity.
R&D investments. The Flemish firms account for 63.6% ofthis total against 23.1% in Wallonia and 13.1% in theregion of Brussels-Capital.7, 8 The largest firms in terms ofR&D expenditure are Agfa-Gevaert, Janssen Pharma-ceutica and Alcatel Bell in Flanders, Smithkline Beecham,Fina Research and Shell Research in Wallonia and Solvayin Brussels. It can be observed that the R&D intensity ofthe Flemish firms with 1.6% is significantly higher than inWallonia and Brussels with 1.3%. Besides the sectoral col-lective research centres, seven important RTOs can beidentified in Belgium: the VITO, IMEC and VIB inFlanders, the ISSEP in Wallonia and the IRE, CEN andIBN at federal level. In higher education sector, the Dutch-speaking universities have 63143 registered studentsagainst 62420 in the French-speaking universities. Thesefigures include about 18000 foreign students mainlyenrolled in the French-speaking universities (about 67%).
4 See the recent studies of Larosse (1997a and 1997b) and Capron et al.(1998).
5 Source: OECD/STI (1996).6 See Capron et al. (1999).7 See Meeusen et al. (1999).8 This data must be used cautiously, given that official figures published by
Eurostat lead to a different distribution of business R&D expenses. Accordingto this source, the business R&D expenses are evaluated at 86 billion BEF andthe regional distribution is equal to 67%, 23% and 10% for Flanders, Walloniaand Brussels respectively.
1 6
The quality of human resources is a main factor of eco-nomic growth and competitiveness. Past and presentinvestments in human capital explain to a large extent thepresent and the future of a country’s skills and compe-tencies. More basically, education plays a prominent rolein the effectiveness of innovation systems. The acquisitionof basic and high level skills is a long-term process thatimplies important public investment in education andtraining infrastructure. No economic and social develop-ment can be achieved without the availability of an edu-cated and qualified working force. Stimulating innovationand technology transfer capacity as well as technology dif-fusion will only be effective if there exists a sufficient back-ground regarding absorptive capacity. An in-depth analy-sis of the components of the absorptive capacity is a sinequa non condition to design efficient policy aimed atensuring the transition towards the learning economy.
It is not an easy task to estimate the causal relationshipbetween skills and competencies of a workforce and eco-nomic development. It is however largely recognised thatthe qualification level of human resources is at the sourceof competitiveness and growth. Although it is out of ques-tion to enter here into an in-depth analysis of regionaleducation and training systems, it is of great importanceto put forward some relevant characteristics directly linkedto the innovation system: effectiveness of the early schoolsub-system in the learning of science-linked fields, thepercentage of students in higher education in the 18-24year-old population and the qualification level of the work-ing force.
The educational attainment of the young population givesa view of the ability of a country to supply a sufficientlyqualified workforce on the labour market so that, in thefuture, companies can dispose of the technological andmanagerial skills and competencies necessary to preservetheir competitiveness and growth. Consequently, theeffectiveness of the early school system is of great impor-tance for the future economic and technological develop-ment. This question is approached by the InternationalEducation Association (IEA), Third InternationalMathematics and Science Study (TIMSS, 1997a, 1997b)that gives a measure of the attainment in mathematicsand science of school children of the same age for a large
sample of countries. The achievement measure is basedupon comparable tests that lead to score the averageeight grade achievement of a country in selected disci-plines and allow one to compare its performance with theother countries.
Table 3.1 gives the indexes obtained by Belgium and itstwo main Communities compared to the European aver-age. They indicate that compared to other Europeancountries, Belgium has a good performance indicator formathematics but underscores in science. At regionallevel, data show that the students of the FlemishCommunity obtain better results than the ones of theFrench Community and there is a real mismatch withregard to the teaching of science in the FrenchCommunity. This suggests that the French Communitymight be faced with an imbalance between the supplyand demand of scientific and technological skills as wellas the capacity of the population to take full advantage ofthe knowledge-based economy in the future. The sametable also shows the results obtained for the higher edu-cation system measured as the share of students enrolledin higher education in the 18-24 year-old populationcompared to the European average. Both Communities,and consequently Belgium, record a comparatively goodperformance, the French Community having a slightadvantage over its Flemish counterpart.
If we now take a closer look at the number of students inthe higher education system, Table 3.2 shows that theshare of the 18-24 year-old population in higher educa-tion is very high. Yet, the distribution of students accord-ing to the different teaching categories differs radicallyamong Communities. Indeed, the data reported in thetable show that, compared to the French Community,
SS ee cc tt ii oo nn 33The education & training challenge
FRENCH FLEMISH
COMMUNITY COMMUNITY BELGIUM
Mathematics 101 108 105
Science 88 103 97
Higher Education 118 113 115
Table 3.1. Effectiveness of the Education System (EUR15 = 100)
Data source: TIMSS 1997a, 1997b, EUROSTAT.
1 7
more Flemish students choose technical training whilemore French-speaking students prefer the teaching train-ing. So, the Flemish Community has a more balanced dis-tribution of students among the three main categories ofinstitutions that form the education and training system9.
The number of university students is higher in the FrenchCommunity than in the Dutch-speaking universities in rel-ative terms. It is worth highlighting that, in addition,around 6% of students enrolled in French-speaking uni-versities live in the Flemish region (mainly French-speak-ing people located in the Brussels suburban areas).
If we now turn to the evaluation of skills of the economi-cally-active population as measured by the distribution ofthe working force according to the ISCED levels10, Table3.3 shows that the Belgian distribution of the active popu-lation differs significantly from the European average11.The high value of the indexes for the low and high qualifi-cation levels suggests that Belgium is characterised by adual working force. Although this observation applies tothe three regions, it is in the Walloon region that the dual-ity of the working force is the most apparent. The trend inup-skilling of the workforce in both manufacturing and ser-vices calls for an effective training policy in Belgium, andespecially in Wallonia, in order to upgrade the average skilllevel of the active population. It is certainly a main chal-lenge that Belgium has to take up if the country wants tobe successful with its economic restructuring and ensure itstransition towards the knowledge-based economy.
It is a well-known fact that Europe performs weakly interms of job creation compared to the US and Japan.Within Europe, Belgium is one of the countries with the
lowest employment rate of the population. So, the relativelevel of the occupied population as a percentage of thetotal population in 1996 is equal to 36% against 40% inEurope. If we take the active population instead of theoccupied one to measure the share of the working popu-lation, the ratios are respectively equal to 41% and 45%.The data about the activity rates measured as the per-centage of the (active or occupied) population in the 18-65 year-old population that are reported in Table 3.4show that the country is faced with a double problem. Onthe one hand, with an unemployment rate equal to 9.6%in 1996, there is a need for improving the labour marketperformance. On the other hand, the low share of theworking force in the 18-65 year-old population suggeststhat the under-activity rate of population could challengethe growth process and that there is a real problem withthe effectiveness in the allocation of human resources.This last observation is mainly explained by the upgradingof the school obligatory period (till 18 year old) as well asby the choice of the Belgian government to resort to a pre-retirement system to partly solve the high increase inunemployment.
HIGHER EDUCATION FRENCH FLEMISH BELGIUM
(% OF 18-24 YEAR COMMUNITY COMMUNITY
OLD POPULATION)
Total 31.1 29.9 30.4
Of which: Technical Training 14.8 15.9 15.5
Teaching Training 4.0 1.3 2.1
University* 12.3 11.6 11.7
Table 3.2.Distribution of Higher Education Students (1995)
Note: * Foreign students not included and domestic students allocated according to their resi-dence place, Data source: National Statistical Office.
WALLONIA FLANDERS BRUSSELS BELGIUM
QUALIFICATION INDEX
Low 109 98 89 100
Medium 77 84 76 81
High 132 136 166 137
Table 3.3. Qualification Level of the Economically-active Population, 1994 (EUR12 = 100)
Notes: Low = ISCED 3 and below, Medium = ISCED 4, High = ISCED 5 and above.Data source : Eurostat.
1 8 3 . T h e e d u c a t i o n & t r a i n i n g c h a l l e n g e
Table 3.5 puts forward that the low-skilled working forceconcentrates two third of the unemployed in Belgium. Theimplementation of efficient training programmes is cer-tainly one of the main ways to solve the unemploymentproblem. Yet, as a main part of the unemployed have nospecific or general skill they do not generally have anenough educational background to follow programmesaimed at improving their ability to use technology-inten-sive equipment. Although the promotion of the develop-ment of low-skilled activities can be expected to solve theunemployment problem, it remains a short term policythat might lead the country to a long term growth trajec-tory moving away the trend towards the knowledge-based economy. This table also gives some additionalpieces of information about the regional scores obtained
in the higher education sector. It clearly appears that thehigh score obtained by the French Community is essen-tially a result of the higher propensity of young Brusselspeople to enrol in the university teaching.
ACTIVITY RATES
POTENTIAL REAL
Age Classes 15-24 25-34 35-44 45-54 55-64 >64 Total
Wallonia 30,6 85,7 82,2 68,6 22,7 1,4 48,9 42,6
Flanders 35,4 89,8 84,8 68,2 21,8 1,4 51,4 47,0
Brussels 24,2 80,6 81,6 75,4 30,7 2,1 49,3 46,0
Belgium 32,8 87,6 83,7 69,0 22,8 1,5 50,4 45,6
Europe 46,3 82,2 83,6 76,7 39,4 3,5 55,3 49,3
Table 3.4.Regional Activity Rates
Note: The potential activity rate is based on the active population whereas the real one refers to the occupied population.Data source: Eurostat.
WALLONIA FLANDERS BRUSSELS BELGIUM
QUALIFICATION LEVEL
OF UNEMPLOYED (%)
Low & Undetermined 66 63 66 65
Medium 27 28 21 27
High 7 9 13 8
HIGHER EDUCATION
(% OF 18-24 YEAR OLD POPULATION)
Total 31,1 29,9 - 30,4
whose : Technical Training 14,8 15,9 - -
Teaching Training 4,0 1,3 - -
University 11,5 11,6 14,5 11,7
Table 3.5.Qualification level of the Unemployed
Data source: 1991 Census and National Statistical Office.
1 93 . T h e e d u c a t i o n & t r a i n i n g c h a l l e n g e
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3The quality of human resources is a main factor of
economic growth and competitiveness. The Flemishstudents obtain better results than the ones of theFrench Community. Yet, regarding the effectiveness ofthe higher education system, both Communitiesrecord a very good performance compared to theEuropean average. Nevertheless, Flanders has a morebalanced distribution of students among the differentcategories of educational institutions. The Belgianregions are characterised by a dual working force.Within Europe, they are also characterised by lowemployment rates of the population. Improving theeffectiveness in the allocation of human resources iscertainly a main challenge to take up to ensure thetransition towards the knowledge-based economy.
9 These general statistics should be completed by an analysis of regional differ-ences in vocational and continuous training. A main challenge in industrialisedcountries is to develop an efficient system for training skilled workers as well asfor supplying some minimal training to unqualified workers. This highly impor-tant issue for innovation systems should be deepened in further studies.
10 ISCED (International Standard Classification of Educational Diplomas) is usedto compare the levels of education and qualification. ISCED 1, 2 and 3 refersto low school and below education levels, ISCED 4 to high school educationlevel and ISCED 5 and above to post-school education levels.
11 For example, in Germany, the distribution of the active population (110, high;144 medium; 42, low) is more balanced among the three categories of work-ers. Consequently, Belgium has a higher proportion of unqualified workingforce.
2 0
A clear view of main regional R&D indicators is an essen-tial component in the analysis of RISs. If a national com-parison of Belgian regions can give some useful pieces ofinformation about their relative positioning, a benchmark-ing approach calls for an extension of the scope of theanalysis. With this in mind, a clustering analysis ofEuropean regions is developed as a first step in this direc-tion.
4.1. CHARACTERISTICS OF THE REGIONAL R&D
SYSTEMS
Given that Belgium is a country characterised by strongregional and cultural identities, any analysis of its innova-tion system cannot escape to the issue of the regionaldesign that sustains the Belgian innovation performance.More than in other countries, geography does matter inBelgium and a question is to know if, besides the econom-ic gap, there is really a deep technology gap amongregions.
In its analysis of the interaction between economic andtechnology development, the European Commission(1997) made use of a cluster approach to positionEuropean regions. By analogy with the Boston ConsultingGroup’s product matrix, regions were classified into fourgroups: the sleeping birds that refer to the less performingregions, the question mark that clusters low R&D-intensiveregions, the cash cows that contain regions catalogued asthe industrial core of Europe and, finally, the stars pinpoint-ed as the technology leaders. The three Belgian regions areclassified in the third group whose main characteristics aretheir industrial specialisation, a very low economic growth,a medium to high economic activity and a medium unem-ployment rate. A main observation is that these regionscould gain much from specialising in a small number oftechnological domains. To what extent can we agree withthe main conclusion of this analysis that the innovation sys-tems of the three regions are relatively similar? If it is right,regions should not matter, or at the most only marginally, inthe analysis of the BIS.
It is commonly acknowledged that there is an economicgap among Belgian regions. A further look at the region-al technological profiles could help to indicate if there is a
technology gap among regions, or if a technology gap isforming as a consequence of the economic gap, or ifalternatively the regions are increasingly followingautonomous technological trajectories. In order to answerthis question, the historical roots of the present Belgianeconomic prosperity must be kept in mind because theyexplain a major part of the regional specialisation pattern.
A global view of both economic and technological perfor-mances of regions is given in Table 4.1. Economic indica-tors like gross domestic product (GDP) per capita andlabour productivity are of primary importance becausethey are an ultimate measure of the absorptive, transferand creative capacity of a region or country. The first indi-cator shows that although Flanders and Brussels havebeen able to efficiently exploit their economic advantages,the economic base of the Walloon region has been large-ly affected by the decline of industrial activities that wereat the source of its economic prosperity and leadership inthe nineteenth and the first half of the twentieth centuries.Yet, the second economic indicator balances the diagno-sis about the economic gap between Flanders andWallonia that is not completed by a deep productivity gap.A large part of the difference in productivity is explainedby the high economic return of harbour activities inFlanders. The high productivity index of Wallonia givesevidence that, despite the weakening of its economicbase, the region has kept its competitiveness and that itsmain problem is to ensure a renewal of its economicstructure. Regarding Brussels, we note that, although theregion is in a position to capture a significant part of theBelgian growth thanks to its central position, its labourproductivity is not very high compared to the two otherregions.
Both the productivity and higher education R&D indexesobtained for Wallonia indicate that the region has main-tained a satisfying level in some basic components of itsabsorptive capacity. Yet, both its transfer and creativecapacities are not at a sufficient level to ensure the eco-nomic recovery. A main drawback of the Belgian NIS as awhole is the relative absence of strong government infra-structure. If this observation can be explained by thechoice of the government to promote the creation of col-lective research centres in the sixties, their activities are to
SS ee cc tt ii oo nn 44Regional R&D intensities and technological bases
2 1
a large extent limited to the development or the preserva-tion of existing industrial activities and not orientedtowards high-tech sectors. Futhermore, even if we takethis aspect into account, the government R&D infrastruc-ture can be considered as under-developed compared tothe highly performing government R&D infrastructurethat exists, for example, in France and Germany.
Except for government R&D, Flanders has high techno-logical indexes, especially for the indicators representativeof the innovativeness degree. Yet, compared to the richestEuropean regions, the higher education R&D is not ashigh as could be expected12. Although the per capita totalR&D index is slightly above the European average, theintensity index reveals insufficient support to the highereducation R&D. The recent emphasis of the Flemish gov-ernment’s support to the development of inter-universityresearch centres could partly close the gap.
The indicators regarding the business R&D lead one toconclude that the Flemish industrial R&D system is highlyperforming. Not only are its industrial R&D indexes high13
but the indexes relative to the number of patent applica-tions and the R&D productivity are largely above theEuropean average14,15. Mainly thanks to its central posi-tion, the Brussels region also exhibits good indexes aboutthe business R&D. Yet, the output indexes are globallyvery weak, what can be explained by the high communt-ing rate of the active population. Indeed, lots ofresearchers working in the Brussels region live in theFlemish and Walloon peripheral districts. The indexesobtained for the Walloon region are not very favourable.This low performance is not mainly a consequence of thelower propensity to invest in R&D of Walloon enterprisesbut to a large extent of its unsufficient industrial base. Yet,as can be observed, both the productivity and patentindexes give evidence of a lower inventiveness degree ofthe Walloon R&D, a phenomenon that might be explained
WALLONIA FLANDERS BRUSSELS BELGIUM
GDP per Capita 89 115 169 112
Labour Productivity 119 135 105 125
R&D Intensity
Business R&D 81 102 99 96
Government R&D 10 16 50 19
Higher Education R&D 109 96 180 111
Total R&D 75 87 107 87
R&D per Capita
Business R&D 77 124 180 114
Government R&D 9 19 90 23
Higher Education R&D 103 115 324 131
Total R&D 72 106 196 103
R&D per Active
Business R&D 100 143 108 125
Total R&D 92 120 116 112
Patent Applications
per capita 61 123 114 102
per active 78 141 68 111
R&D Productivity
Business R&D 84 105 67 95
Total R&D 91 124 62 105
Table 4.1.R&D Investment Indexes – 1994/95 – EUR15 = 100
Notes: Brussels industrial R&D expenditures have been corrected upwards (see footnotes 7 & 8). The R&D productivity as measured by the ratio ofpatents on R&D expenditures. Patents are allocated to the resident place of inventors.
Data source: EUROSTAT, UEST-DULBEA calculations.
2 2
by the industrial specialisation pattern as well as theresearch orientation of enterprises.
While regions display very varied performances in theirR&D activities, it cannot be concluded that there exists asignificant technological gap as important as the eco-nomic one, as far as we consider the R&D intensity.Although it cannot be denied that the Flemish regioninvests more in R&D and exhibits better output indicatorsthan the Walloon region, historical factors must be kept inmind when making any comparisons between regions.Thanks to its more recent industrial structure and geo-graphic advantages, it is indisputably easier for theFlemish region to take up the challenge of the presentchange of technological regime than the Walloon region,which must simultaneously manage its industrial revolu-tion heritage and ensure the transition to the knowledge-based economy. Yet, it is true that efforts should be devot-ed in the Walloon region to boosting the R&D intensity.On its part, Flanders is on the way to being one of themost innovative European regions. Although the R&Dindicators are still very high in the Brussels region, the fed-eralisation of the country has led to a more balanced dis-tribution of R&D expenses among the regions. So the highconcentration of industrial R&D expenses in the Brusselsregion has substantially decreased over time.
4.2. THE EUROPEAN REGIONAL TECHNOLOGICAL
DISPARITIES
A prominent fact of the past twenty years is the increasingimplication of regional authorities in the design andimplementation of S&T policy. Although it is mainly thecase of regionalised or federalised states such asGermany, Belgium, Austria and Spain, we can observethat regions in other countries such as France and Finlandview the promotion of new technologies as a main com-ponent of their development. This radical change is main-ly a consequence of the awareness of the central role ofS&T in economic growth and social development as wellas the recognition by national governments of the need toadapt S&T policy to local and regional environments. Soscientific and technological development has nowbecome a key element of regional planning and policy:regions are increasingly considering themselves as strate-gic competitors and are so adopting autonomous and
competitive behaviours towards other regions and nation-al authorities.
At the supranational level, the European Union also con-tributes to this tendency with the launch of projects suchas Regional Innovation Strategies, Regional Innovationinfrastructures and Technology transfer Strategies andInfrastructure and Regional Technology Plans. Further-more, S&T measures aimed at promoting regional tech-nological potentials absorb a substantial part of structuralfunds devoted to regional development. In Objective 1regions, those where the development is lagging behind,the share of R&D-related Community expenditure repre-sents 5.4% of the total budget for this group of regions forthe period 1994-1999. In Objective 2 regions, which areseriously affected by industrial decline, the share is equalto 16%16.
Regarding Belgium, a Flemish project was selected within1995 in the framework of the innovative actions of theStructural Funds. The technological plan entitled «StrategicPlan Innovation: New Opportunities For Firms» covers apart of the province of Limburg. Its main objective is tounderstand the real obstacles for SMEs to innovate,improve the interaction between SMEs and the S&T com-munity, develop pilot demand-oriented projects and to pro-pose new actions based on a long term view on innovation.In 1998, a Walloon project called «Prométhée» was alsoselected. The objective of the project is to improve theknowledge of the Walloon innovation potential, stimulatepartnerships and synergies by the implementation of clus-ters in the fields of strategic competencies and to organisea supply network of competencies adapted to the needs ofenterprises.
The Community support of the Belgian regional develop-ment programmes is substantial and amounts to 1.4 bil-lion Euros. Half this amount is allocated to the province ofHainaut as an Objective 1 region. The share related toR&D and innovation activities represents 5.7% of theCommunity grant. In Objective 2 regions, that partly coverthe districts of Liège, Turnhout and Arlon and the provinceof Limburg, the Community intervention is equal to 0.27billion of Euros17 of which 15% are allocated to R&D-relat-ed activities. Consequently, the Community support to
4 . R e g i o n a l R & D i n t e n s i t i e s a n d t e c h n o l o g i c a l b a s e s
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R&D actions in the framework of local and regional devel-opment strategies is significant and so is also its influenceon regional R&D policies.
However, what is the extent of the regional technologicalgap at a European level and what is the distribution ofregions with regards their technological potential? As afirst step, a measure of the technological gap is proposedin order to give an overview of the present technologicalchallenge that the European policy must face.18 Secondly,a typology of European regions based on technologicalindicators is developed. The objective of the clusteringapproach is to position the Belgian regions within theEuropean regional landscape.
The extent of European regional disparities can be appreci-ated by measuring the concentration of R&D personnel inregions by means of Lorenz curves. Indeed, they give anillustration of the distribution of selected variables in com-parison to the distribution of regional population. So thepopulation is taken as a reference to evaluate the degree ofconcentration of selected R&D variables. The degree ofconcentration is indicated by a concave curve. The moreconcave the curve, the greater is the concentration of thestudied variable. Put differently, the closer the curve is to thediagonal axis, the more the considered variable is equallydistributed among regions. Consequently, if there was aperfectly equal distribution of variables, the line describingthe relationship would be straight and 45 degrees to eachof the axes.
In order to appreciate the concentration of R&D activitiesamong regions, several curves have been constructed fora total of 111 regions19. The set of variables considered isthe following: patent applications; R&D personnel20 in thebusiness sector; R&D personnel in the government sector;R&D personnel in the higher education sector; and theGDP. Instead of exclusively using the total R&D personnelin order to mesure the extent of disparities, the breakdownof data among the different categories of R&D activitiesallows one to appreciate the role played by each catego-ry in the technological gap.
The concentration curve for the GDP is presented so thatthe extent of disparities of R&D personnel can also be
compared to the wealth disparity. Figure 4.1 shows thatR&D disparities are really deeper than wealth ones. Theregional distribution of business R&D personnel is moreconcentrated than the one of higher education R&D per-sonnel. With regard to government R&D personnel, thedistribution is comparable to the one obtained for busi-ness R&D. Yet, the higher concentration is observed forpatent applications. The regions concentrating 50 % ofthe European population apply for more than 85 % ofpatents. Put differently, half the regions representing 50 %of the European population are concerned with less than15 % of European patent applications. Globally, theseregions employ less than 20 % of the business and gov-ernment R&D personnel and less than 30 % of highereducation R&D personnel. Yet although a majority ofregions that underinvest in R&D are also those that havethe weaker GDP per capita, there are noticeable excep-tions. This is the case of Champagne-Ardenne, Trentino-Aldo-Adigo, Valle d’Aosta, Marche, Saarland, Salzburgand Islas Baleares for which the wealth level is higher thanthe European average but the technological positioninglargely unfavourable. While the relationship between R&Dand economic growth is very complex, it is clear that theimprovement of R&D infrastructure has to be a priorityaxis of any development policy in favour of laggingregions.
Figure 4.2 gives a general view of the most innovativeregions as well as the extent of technological disparities.The positionning of European regions illustrated in thisfigure is based on the regions’ patents and R&D per capi-ta indexes. According to whether the values taken bythese indexes are above or under the EU average, a par-tition of the figure into four classes can be operated. A fur-ther distinction can be made by taking the first bisectingline into consideration. This line which also represents theEU average can be interpreted as the productivity of R&Das measured by patents. It follows that both the Walloonand Brussels regions are under the European averageproductivity which is not the case for the Flemish region.In terms of R&D per capita, the performance of theregions leads to a different ranking, since the region ofBrussels comes before Flanders followed by Wallonia, theonly Belgian region under the EU average. This observa-tion can be explained by the higher concentration of R&D
4 . R e g i o n a l R & D i n t e n s i t i e s a n d t e c h n o l o g i c a l b a s e s
active actors in Brussels. In terms of patents per capita,Flanders and Brussels appear to have a similar scorewhich is better than the corresponding one obtained inWallonia, once again under the EU average. Several fac-tors can explain these differences. This question is exam-ined in section 6. Finally it is interesting to compare theBelgian to other European regions. A first conclusion thatemerges is that Belgian regions are relatively close toeach other than the most distant regions plotted in theFigure 4.1. In other words in terms of patents and R&Dper capita measures, the Belgian regions seems to havesomewhat similar performances compared to the regionsthat obtain the best and worst scores. As a benchmarkindicator, the Flemish region shows indexes that are closeto the ones observed for The Netherlands and the regionsof Piemonte, Lombardia, Niedersachsen or Alsace.
2 4 4 . R e g i o n a l R & D i n t e n s i t i e s a n d t e c h n o l o g i c a l b a s e s
Globally, the scope of disparities displayed by the concen-tration curves is confirmed by Figure 4.2. In order to fur-ther investigate this question, a clustering of Europeanregions has been performed on the basis of several index-es based on patenting and R&D activities and the labourproductivity defined as the ratio of GDP per active. ForR&D, a distinction is made between the government, edu-cation and business sectors. For patents and R&D, twodifferent indexes have been calculated. The first onerefers to the variable considered, i.e. patents or R&D,divided by the total population of the region. The indexbased on R&D is intended to proxy the extent to which agiven region has sufficiently invested in this kind of activi-ties in order to insure its economic development com-pared to the European average. The index based onpatents can be interpreted as the region’s creative capac-ity. The R&D mix index shows the degree of diversificationof R&D activities between the government, education and
Figure 4.1.Regional Disparities - 1993 (111 Regions)
0 10 20 30 40 50 60 70 80 90 100
0
10
20
30
40
50
60
70
80
90
100
Cum
ulat
ed V
alue
of V
aria
bles
(%)
Cumulated Value of Population (%)
Business R&D Government R&D Higher education R&D
Patent application GDP
Data source: EUROSTAT, UEST-DULBEA calculations.
2 54 . R e g i o n a l R & D i n t e n s i t i e s a n d t e c h n o l o g i c a l b a s e s
industry. The second index, constructed by dividingpatents or R&D by GDP, shows the level of technologicalintensity and allows one to appreciate the degree ofinvestment of a region given its level of wealth. All theseindexes have to be compared with the EU average equalto 100.
It follows almost immediately from Table 4.2 that five clus-ters of European regions can be identified.
1) The first contains the regions with the best technolog-ical performances, i.e. patent and R&D indexes abovethe European average. Except for East-Anglia, theseregions are also characterised by a high degree ofcompetitiveness in terms of labour productivity. Theseregions demonstrate a high level of creative, transferand absorptive capacities in terms of technologicalactivities. They also account for an important part inexplaining the high variability observed for patentapplications across European regions. Indeed, five out
of twelve regions of this cluster account for around40% of patent applications and are among the mostinnovative European regions: Baden-Württemberg,Bayern, Nordrhein-Westfalen, Wien and Ile de France.These regions are central places of Members Statesand are main beneficiaries of national R&D infrastruc-ture and dominate the European technological space.Except mainly for Germany, capital regions emerge asmain R&D centres. This is particularly evident inFrance and Austria where Ile de France and Wien con-centrate 50 and 48% of national business R&D activi-ties respectively against less than 20% of their respec-tive national population.
2) The regions in the second cluster are still characterisedby a high creative capacity compared to the Europeanaverage. For instance, Stockholm and Vorarlberg arecharacterised by a high degree of innovativeness. Yet,these regions exhibit some lower efficiency for at leastone of the R&D indexes. The Flemish region belongs
Figure 4.2.Positioning of European Regions (1994/95)
Data source: EUROSTAT, UEST-DULBEA calculations.
400
350
300
250
200
150
100
50
00
50 100 150 200 250 300 350 400
Lazio
Wallonia
SachsenPACA
Franche-ComtéPiémont
Niedersachsen South-East
Midi-Pyrénées
Berlin
Ovre NorlandRhône Alpes
Suomi
Nederlands
Vlaams gewestBruxelles
AlsaceSmaland
SteiermarkNorth-West
Norra Mellansverige
Vorarlberg
EU Average
EU Average
Nordhrein-Westphalen
SydsverigeVastsverige
Ostra Mellansverige
Wien
Ile de France
Bremen
Baden-Wurtemmberg
Stockholm
East-Anglia
Rheinland-Pfalz
Hessen
KobenhavnBayern
HamburgAarhus
OberosterreichLombardia
R&D per capita Index
Pate
nts
per
capi
ta In
dex
2 6 4 . R e g i o n a l R & D i n t e n s i t i e s a n d t e c h n o l o g i c a l b a s e s
TEC
HN
OLO
GIC
AL
INTE
NSI
TY
PATE
NTS
HIG
H C
REA
TIV
E C
APA
CIT
YLO
W C
REA
TIV
E C
APA
CIT
Y
R&
D M
IXTO
TAL
EFFI
CIE
NC
YPA
RTI
AL
EFFI
CIE
NC
YTO
TAL
EFFI
CIE
NC
YPA
RTI
AL
INEF
FIC
IEN
CY
TOTA
L IN
EFFI
CIE
NC
Y
Kob
enha
vn, I
le d
e Fr
ance
,W
ien
, Bay
ern
Brem
en, M
idi-P
yrén
ées
Rhô
ne-A
lpes
, Fin
land
Nor
drhe
in-W
estp
hale
n
Bade
n-W
uert
tem
berg
, H
ambu
rg, A
arhu
s
Berli
n
East
Ang
liaSo
uth
East
Vora
rlber
g, A
lsac
eBr
uxel
les,
Lom
bard
ia
Ovr
e N
orrla
nd, S
tock
holm
Smal
and,
Väs
tsve
rige,
Hes
sen,
Rhe
inla
nd-P
falz
Vla
ams
Gew
est,
Nor
ra M
ella
nsve
rige
Ned
erla
nds
Stei
erm
ark,
Obe
rost
erre
ich,
Ost
ra M
ella
nsve
rige,
Syds
verig
e, N
orth
Wes
t,
Nie
ders
achs
enLa
ngue
doc-
Rou
sillo
n,
Hau
te N
orm
andi
e
Bret
agne
, Auv
ergn
e,
Fyns
, Sch
lesw
ig-H
olst
ein
Fran
che-
Com
té, P
aca,
Salz
burg
, Tiro
l, Sa
arla
nd,
Rég
ion
Wal
lonn
e,
Friu
li-Ve
nezi
a-G
iulia
,
Emili
a-R
omag
na
Mad
rid, S
cotla
nd, L
azio
, M
elle
rsta
n
Piem
onte
, Eas
t Mid
land
s,
Sout
h W
est,
Sach
sen,
Thur
inge
n, S
asch
sen-
Anh
alt,
Bran
denb
urg,
TEC
HN
O-
LOG
ICA
L
BASE
HIG
H
CR
EATI
VE
CA
PAC
ITY
TOTA
L
EFFI
-
CIE
NC
Y
LOW
CO
MPE
TI-
TIV
ENES
S
LOW
CO
MPE
TI-
TIV
ENES
S
PAR
TIA
L
EFFI
-
CIE
NC
Y
PAR
TIA
L
EFFI
-
CIE
NC
Y
HIG
H
CO
MPE
TI-
TIV
ENES
S
LABO
UR
PRO
DU
C-
TIV
ITY
HIG
H
CO
MPE
TI-
TIV
ENES
S
LOW
CO
MPE
TI-
TIV
ENES
S
HIG
H
CO
MPE
TI-
TIV
ENES
S
Tabl
e 4.
2.Te
chno
logi
cal c
lust
erin
g of
Eur
opea
n re
gion
s (1
994/
95)
2 74 . R e g i o n a l R & D i n t e n s i t i e s a n d t e c h n o l o g i c a l b a s e s
Mec
klem
burg
, Krit
i,
Lisb
oa, A
core
s
Ligu
ria, L
imou
sin,
Cha
mpa
gne-
Ard
enne
,
Bass
e-N
orm
andi
e,
Poito
u-C
hare
ntes
, Cor
se,
Nor
d-Pa
s-de
-Cal
ais,
Pays
de
la L
oire
, Lor
rain
e,
Pica
rdie
, Bou
rgog
ne,
Cen
tre,
Aqu
itain
e,
Nor
djyl
land
s,
Sond
erjy
lland
s &
Rib
e,
Vejle
& V
ibor
g, Ir
elan
d,
Vest
sjae
lland
s
Um
bria
, Sic
ilia,
Bu
rgen
land
, Kär
nten
,
Sard
egna
, Tos
cana
, N
orth
ern
Irel
and,
Wal
es,
Can
aria
s, C
entr
o,W
est
Mid
land
s, N
orth
,
Nie
derö
ster
reic
hH
umbe
rsid
e, C
ampa
nia,
Mur
cia,
Bas
ilica
ta, P
uglia
,
Tren
tino-
Alto
Adi
ge,
Valle
d'A
osta
, Ven
eto,
Mar
che,
Abr
uzzi
,
Cal
abria
, Mol
ise,
Can
tabr
ia, R
ioja
,
Ast
uria
s, A
rago
n,
Com
unid
ad V
alen
cian
a,
Extr
emad
ura,
Cas
tilla
-Leo
n, C
astil
la-la
Man
cha,
Gal
icia
, Pai
s
Vasc
o, A
ndal
ucia
, Bal
eare
s,
Cat
alun
a N
avar
ra,
Ken
trik
i Mak
edon
ia,
Atti
ki, D
ytik
i Ella
da,
Ana
tolik
i Mak
edon
ia,
Thra
ki, A
igai
o, Ip
eiro
s,
Thes
salia
, Pel
opon
niso
s,
Ster
ea E
llada
, Ion
ia N
isia
,
Nor
te, A
lent
ejo,
Alg
arve
,
Mad
eira
TEC
HN
O-
LOG
ICA
L
BASE
TOTA
L
INEF
FI-
CIE
NC
Y
LOW
CO
MPE
TI-
TIV
ENES
S
HIG
H
CO
MPE
TI-
TIV
ENES
S
LOW
CR
EATI
VE
CA
PAC
ITY
Dat
a so
urce
: EU
ROST
AT, U
EST-
DU
LBEA
cal
cula
tions
.
2 8 4 . R e g i o n a l R & D i n t e n s i t i e s a n d t e c h n o l o g i c a l b a s e s
to this group. In terms of technological intensity, theperformance observed in these regions is partiallyunder the European average. Globally, these regionsshow a high potential of endogenous development.This is certainly the case for Vorarlberg and NorraMellanssverige. Some other regions, like the VlaamsGewest and Rheinland-Pfalz, exhibit a high potentialof endogenous development combined with a highlysupported institutional system. Such regions are aboutto close the gap with the regions included in the firstcluster.
3) The third cluster concentrates seven regions amongwhich the Brussels region. These regions are still char-acterised by an important creative capacity such asLombardia, which dominates the Italian innovationsystem with more than 38% of national patent appli-cations. However, these regions are less well posi-tioned for at least one of the R&D mix indexes and interms of competitiveness.
4) The fourth cluster includes regions with low indexes oftechnological intensity and technological base.Despite some potential in transfer and absorptivecapacities, the creative one is weak in these regions.The poor performance in R&D activities observed inregions such as Wallonia or Lorraine must be relatedto their insufficient industrial base in R&D intensivesectors. The unfavourable industrial heritage fromwhich these regions suffer requires important financialresources for the restructuring and the reconversion ofdeclining industries. Unfortunately, these resourcescannot be allocated to the development and supportof knowledge-based activities.
5) The last cluster is characterised by the regions with theweakest performances as regards all the indexes.Some of these regions such as Trentino-Alto Adige,Valle d'Aosta or Marche report important economicactivities compared to the European average, i.e. theGDP index is above 100. The low R&D potential char-acterising these regions contrasts with their dynamismand high degree of entrepreneurship. With a fewexceptions, the other regions present in this last clusterare the poorest EU regions in economic terms. The
low level of industrial activity puts a brake on the devel-opment of R&D.
In a nutshell, despite the increased concern of regionsregarding technological activities, the European innova-tive capacity is strongly concentrated in a number ofregions which dominate the European innovation system.The technological indicators analysed in this section sug-gests the following points:
- whatever the technological indicator being considered,regional technological disparities are largely higher thanwealth disparities;
- the high concentration of technological infrastructurewithin Members States, mainly in central places, leadsone to observe that intra-national disparities explain alarge part of the European technological disparities;
- the European technological potential, particularly withregard to business R&D, is dominated in relative as wellas in absolute terms by a few highly innovative regions.
Consequently, there is a need to promote a more bal-anced spatial distribution of technological capabilities.Lots of European regions do not benefit from the criticalmass of R&D potential allowing them to adapt and diver-sify their production structure. In these regions, the stressshould be put on the development of higher educationR&D infrastructure and the improvement of training andon-the-job training which are a necessary condition totechnological assimilation and adaptation. A secondimportant type of regions such as Wallonia are those fac-ing recovery and restructuring problems which have gen-erally a highly performing higher education R&D infra-structure but an index of business R&D per capita inferi-or to the European average. Furthermore, their R&D spe-cialisation is to a large extent concentrated in low andmedium tech industries. These regions could benefit frompolicies aimed at developing university-industry co-opera-tion and stimulating a diversification of R&D activitiesbased on regional specificities. For regions such asFlanders, a benchmark approach could be implementedin order to appreciate the speed at which the regioncatches up the most performing cluster over time.Furthermore, it would be of high interest for S&T policymakers to improve the fine-tuning of the R&D mix. An in-
2 9
depth joint analysis of the R&D mix and technological aswell as economic performances of European regionswould allow one to draw some relevant guidelines in thisrespect.
Closing the European regional technological gap is along-term job. Among priority actions, it is vital to ensurethe accessibility to information on technology and to pro-mote the receptivity to new technology. With regard topolicy choices, they have to be guided by consistency andselectivity criteria. While the former criterion refers to theintegrated character of any development strategy and thetime coherence of actions, the latter would help to avoida scattered-shot public support and to adapt the strategyto the regional specificity.
4 . R e g i o n a l R & D i n t e n s i t i e s a n d t e c h n o l o g i c a l b a s e s
SU
MM
AR
Y S
EC
TIO
N 4
4The analysis of regional technological profiles allows
one to tell if there is a technology gap among regionscomparable to the economic gap. Although Flandersinvests more in R&D and exhibits better output indica-tors than the Walloon region, historical factors mustbe kept in mind when making any comparisonbetween regions. At European level, R&D disparitiesare really deeper than wealth ones and innovativenessis strongly concentrated in some regions. In order todeepen this question a clustering of European regionsis performed on the basis of patent and R&D data.Flanders is classified in a cluster characterised by ahigh creative capacity compared to the Europeanaverage. Although the regions of this group exhibitsome lower efficiency for at least one of the R&Dindexes, they often show a high potential of endoge-nous development.
12 Up to a total of 77 European regions (EUR12 excluding Sweden, Finland andAustria), Flanders is among the top fifteen of richest regions (Capron, 1998).Regarding the higher education R&D indexes, it is only placed in the top thir-ty. For example, Alsace has a per capita index equal to 226 and an intensityindex of 176. The Baden-Wurttemberg has indexes equal to 164 and 111respectively and Scotland equal to 129 and 147. For the sake of comparison,Brussels is placed in the top five and Wallonia only in the top fifty with regardsthe GDP per capita. Regarding the higher education R&D, Brussels is in the topfive while Wallonia is close to the Flemish region.
13 Once more, refering to a set of 77 European regions, Flanders is, like Brussels,in the top twenty and the Walloon region in the top thirty.
14 Flanders comes in the top fifteen, Brussels in the top twenty and Wallonia inthe top forty.
15 It is worth underlining, as shown below in section 6, that Agfa-Gevaert con-centrates around 20% of Flemish patent applications.
16 Cf. the eight annual report on the Structural Funds in 1996 (EuropeanCommission, 1997) which devoted special attention to the Community supportto the technological development of regions.
17 The rest of the Community support is devoted to rural development and thefinancing of Community Initiatives.
18 This part is essentially based on Capron (1997).19 The sample is based on the following regional disaggregation: Austria- NUTS
II, Deuschland-NUTS I (new Länder excluded), Belgium, Sverige- NUTS II,France- NUTS II, Nederland, Italia, United-Kingdom -NUTS I, Ireland,Danmark, Spain- NUTS II, Greece - NUTS II, Finland, Portugal - NUTS II. Forsome variables, an extended sample of 131 regions is available and gives con-centration curves very similar to the ones obtained from the restricted sample.In the case of France, the regional data for higher education R&D personnelhave been obtained by applying a proportionality rule to the available partialregionalised data. The analysis is mainly based on the data available for 1993.
20 R&D personnel instead of R&D expenditures has been held because expendi-ture is to a large extent affected by price and cost effects.
3 0
SS ee cc tt ii oo nn 55Technological collaborations
The significant increase of cross-border collaborationsover the last two decades is one of the most prominentcomponents of the technological globalisation process.Technological complementarity and reduction of innova-tion time-span are two main motives often put forward toexplain the formation of international joint ventures incore technologies (Hagedoorn and Schakenraad, 1990).The techno-globalisation process makes both regionaland national technology policies more difficult but alsomore important. On the one hand, national policy instru-ments implemented by governments are less and lesseffective in ensuring that the research output financed bypublic money will be exploited within the national borders.On the other hand, governments are inclined to fosterinternational technology cooperations in order to be inte-grated into international networks and maintain theirtechnological base. In order to appreciate to what extentBelgian organisations are highly engaged in world-wideresearch networking and transfer, three types of informa-tion can be used: the pre-competitive collaborations andnear-market cooperation supported by both the Europeanand national public authorities and strategic alliancesformed on a private basis.
5.1. PRE-COMPETITIVE RESEARCH COOPERATION
Thanks to the launch of several successive FrameworkProgrammes, the European Union is become an essentialactor in technology policy. Yet the measure of the realimpact of European collaborative programmes on eco-nomic performance remains a question under scrutiny.Some argue that subsidising exclusively European collab-orations may not be an effective use of European meansand that despite the creation of an impressive array oflinks between actors, the political spillovers have beenminimal (Peterson and Sharp, 1998). The sheer complex-ity of many EU collaborative research programmes is alsoquestioned in the sense that it may have reduced theireffectiveness (Mowery, 1994). If the collaboration require-ment ensures the development of some types of network-ing, it may not necessarily be the most cost-effectivemeans of supporting technological diffusion to SMEs aswell as to regions faced with economic restructuring ordevelopment problems (Soete and Arundel, 1993). It isrecognised however that, if the European collaborative
programmes may not have improved competitiveness,they have stimulated the acquisition of new competenciesand sharpened research skills. It is with these differentpoints in mind that the role of the Belgian participation inthe Framework programmes must be assessed.
In order to appreciate the commitment degree of Belgianresearch teams to shared-cost actions financed under theFramework Programmes (FPs), six types of indexes havebeen calculated (Appendix 5.1):
- the per capita participation index which gives a mea-sure of the degree of participation independently of thetechnological base;
- the per researcher participation index which gives ameasure of the degree of participation by taking thetechnological base into account;
- the distribution index which gives a measure of thedegree of participation of the different categories ofactors (large enterprises, SMEs, research centres, high-er education and others), all other things being equal;
- the per capita collaborative links index which gives ameasure of the collaborative links independently of thetechnological base;
- the per researcher collaborative links index which givesa measure of the collaborative links by taking intoaccount the technological base;
- the mutual collaboration spatial specialisation which isa measure of the geographical orientation of mutualcollaborations of a country.
The Belgian participation in European R&D programmesis very high as can be seen in Table 5.1. Yet the per capi-ta as well as the per researcher participation indexesobtained for the other European countries show that someother small countries perform better than Belgium. Thegood position obtained by Greece, Ireland and Portugal isexplained by the fact that the FPs include some specificactions to stimulate technology cohesion. The indexobtained for Greece is in fact very impressive given itsweak technological base. The weak value of indexesobtained by large Member States results from the limitednumber of projects to which they can participate giventheir large technological base. Globally, these indexesshow that small countries are, in relative terms, the main
3 1
teams of large countries appear to have relatively lessintra-national collaborative linkages than small countries.Just behind the four largest European countries, we findBelgium whose intra-national collaboration links are lessstrong than those observed in other small countries suchas The Netherlands and the Scandinavian countries. Acomparison of the Belgian intra-national collaborativelinks indexes from the 3th FP to the 4th shows that thevalue obtained decreases from 129 to 9921. As a conse-quence, the Belgian teams do not seem to exploit theircomplementarities and specialisation patterns in order toimprove their positionning in the European networks. Ingeneral, small countries do not have enough resources tocover a large spectrum of technological fields and teamsare often specialised in technological niches in oppositionto large countries in which large-scale research centres ofmultinational companies are mainly concentrated anduniversity research teams have often the critical mass nec-essary to cover large technological fields. On the policyissue, it will be useful to deepen the analysis in order to
beneficiaries of the research networks created under theimpulse of the EU technology policy. Yet in absolute terms,the five largest Member States concentrate two thirds ofthe participations. So despite their low per capita indexes,large countries dominate the transeuropean research net-works and form the nucleus of the network (EEC, 1997).In fact, they have a strategic position within theCommunity collaboration network given their large tech-nological base.
Another main observation is that the collaborations tiedby countries are largely influenced by geographic and/orcultural proximities. Among main geographic clusters ofcollaborations that can be identified in Table 5.2, we cancite the Scandinavian countries, the German-speakingcountries and the Latin language countries. In the case ofBelgium, it appears that the weight of collaborations withthe neighbouring countries is particularly important.Another interesting observation bears on the propensity ofcountries to develop intra-national collaborations. The
THIRD FRAMEWORK PROGRAMME FOURTH FRAMEWORK PROGRAMME
Participations Participations Collaborative links
Per capita Per researcher Per capita Per researcher Per capita Per researcher
Index Index Index Index Index Index
DK 251 GR 450 FI 222 GR 444 FI 224 GR 473
IR 234 IR 219 DK 208 IR 189 IR 214 IR 201
NL 171 PO 200 IR 201 PO 171 DK 197 PO 200
BE 170 DK 183 SW 195 LU 164 SW 187 LU 172
GR 157 NL 172 NL 159 NL 160 GR 165 FI 150
UK 110 BE 166 BE 158 BE 154 LU 159 NL 148
PO 106 IT 109 GR 155 DK 151 BE 149 BE 146
FR 104 SP 102 LU 151 FI 149 NL 147 DK 143
SW 102 UK 96 UK 94 SW 131 PO 106 AU 129
DE 99 FR 88 FR 94 AU 127 AU 93 SW 125
LU 78 LU 85 DE 92 SP 123 FR 85 SP 125
FI 75 DE 69 AU 91 IT 114 UK 85 IT 106
IT 65 SW 68 PO 90 UK 82 DE 84 UK 74
SP 55 FI 50 IT 68 FR 80 SP 68 FR 73
AU 29 AU 40 SP 67 DE 64 IT 63 DE 58
Table 5.1.Participation and Collaborative Links Indexes of Countries Participating in the Shared-cost Research Actions under Framework Programmes
Note: Data about the 4th FP are limited to the period 1994-1996.Data source: Second European Report on S&T Indicators, UEST-DULBEA calculations.
3 2 5 . T e c h n o l o g i c a l c o l l a b o r a t i o n s
BE DK DE FR GR UK IT SP IR NL PO AU SW FI LU
BE 99 80 103 112 86 95 90 99 91 123 105 87 76 92 317
DK 166 93 70 95 109 75 73 113 129 99 75 138 130 107
DE 73 117 93 105 105 91 78 108 84 140 105 96 99
FR 77 89 110 113 120 88 91 85 89 89 73 118
GR 137 103 125 98 110 79 121 96 90 95 102
UK 72 97 92 131 119 98 79 104 92 52
IT 86 124 77 77 92 104 86 92 71
SP 113 97 81 138 95 79 79 48
IR 154 106 122 104 89 127 119
NL 107 85 77 103 105 73
PO 220 57 95 91 88
AU 216 77 126 111
SW 124 159 50
FI 158 153
LU 1949
Table 5.2.Mutual collaboration spatial specialisation between countries participating in the shared-cost research actions
under the Fourth Framework Programme (1994-1996)
Data source: Second European Report on S&T Indicators, UEST-DULBEA calculations.
Inversely, the one obtained for large enterprises is 22 per-cent below the European average. In fact, the combinai-son of the three indexes allows one to appreciate the realposition of the different Belgian categories of actors with-in the European networks. Indeed, the participation indexof Belgium as measured by the number of participationsper capita relative to the European average shows thatBelgian participation is 58 percent above the Europeanaverage. Consequently, although the distribution index forthe large enterprises is below the European average, andweaker compared to other types of organisations, we can-not conclude that their degree of participation is belowthe European average. Indeed, the combination of boththe participation and the distribution indexes produces theparticipation index of large enterprises in EuropeanProgrammes. In the 4th FP, their index of participation isequal to 123, largely above the European average.However, universities are the most committed in network-ing with an index equal to 210 for the same programme.
The SMEs also exhibit a noticeable index for their partici-pation to the FP, its value being equal to 169. The cate-gory of actors least committed in the FPs seems to be theresearch organisations whose index value is ‘only’ equal
appreciate to what extent this observation is due to theregionalisation of a large part of the S&T policy or if it isindependent of the federalisation process of the country.
Table 5.3 provides further information on the evolution ofBelgian participations in FPs. The Belgian participationsas well as collaborative links indexes exhibit downwardtrends. This a priori negative observation is explained bythe fact that the participations as well as the collabora-tions have become more diversified over time as a conse-quence of both the increasing participation of third coun-tries22 and the EU enlargement.
Regarding the value obtained for the distribution indexes,we mainly focus our attention on the R&D projects in the4th FP. All things being equal otherwise, the distributionindex shows to what extent the distribution of participa-tions among the different categories of actors is similar tothe one observed at the European level. With a value of33% higher than the European average, the higher edu-cation sector appears to play a prominent role in theexplanation of both the high participation and collabora-tive links indexes.
3 35 . T e c h n o l o g i c a l c o l l a b o r a t i o n s
to 104. This can be explained by historical factors, amongwhich the choice of the Belgian government to sustaincollective research centres. Yet, with the federalisation ofthe S&T policy, the Belgian institutional map is changing,a main factor being the decision of the Flemish govern-ment to promote inter-university research centres such asthe IMEC, VITO and VIB. As will be shown below, theIMEC has developed a large web of European collabora-tions.
In a nutshell, despite a slight reduction of both the partic-ipation and collaborative links indexes from the 2nd FP tothe 4th, the integration of the different categories oforganisations to the European R&D networks remainsvery high. The high value of both the collaborative linksand participation indexes gives evidence of the activeBelgian role in European networking. It appears that theBelgian S&T system is well integrated into the EuropeanS&T network. Its position could certainly be improvedgiven that its score remains relatively inferior to the oneobserved in some other highly industrialised countries. Aquestion remains with respect to the extent that this phe-nomenon at the pre-competitive level is translated to anequally favourable position in near-market research andstrategic alliances.
At the regional level, the French-speaking universities (53% of Belgian university participations) appear to be moreintegrated into the European networks than their Flemish
counterparts (47%). The Flemish firms and research cen-tres have a higher propensity to collaborate at theEuropean level than their Walloon counterparts.
As can be seen in Table 5.4, the six main universities con-centrate 40% of Belgian participations in CORDIS pro-jects, equally distributed among Dutch- and French-speaking universities. Other main actors are the IMEC, theUniversity Centrum of Antwerp, the Centre of NuclearEnergy and the Centre of Metallurgy Research. So tenactors intervene in 50% of Belgian collaborations. Thestructure of participations differs significantly betweenregions. Compared to the two other regions, Wallonia ischaracterised by a largely higher participation of HEI’sand a weaker implication of the industrial sector. InFlanders, RTOs participate actively in pre-competitiveresearch, which can be partially viewed as a consequenceof the Flemish S&T policy.
The distribution of Belgian collaborative links with theother EU countries reported in Table 5.5 does not empha-sise major differences between regions. Brussels andWallonia exhibit a higher propensity to collaborate withFrench and Italian teams with 25.5% and 27.8% of col-laborations respectively against 21.3% for Flanders. On itsown, Flanders is relatively more linked to German andDutch teams with 25% of collaborations against 20.2%and 19.9% for Brussels and Wallonia respectively.Futhermore, Flemish teams play a more central role in
FINANCING PARTICIPATION
PROGRAMMES SECOND THIRD FOURTH SECOND THIRD FOURTH
% Index % Index % Index % Index % Index % Index
Collaborative links - - - - - - - - 5.0 174 4.3 149
Participation - - - - - - 5.5 193 4.5 170 4.3 158
Distribution:
- Large Enterprises 20.1 49 20.3 59 16.9 63 13.0 59 13.7 64 15.0 78
- SMEs 16.4 88 17.6 107 14.9 93 18.0 99 16.9 117 18.5 107
- Research Centres 28.4 137 20.2 86 17.9 75 24.7 84 22.6 76 16.5 66
- Higher Education 34.5 183 35.3 157 41.3 151 42.6 146 41.5 132 38.9 133
- Other 0.7 117 6.6 194 9.0 153 1.6 133 5.3 183 12.1 122
Table 5.3.Belgian Participation to European Programmes
Note: The indexes reported are the per capita ones.Data source: First & Second European Reports on S&T Indicators, UEST-DULBEA calculations.
3 4 5 . T e c h n o l o g i c a l c o l l a b o r a t i o n s
intra-national networking than their Walloon and Brusselscounterparts. As the intra-national research networks canbe split into intra-regional and inter-regional ones, furtherstudies should highlight to what extent the intra-nationalnetwork is mainly structured upon an intra-regional orinter-regional basis. About this point, the Meeusen andDumont (1998) study gives some clues that at industry
level, networks are mainly structured upon an intra-regional rather than inter-regional basis.
The Community intervention system in S&T is drawn upona selection of scientific and technological priorities to befinanced. The distribution of participations among tech-nological fields covered by Community RTD actions
BRUSSELS 1808 26.9 3.6 46.6 39.8 16.4 23.1 3.7 17.0
Université Libre de Bruxelles 410 22.7 3.5 44.9 X
Vrije Universiteit Brussel 216 11.9 3.8 44.9 X
European commission 126 7.0 1.4 92.9 X
LEUVEN 1066 15.9 3.4 38.2 62.0 22.3 9.9 5.7
Katholieke Universiteit Leuven 651 61.1 3.6 34.9 X
Interuniversity Microelectronics Centre (IMEC) 195 18.3 3.5 34.4 X
GHENT 808 12.0 3.8 35.7 66.7 11.8 18.9 0.4 2.2
Rijksuniversiteit Gent 506 62.6 3.7 35.4 X
Alcatel Mietec 53 6.6 4.5 24.5 X
Plant Genetics Systems 25 3.1 2.4 32.0 X
ANTWERP 433 6.4 4.1 33.7 40.2 17.8 35.1 1.8 5.1
Universitaire Instelling Antwerpen 116 26.8 3.7 29.3 X
Alcatel Bell Telephone 69 15.9 4.6 24.6 X
Instituut voor Tropische Geneeskunde
Prins Leopold 66 15.2 1.8 57.7 X
Universitair Centrum Antwerpen 27 6.2 6.7 25.9 X
Universiteit Antwerpen RUCA 18 4.2 2.4 44.4 X
TURNHOUT 306 4.6 3.7 41.8 83.0 10.8 6.2
Studiecentrum voor Kernenergie CEN/SCK 170 55.6 2.8 53.5 X
VITO - Vlaamse Instelling voor
Technologisch Onderzoek 78 25.5 5.4 25.6 X
HALLE-VILVOORDE 141 2.1 3.8 40.4 17.0 35.5 43.3 0.7 3.5
Institut Von Karman de
Dynamique des Fluides 26 18.4 3.9 34.6 X
Laborelec – Laboratoire Belge
de L'Industrie S.C.R.L. 14 9.9 6.4 21.4 X
Université Libre de Bruxelles 12 8.5 2.6 50.0 X
Vrije Universiteit Brussel 12 8.5 2.7 66.7 X
HASSELT 83 1.2 4.6 32.5 28.9 12.0 43.4 15.7
Limburgs Universitaire Centrum 22 26.5 5.2 9.1 X
HMZ Belgium 7 8.4 3.7 57.1 X
KORTRIJK 58 0.9 5.8 22.4 3.4 5.2 82.8 5.2 3.4
Barco-Industries 15 25.9 8.7 20.0 X
Bekaert 7 12.1 7.3 0.0 X
Table 5.4.Cordis Participations
# OF PARTICIPATIONS %
AVERAGE # OF CONTRACTORS
% OF MAIN CONTRACTORSHEIs
RTOsFIRMS
GOVERNMENTOTHER
3 55 . T e c h n o l o g i c a l c o l l a b o r a t i o n s
allows one to appreciate in which type of activities the col-laborations developed by a region are concentrated. Inorder to position Belgium as well as its regions, the tech-nological revealed comparative advantage indexes(TRCAs) have been calculated. We can also measuretechnological revealed comparative base indexes (TRCBs)in order to appreciate if, given its size, the country has asufficient number of participations in the identified spe-cialisation fields.
The values reported in Table 5.6 show that Belgium hashigh TRCB indexes for a majority of technological fields.Its main weakness in European networks is to be found inthe energy sector and, to a lesser degree, in the environ-ment and health sectors. The Belgian position is veryfavourable in high tech sectors such as electronics,telecommunications, aerospace, information technolo-gies and biotechnologies. These observations must betempered because the participations to Community pro-grammes are largely modulated according to the struc-ture of budget appropriations. For example, 12% of
OTHER FLEMISH DISTRICTS 182 2.7 4.2 21.4 3.6 12.1 72.0 5.5 7.1
WALLONIA 1709 25.4 3.7 39.4 65.7 14.8 16.0 0.8 2.7
Université Catholique de Louvain-La-Neuve 492 28.8 3.3 37.6 X
Universite de Liège 343 20.1 4.5 30.3 X
Centre de Recherches Métallurgiques (CRM) 129 7.5 1.2 95.3 X
Facultés Universitaires
Notre-Dame de la Paix 90 5.3 3.6 30.0 X
Faculté des Sciences Agronomiques
de Gembloux 81 4.7 5.1 30.9 X
Université Mons-Hainaut 41 2.4 5.1 22.0 X
Faculté Polytechnique de Mons 34 2.0 4.1 38.2 X
Institut Scientifique de Service Public (Issep) 24 1.4 4.1 37.5 X
BRUSSELS 1808 26.9 3.6 46.6 39.8 16.4 23.1 3.7 17.0
FLANDERS 3078 45.8 3.8 35.9 46.5 24.3 23.4 0.8 5.0
WALLONIA 1709 25.4 3.7 39.4 65.7 14.8 16.0 0.8 2.7
UNKNOWN 122 1.8 7.0 0.0 1.6 13.1 42.6 7.4 34.4
TOTAL 6717 100 3.8 39.0 48.7 19.6 21.8 1.7 8.2
Table 5.4.Cordis Participations (continued)
Note: 60 participations of the UCL are allocated to the Brussels region.Data source: CORDIS database, UEST-DULBEA calculations.
BELGIUM BRUSSELS FLANDERS WALLONIA
42616 11333 20227 9850
FR 15.9 FR 16.9 DE 15.5 FR 19.9
DE 14.3 UK 13.1 FR 13.6 DE 13.4
UK 13.2 DE 13.1 UK 13.5 UK 12.7
BE 10.0 BE 8.8 BE 10.2 BE 9.2
NL 8.0 IT 8.7 NL 9.5 IT 7.9
IT 8.0 NL 7.1 IT 7.7 SP 6.5
SP 6.0 SP 6.2 SP 5.8 NL 5.9
DK 3.2 GR 3.3 DK 3.2 GR 3.2
GR 3.0 DK 3.2 SE 2.9 DK 2.9
SE 2.9 SE 3.1 PT 2.8 PT 2.8
PT 2.8 PT 2.9 GR 2.8 SE 2.6
IE 2.2 IE 2.2 IE 2.2 IE 2.4
FI 1.5 FI 1.6 FI 1.5 FI 1.3
AT 1.1 AT 1.1 AT 1.1 AT 1.0
LU 0.4 LU 0.4 LU 0.2 LU 0.5
Others 7.7 Others 8.4 Others 7.6 Others 7.6
Table 5.5.Distribution of collaborative links (in %)
Data source: CORDIS database, UEST-DULBEA calculations.
# OF PARTICIPATIONS %
AVERAGE # OF CONTRACTORS
% OF MAIN CONTRACTORSHEIs
RTOsFIRMS
GOVERNMENTOTHER
3 6 5 . T e c h n o l o g i c a l c o l l a b o r a t i o n s
Belgian participations are located in information tech-nologies, a sector that concentrates around 18% of theCommunity budget to the four FPs. In the biotechnologysector, we observe a Belgian participation of 4% while theshare of this specific programme in the total budget is 3%.
At regional level, two TRCA indexes are reported. The firstone, TRCA-BEL, has been calculated with respect to theBelgian participations whereas the second one, TRCA-EUR, is a comparison with the European average. Giventhe formulation of the TRCA-BEL index, the specialisationfields will be distributed between regions whatever theirdegree of participation to networks. As the TRCA-EURindexes take all the European participations into account,they allow one to balance regional specialisation fields. Sothe Belgian specialisation obtained by Brussels andWallonia in the energy sector at the Belgian level is not
confirmed at a European level. Electronics and informa-tion technologies appear to be two main strenghts of theFlemish S&T system at Belgian as well as at European lev-els. Brussels also obtains good scores for these fields,which it is not the case for Wallonia. The industrial andmaterials technologies come out as a strong Walloon spe-cialisation. Biotechnology appears to be a common spe-cialisation field of both Wallonia and Brussels.
Regarding the technological proximities between organi-sations, the HEI’s of the three regions are present in thesame fields and are a complement rather than a substi-tute to the industry participations (see Appendix 5.2). Theother types of organisations draw a more mixed profilewith specialisation patterns partly in the same technologi-cal fields as industry and HEIs.
Figure 5.1.Number of CORDIS participations
HEIs RTOs Large firms Government Other
# of Cordis projects
......500
3 7
At a district level, the following spatial specialisation patternscan be highlighted (see Appendix 5.3): biotechnologies,agriculture and aquaculture in Ghent; electronics and infor-mation technologies in Leuven; telecommunication inAntwerp; and nuclear energy in Turnhout. As discussedabove, the participation of the other Flemish districts is verylimited so that their specialisation patterns must be inter-preted cautiously. The high specialisation of Ghent inbiotechnology associated with the weak positioning forFlanders give evidence that the region has some potential inthis field, whose roots should be consolidated in the future.
To sum up, Figure 5.1 draws the map of Belgian partici-pations in the European network. For a total of 43 dis-tricts, 5 of them concentrate three quarter of all the par-ticipations: Brussels, Leuven, Ghent, Nivelles and Liège.At a second level, Antwerp, Turnhout and Namur come
out with a total of 15%. Given the strong implication oflarge universities, the participations in pre-competitiveresearch are highly concentrated in the university districts.
5.2. NEAR-MARKET RESEARCH COOPERATION
EUREKA’s focus on near-market research aims at com-plementing the pre-competitive Community programmes.As pointed out by Peterson and Sharp (1998 p.93),«EUREKA is a strange and amorphous initiative aboutwhich it is difficult to generalise. However, it has becomean important tool in Europe’s technology policy arsenal».It is worth recognising that there is, in fact, some rivalrybetween the EUREKA initiative and the European frame-work programmes and that some projects cover more pre-competitive research rather than near-market research.
5 . T e c h n o l o g i c a l c o l l a b o r a t i o n s
Figure 5.2.Number of EUREKA participations
Government Large firms RTOs SMEs Universities
# of Eureka projects
......18
3 8 5 . T e c h n o l o g i c a l c o l l a b o r a t i o n sTa
ble
5.6.
TRCA
Inde
x by
Tec
hnol
ogic
al F
ield
bas
ed u
pon
CORD
IS p
artic
ipat
ions
, 198
7-19
98
FLA
ND
ERS
TRC
ABR
USS
ELS
TRC
AW
ALL
ON
IATR
CA
BELG
IUM
%TR
CA
TRC
B
BEL
EUR
BEL
EUR
BEL
EUR
BEL
EUR
Res
ourc
es o
f th
e Se
a, F
ishe
ries
105
178
Tele
com
mun
icat
ions
180
224
Res
ourc
es o
f th
e Se
a,11
920
2R
esou
rces
of
the
Sea,
417
018
8
Fish
erie
sFi
sher
ies
Mea
sure
men
t M
etho
ds11
616
6St
anda
rds
109
156
Agr
icul
ture
134
171
Stan
dard
s4
143
158
Elec
tron
ics,
Mic
roel
ectr
onic
s12
115
4In
form
atio
n Pr
oces
sing
,12
815
4In
dust
rial M
anuf
actu
re14
413
3M
easu
rem
ent
Met
hods
314
315
8
Info
rmat
ion
Syst
ems
Aer
ospa
ce T
echn
olog
y12
214
8Sa
fety
143
144
Mat
eria
ls T
echn
olog
y14
412
3A
gric
ultu
re6
128
142
Stan
dard
s10
314
7El
ectr
onic
s, M
icro
elec
tron
ics
109
139
Aer
ospa
ce T
echn
olog
y96
116
Elec
tron
ics,
Mic
roel
ectr
onic
s8
127
141
Rad
iatio
n Pr
otec
tion
127
134
Biot
echn
olog
y12
813
7En
viro
nmen
tal
135
115
Tele
com
mun
icat
ions
412
413
7
Prot
ectio
n
Agr
icul
ture
100
128
Res
ourc
es o
f th
e Se
a,72
122
Biot
echn
olog
y10
711
4A
eros
pace
Tec
hnol
ogy
812
213
4
Fish
erie
s
Info
rmat
ion
Proc
essi
ng10
312
4M
easu
rem
ent
Met
hods
7711
1Sa
fety
107
108
Info
rmat
ion
Proc
essi
ng12
121
133
Tele
com
mun
icat
ions
8210
1En
viro
nmen
tal P
rote
ctio
n12
910
9M
easu
rem
ent
Met
hods
6086
Biot
echn
olog
y4
107
118
Indu
stria
l Man
ufac
ture
102
94M
edic
ine,
Hea
lth13
098
Stan
dard
s57
82R
adia
tion
Prot
ectio
n2
106
117
Biot
echn
olog
y86
92A
gric
ultu
re71
92R
adia
tion
Prot
ectio
n72
76Sa
fety
610
111
2
Mat
eria
ls T
echn
olog
y98
84R
adia
tion
Prot
ectio
n82
86El
ectr
onic
s,54
69In
dust
rial M
anuf
actu
re10
9310
2
Mic
roel
ectr
onic
s
Safe
ty80
80A
eros
pace
Tec
hnol
ogy
6376
Info
rmat
ion
5668
Mat
eria
ls T
echn
olog
y11
8594
Proc
essi
ng
Med
icin
e, H
ealth
103
78R
enew
able
Sou
rces
of
Ener
gy11
866
Foss
il Fu
els
117
64En
viro
nmen
tal P
rote
ctio
n6
8594
Envi
ronm
enta
l Pro
tect
ion
7261
Foss
il Fu
els
118
65R
enew
able
Sou
rces
116
64M
edic
ine,
Hea
lth4
7684
of E
nerg
y
Foss
il Fu
els
8748
Mat
eria
ls T
echn
olog
y63
54M
edic
ine,
Hea
lth71
54R
enew
able
Sou
rces
556
61
of E
nerg
y
Ren
ewab
le S
ourc
es o
f En
ergy
8547
Indu
stria
l Man
ufac
ture
5853
Tele
com
mun
icat
ions
4252
Foss
il Fu
els
355
61
Coo
rdin
atio
n, C
oope
ratio
n95
120
Coo
rdin
atio
n,
109
138
Coo
rdin
atio
n,10
513
3C
oord
inat
ion,
126
141
Coo
pera
tion
Coo
pera
tion
Coo
pera
tion
Educ
atio
n, T
rain
ing
8797
Educ
atio
n, T
rain
ing
104
116
Educ
atio
n, T
rain
ing
123
137
Educ
atio
n, T
rain
ing
111
124
Not
es :
% =
per
cent
age
with
resp
ect t
o th
e to
tal n
umbe
r of p
artic
ipat
ions
,
, whe
re i
= te
chno
logi
cal f
ield
and
j =
regi
on, t
he s
um o
n j r
efer
s to
the
Belg
ian
(BEL
) and
the
Euro
pean
(EU
R) a
reas
resp
ectiv
ely,
, whe
re p
opj=
pop
ulat
ion
of c
ount
ry j.
Dat
a so
urce
: Co
rdis
data
base
, UES
T-D
ULB
EA c
alcu
latio
ns.
TRC
B =
[]
ijn i
j
pop
jpo
pj
[]
j∑jn i
j∑
TRC
A
=[
]ij
in ij n i
j∑
[]
i,jn i
j∑j
n ij
∑
3 95 . T e c h n o l o g i c a l c o l l a b o r a t i o n s
The main findings of the evaluation realised in 1998 (EURE-KA Secretariat, 1998) confirm to a large extent the resultsof past exercises. They can be summarised as follows : - 70% of the industrial participants had created new prod-
ucts or processes by the end of their project, and a fur-ther 12% expected to do so shortly afterwards, 20%have either applied or expect to apply for licenses andpatents.
- Converting technological success to a commercial oneappears to be difficult: while 90% of all industrial par-ticipants rated their technological achievements as'excellent' or 'good', only 70% of the SMEs and 46% ofthe large industrial enterprises rated their commercialachievements equally well.
- EUREKA helped 63% of participants to access funding:15% of all participants reported lack of public financingas a major obstacle (11% for private finance). Fundingproblems become more important after the project hasfinished, where the 'development gap' between researchand commercialisation is most keenly felt.
- Broader socio-political, economic and cultural factors
are critical: factors such as 'communication problems','market changes' and 'changes in partners strategy' allrated highly (60-70%) in projects where commercialimpact was poorly rated.
- EUREKA's principal effect seems to have been to safe-guard jobs, rather than create significant numbers ofnew ones: while around a third of the companies report-ed increased employment by an average of seven jobseach, this statistic must be treated with caution, as 44%did not respond at all.
- Project impact on turnover varies enormously: whilearound half of the industrial participants (57% of theSMEs, 45% of the large companies) reported an impactof less than 1 million Euros on turnover, a very smallnumber (2% of all respondents) increased their turnoverby over 50 million Euros. 'Indirect' benefits are impor-tant: Over half of the interviewees reported benefitswhich are difficult to quantify.
Although Belgium is involved in 12.6% of the total num-ber of projects, the Belgian teams only represent 4.1% of
PROJECTS PARTICIPATIONS ORGANISATIONS BUDGET INDEXES
# % # % SMEs RTOs Total % Project Partici- Budget
& HEIs budget country pations
DE 452 14.4 921 16.1 264 288 14739 25.8 66 73 94
UK 307 9.8 619 10.8 195 148 8764 7.9 62 69 24
FR 431 13.7 981 17.2 350 248 17446 32.9 87 109 197
IT 211 6.7 405 7.1 78 131 14928 18.1 44 46 95
SP 287 9.1 448 7.8 179 106 8599 8.5 87 75 37
NL 349 11.1 524 9.2 228 91 13469 15.5 266 219 269
GR 39 1.2 54 0.9 13 24 541 5.0 44 34 5
BE 166 5.3 233 4.1 87 61 12195 5.4 194 150 130
PT 131 4.2 208 3.6 76 58 869 13.1 158 138 23
SE 230 7.3 288 5.0 110 61 9002 2.6 307 212 53
AT 164 5.2 237 4.1 86 67 8825 2.6 242 192 57
DK 159 5.1 198 3.5 73 45 5855 4.8 359 245 107
FI 147 4.7 254 4.4 85 47 10259 4.8 341 323 192
IE 34 1.1 333 5.8 13 9 4690 1.1 110 591 28
LU 11 0.4 14 0.2 4 0 800 1.6 308 215 62
Eur. Comm. 23 0.7 0 0.0 0 0 4049 17.3 - - -
EU15 1366 100 5717 100 1841 1384 18518 90.5 100 100 100
Other - - 1121 403 418 708 - - - -
Table 5.7.Eureka projects
Data source: EUREKA, UEST-DULBEA calculations.
4 0 5 . T e c h n o l o g i c a l c o l l a b o r a t i o n s
the number of participating EU organisations and, last butnot least, its financial contribution is limited to 3.6% oftotal EU funds. In order to appreciate the importance ofthe Belgian participation compared to other Europeancountries, some indexes calculated as the ratio of theBelgian participation divided by the population ratio arereported in Table 5.7. As shown in this table all theBelgian indexes are above the European average. Yet,other small countries are more present in European net-works but with a financial participation generally lesserthan the Belgian one. Only two small countries performbetter than Belgium: The Netherlands and Finland.Among large countries, France and, at a second level,Germany23 are the two most active in the European net-works. Both countries globalise more than 50% of funds.In relative terms, UK appears to be the country the leastengaged in European networks.
Given this general positioning of Belgium, what can we sayabout the Flemish participation? Figure 5.2 indicates thatthe Belgian participations are highly concentrated in a fewdistricts, mainly located in the Flemish region. It appearsimmediately that main participations are not located in dis-tricts with the higher economic activity except for Brussels.Table 5.8 presents the main results obtained for theFlemish districts as well as a comparison with other Belgianregions. Due to the lack of detailed data about financialcontributions at a desegregated level for Belgian districts,the financial distribution is not reported.
A first main observation is that the Flemish region is, to alarge extent, the main Belgian actor in the EUREKA net-work. Of a total of 244 active Belgian participations, 161are located in the Flemish region. Two Flemish districtsare strongly implicated, Ghent and Leuven, with a con-centration of about 50% of collaborations. Furthermore,they are the main contractors in a significant number ofresearch projects. On the other hand, the Walloon regiondoes not seem very implied in the EUREKA network. Sothe index for the number of participants is equal to 1.8 forthe Flemish region against .8 for Wallonia. With regard toBrussels-Capital, the index is 3. The Brussels index is, infact, largely overestimated given 20% of participations areattributed to the federal government which, at a secondlevel, selects the regional teams whose research will be
financed in the framework of OSTC activities. As no cor-rection has been operated for this bias, the Flemish indexmust be interpreted as a value by default.
If we now look at the types of organisations participatingin networks, we observe that the SMEs are more presentthan large companies. In the Ghent and Leuven districts,universities are also main actors. In relative terms, no sig-nificant regional differences can be observed among thethree regions.
With regards to the technological fields, the regional dif-ferences are very limited. Three technological fields con-centrate a large part of collaborations: information tech-nology, environment and the medical area and biotech-nology. Within the Flemish region, the research projects innew materials are mainly located in the Hasselt and Sint-Niklaas districts while Hal-Vilvoorde is more concernedwith projects linked to telecommunications.
Turning to the number of European participants in pro-jects, it appears that, once again, Ghent and Leuven aremore engaged in large-scale and/or large-team projects(mainly the JESSI project for Leuven and the EURO-TRACK project for Ghent and Antwerp). The large num-ber of participants observed for Brussels is once moreexplained by the relay role played by the OSTC in somelarge-scale projects.
If we compare the distribution of Belgian participantsamong organisations to the distribution observed at theEuropean level, it comes out that the European universi-ties and RTOs are more implied than Belgian ones andconversely for SMEs. Yet if such an observation is right inrelative terms, we must keep in mind that it is not the casein absolute terms given the high participation rate ofBelgium. A major difference between Flanders andWallonia is the very weak level of participation of enter-prises in the second region.
Finally, regarding the spatial distribution of European part-nerships, if the weight of non-Belgian partners is, as couldbe expected, relatively high, the projects to which partici-pate the Hasselt and Sint-Niklaas districts concern also,for one third of the projects, some other Flemish districts.
4 15 . T e c h n o l o g i c a l c o l l a b o r a t i o n s
Furthermore, in addition to the higher participation ofFlanders to European networks, infra-regional links arestronger in Flanders than in other regions. A questionmark is certainly the lesser propensity of both Flemish andWalloon teams to collaborate together. Except for
Brussels, intra-regional collaborations are more importantthan inter-regional ones in the framework of internationalcooperation agreements, which could give evidence of aspreading-out process of regional innovation systems.
# of participations 46 41 16 14 9 8 6 21 44 161 38 244
% of main contractors 23.9 39.0 18.8 35.7 11.1 50.0 50.0 19.0 20.5 29.2 15.8 25.4
Distribution of organisations (%)
Governm./Nat.Admin. 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 20.5 0.0 5.3 4.5
Large Firms 21.7 14.6 25.0 50.0 66.6 50.0 0.0 47.6 25.0 29.2 28.9 28.7
RTO's 13.0 14.6 6.3 7.1 0.0 0.0 0.0 14.3 6.8 10.6 10.5 9.8
SME's 37.0 26.8 56.3 28.6 33.3 50.0 100.0 38.1 25.0 38.5 39.5 36.1
University 28.3 43.9 12.5 14.3 0.0 0.0 0.0 0.0 22.7 21.7 15.8 20.9
Distribution of technological area (%)
Communications 4.3 2.4 0.0 14.3 33.3 12.5 0.0 4.8 11.4 6.2 0.0 6.1
Energy Technology 4.3 4.9 0.0 7.1 0.0 12.5 0.0 4.8 0.0 4.3 5.3 3.7
Environment 15.2 14.6 6.3 21.4 22.2 25.0 0.0 14.3 31.8 14.9 23.7 19.3
Information Technology 30.4 29.3 31.3 7.1 11.1 25.0 50.0 4.8 20.5 24.2 26.3 23.8
Medical and Biotechnology 21.7 24.4 12.5 21.4 0.0 25.0 0.0 9.5 4.5 18.0 15.8 15.2
New Materials 2.2 9.8 31.3 14.3 11.1 0.0 33.3 23.8 9.1 12.4 15.8 12.3
Robotics/Production 19.6 7.3 18.8 14.3 11.1 0.0 0.0 28.6 13.6 13.0 10.5 12.7
Automation/Lasers
Transport 2.2 7.3 6.3 0.0 11.1 0.0 16.7 9.5 9.1 6.8 2.6 7.0
Network members
# of participants 581 704 109 242 91 86 36 203 1185 2052 492 3965
% of Belgian participants 17.2 12.5 46.8 16.1 17.6 15.1 52.8 21.2 9.5 18.0 16.1 14.2
Average number of participants 12.6 17.2 6.8 17.3 10.1 10.8 6.0 9.7 26.9 12.7 12.9 16.3
European organisations (%)
Governm./nat.admin. 5.1 3.2 1.1 3.5 13.4 6.4 0.0 2.7 9.8 4.1 5.3 5.9
Large companies 15.9 40.3 29.0 17.5 41.5 55.1 13.3 45.6 21.0 30.8 12.6 25.8
Research institute 29.5 22.0 21.5 31.1 8.5 11.5 16.7 17.6 28.4 23.6 32.2 26.1
SME's 13.3 15.7 26.9 7.5 28.0 17.9 60.0 19.2 7.5 16.2 11.7 12.6
University 36.4 18.9 21.5 40.4 8.5 9.0 10.0 14.8 33.3 25.1 38.3 29.6
European participants (%)
Brussels 2.1 1.7 2.2 1.8 0.0 2.6 6.7 1.6 2.1 1.9 2.2 1.9
Flanders 7.1 5.0 35.5 8.3 8.5 2.6 36.7 10.4 3.1 8.6 2.4 5.6
Wallonia 0.9 0.5 0.0 0.9 0.0 1.3 0.0 0.0 0.9 0.6 4.4 1.1
EUR14 75.1 86.1 45.2 77.6 73.2 92.3 43.3 81.3 80.8 78.5 78.0 80.4
Other 16.8 8.4 19.4 13.2 18.3 3.8 20.0 8.2 15.3 12.3 15.2 12.9
Table 5.8.Distribution of Belgian Eureka projects
Data source: EUREKA database, UEST-DULBEA calculations.
GHENT
LEUVEN
HASSELT
ANTWERP
HALLE-VILVOORDE
KORTRIJK
SINT-NIKLAAS
OTHER FLEMISH DISTRICTS
BRUSSELS
FLANDERS
WALLONIA
BELGIUM
4 2 5 . T e c h n o l o g i c a l c o l l a b o r a t i o n s
This observation suggests that there are certainly somegrounds for actions from both the federal and regionalauthorities aimed at stimulating joint inter-regional near-market research consortia.
In a nutshell, the diagnosis about the participation ofFlemish research teams in the EUREKA projects is verypositive. The Flemish teams are very active in near-marketresearch. A main question certainly bears on the econom-ic returns of such collaborations. Such an issue should beinvestigated in further studies. When we look at theBelgian participation in EUREKA projects, both Dutch-speaking universities and Flemish enterprises are moreinvolved in collaborations than the French-speaking ones:around 70% for Dutch-speaking institutions against 30%for French-speaking ones. These observations seem toindicate that the Walloon research system is less business-oriented than the Flemish. Despite the high level of its uni-versity research, the Walloon Region faces lots of difficul-ties in valorising its R&D potential, e.g. by promoting near-market research. Consequently, we can conclude thatthere is an important spatial mismatch in the Belgian NIS.
5.3. TECHNOLOGY-BASED ALLIANCES
The globalisation of markets and the acceleration of tech-nological change are both elements that explain the pre-sent trend towards the formation of strategic partnerships.Besides the Framework Programmes and the EUREKAprojects, enterprises decide to enter into alliances on a pri-vate basis in order to expand their market, to reduce riskand to share technological competencies. A major draw-back of FPs and EUREKA data is that collaborationsreported are mainly forged on a European basis so thatthey are not relevant to analyse the extent of collabora-tions between major trading blocks. As put forward bysome studies (EEC, 1997), strategic alliances are closelyrelated to the core technology of partners. One third oftechnology-based alliances contained in the IFO database(EEC, 1997) are concentrated in the pharmaceuticals sec-tor, 15% in the electronics sectors and around 10%respectively in the computer and office machinery andinstruments sectors.
If we consider the data published in the Second EuropeanReport on S&T Indicators (EEC, 1997) on technologicalco-operation between enterprises in the world, the veryhigh degree of internationalisation of the Belgian R&Dsystem as exemplified by its participation in EuropeanR&D programmes needs to be substantially qualified. Ofa total of about 5000 international technology alliancesbetween EU members, the US and Japan, there are only57 collaborations in which Belgian enterprises are record-ed. If we consider only strategic alliances including atleast one EU partner, we observe that the Belgian share inthe total is 3.0%. As shown in Table 5.9, the participationindexes are equal to 106 for the per capita one and 103for the per researcher one respectively. The scoresobtained by some other small countries like TheNetherlands, Sweden and Ireland indicate that Belgiumcould improve its performance24. Yet, the high degree ofmultinationalisation of the country could explain this veryaverage position. Indeed, in a country whose economicstructure is largely dominated by foreign companies, theparticipation in international strategic alliances could behampered by world-wide strategies of headquarters.
DISTRIBUTION (%) PER CAPITA PER RESEARCHER
PARTICIPATION INDEX PARTICIPATION INDEX
UK 28.2 SW 193 NL 192
DE 23.2 NL 191 UK 148
FR 17.7 UK 169 SW 129
NL 8.4 DE 134 IR 117
IT 7.5 IR 125 BE 103
SW 4.9 FR 107 DE 93
BE 3.0 BE 106 FR 91
ES 2.2 FI 103 IT 77
FI 1.5 DK 86 FI 69
IR 1.3 IT 46 DK 62
DK 1.3 ES 20 ES 37
PO 0.4 PO 15 PO 29
GR 0.3 GR 9 GR 26
LU - LU 0 LU 0
Table 5.9.International technology alliances of EU countries (1984-1995)
Note: The alliances taken into account refer to the major trading blocks: the EU, US and Japan.
Data source: Second European Report on S&T Indicators, UEST-DULBEA calculations.
4 35 . T e c h n o l o g i c a l c o l l a b o r a t i o n s
These additional results show that although Belgium haslargely developed its European collaborations thanks tothe EU programmes and the EUREKA initiative, its posi-tion as a partner in strategic alliances is a question mark.In the present era of globalisation of markets, furtherefforts should be devoted by Belgian public authorities topromoting more strategic partnerships of Belgian firms atthe world level. So far its good performance in pre-com-petitive research as well as in near-market research doesnot seem to have much stimulated its participation instrategic alliances. Although we do not have the regionaldistribution of strategic alliances, it can be expected thatthe Flemish region is more committed to these alliancesthan its other Belgian partners. In the framework of abenchmarking approach, Belgium should almost doublethe number of participations to be, in relative terms, at thetop of the ranking.
SU
MM
AR
Y S
EC
TIO
N 5
5The Belgian participation in European R&D pro-
grammes is very high and largely influenced by geo-graphic and cultural proximities. Yet, the weakness ofintra-national collaboration links shows that theBelgian teams do not exploit their complementaritiesenough. The regions have high participations in amajority of technological fields. Five districts concen-trate the most participations: Brussels, Leuven, Ghent,Nivelles and Liège. Regarding EUREKA projects, theFlemish region is the main Belgian actor in the net-works. Two Flemish districts are strongly implicated,Ghent and Leuven. With regard to the technologicalfields, the regional differences are very limited. Amajor difference between Flanders and Wallonia is thevery weak level of participation of enterprises in thesecond region. Furthermore, intra-regional links arestronger in Flanders than in the other regions and alesser propensity of both Flemish and Walloon teamsto collaborate together is observed. The weakness ofinter-regional collaborations could give evidence of aspreading-out process of regional innovation systems.Regarding strategic alliances forged on a privatebasis, the very high degree of internationalisation ofthe Belgian R&D system as exemplified by its partici-pation in European R&D programmes needs to besubstantially qualified.
21 In fact, it is the country registering the highest decrease in the number of intra-national collaborations.
22 Mainly EFTA countries which are not EU Members and countries of Central andEastern Europe.
23 The population taken into account includes the new Länder.24 It is worth underlining that the Belgian position in the European average is
largely dependent on the very low scores obtained by technological laggards.When the indexes are calculated by excluding the four countries drawing thelower scores, the new indexes obtained for Belgium are respectively equal to 90for the per capita one and 97 for the researcher one.
4 4
Patents and scientific publications are among the twomain indicators available to measure the scientific andtechnological output of NISs. Patent statistics are a goodmeasure of the accumulation of national intellectual cap-ital. They represent one aspect of a country’s R&D effortand are a good approximation for technological sophisti-cation. Though this kind of technological indicator is notexempt of any criticism25, it allows one to compare thetechnological performance of different countries andregions as well as to follow the evolution over time for agiven region. Its main advantage is certainly that patentapplications and grants are broken down by technologicalclasses so that they provide internationally comparableinformation on sectoral patenting. In this study, the analy-sis of technological output is performed by using two dif-ferent data sources: the European Patent Office (1978-1997) and the US Patent Office (1978-1998). This infor-mation on patent statistics has been checked and cor-rected by re-allocating the firms’ headquarters zip codesto the regions where technological activities are per-formed.
6.1. REGIONAL EVOLUTION OF THE PATENTING
ACTIVITY
At first, it is useful to look at the regional distribution ofBelgian patents. Figure 6.1 shows the trends in patentingactivities as measured by European patent applications inthe three Belgian regions over the period 1978-1997. Itfollows that the number of patents has risen in eachregion except at the end of the period where a decline canbe observed26. Yet the increase has been much moreimportant in the Flemish region than its neighbours(growth rate from 1980-1982 to 1994-1996 of +297% inFlanders and +56% in Wallonia and Brussels-Capitalrespectively). In absolute terms, Flanders holds 68% of theaverage total number of patents applied by Belgian appli-cants over the period 1994-1996 against 18.6% inWallonia and 13.2% in Brussels. If we compare these fig-ures with the shares of private R&D expenditures acrossthe regions (for 1995, 63.6%, 23.1% and 13.1% in 1995for Flanders, Wallonia and Brussels respectively27), thereturns of technological activities in terms of patents withrespect to R&D expenses appear to be higher in Flanders.Several factors can explain these differences. The most
natural reason that comes to mind is Flanders’ higherdegree of innovativenes. Yet because patents are not aperfect indicator of technological output, it is worth usingthem in alternative ways to get a clearer view of the tech-nological performance of the regional entity being inves-tigated. For instance, the sectoral distribution of techno-logical activities in one region may be more concentratedin fields in which the propensity to patent is higher, e.g.the propensity is high in pharmaceuticals and low in aero-space or in non-manufacturing sectors. In a similar vein,process innovations lead less often to a patent than prod-uct innovations because the efficiency of patents as ameans to protect against imitation is lower in the formercase. Another important distinction is the one betweenfundamental and applied research. Patents are moreoften seen as an output of applied research while the out-comes of basic research lead in general to scientific ortechnical publications. Finally, the strategies followed byfirms to pre-empt imitation from their rivals may differ. Forinstance, a patent may be claimed for each potentialinvention, even if the probability to turn this invention intoa profitable market is low. According to a recent sympo-sium held in Brussels concerning patents, the mainBelgian patenting firms such as Agfa-Gevaert, Bekaert,Picanol or Solvay use patents to ‘hamper’ competitorsrather than to protect new discoveries against imitation28.At the other end, a firm may decide not to patent a newproduct but rather to keep it secret because of easy imi-tation or because of the high costs involved in the patentfilling procedure.
Before analysing these questions more in depth, let usnotice that the number of patents granted at the USpatent office shown in Figure 6.2 exhibits a similar patternover 1978-98 as the corresponding EPO statistics29. Thesharp increase in the number of US patents observedfrom 1993 comes about two years after that detected atEPO. This can be explained by the fact that it takes oneyear on average for a patent application to be granted bythe patent office. In 1997, Flanders has the highest sharewith about 75% against 13.3% and 11.9% for Brusselsand Wallonia respectively.
Another interesting result is that when Agfa-Gevaert, theBelgian firm with the highest number of patents, is left
SS ee cc tt ii oo nn 66Technological output
4 56 . T e c h n o l o g i c a l o u t p u t
out, the increase of patent counts during the end of theperiod is less pronounced both at EPO and USPTO. Thisobservation seems to coincide with the decision of Agfa atthat time to systematically fill in or apply for patents relat-ed to expected potential innovation (and/or parts of it) inorder to pre-empt possible competition of other firmsactive in similar technological fields. In terms of inventors,Table 6.1 gives the number of inventors for each countryof the European Union over the period 1987-1998. The7634 Belgian inventors represent 2.6% of the Europeantotal. The breakdown of total inventors into ‘inside’ inven-tors, i.e. the inventors reported in patent documentsapplied by firms from the inventor country of origin, and‘outside’ inventors, i.e. the inventors reported in patentdocuments applied by firms whose country of origin is dif-ferent than the inventors’ one, gives a view of the extentof the ‘knowledge drain’ phenomenon. By ‘knowledgedrain’, we mean the propensity of a multinational firm toappropriate national knowledge potential without system-atically and locally valorising the outcomes in economic
terms. With 38% of its inventors performing researchactivities in extra national companies or subsidiaries offoreign multinationals that do not patent in the country,Belgium appears to be among the most concerned in thatrespect. Table 6.2 lists the 12 most ‘knowledge draining’firms in terms of patent applications that employ Belgianinventors. These 12 firms represent 44.3% of the totalnumber of patents applied by this kind of firms. Except forProcter & Gamble, Exxon Chemical patents, Colgate-Palmolive and Ludwig Institute for cancer research, thecountries in which these firms are located are neighboursof Belgium.
In order to better appreciate the Flemish technologicalperformance in terms of patenting activities, it is worthexamining the most dynamic firms in this respect. Table6.3 shows the Flemish firms that have experienced thehighest growth rate of European patent applications from1991-1994 to 1995-1998. These firms account for 34.5%of total patents in Flanders. This share was 25.2% in the
0
100
200
300
400
500
'78 '79 '80 '81 '82 '83 '84 '85 '86 '87 '88 '89 '90 '91 '92 '93 '94 '95 '96 '97 '98
Figure 6.1.Number of Belgian EPO patent applications (1978-1997)
Flanders
Flanders less Agfa
Wallonia
Brussels-Capital
Data source: EPO (1998), UEST-DULBEA calculations.
4 6 6 . T e c h n o l i g i c a l o u t p u t
0
50
100
150
200
250
300
'78 '79 '80 '81 '82 '83 '84 '85 '86 '87 '88 '89 '90 '91 '92 '93 '94 '95 '96 '97 '98
Figure 6.2.Number of Belgian patents granted by the USPTO (1978-1998)
Data source: USPTO (1999), UEST-DULBEA calculations.
# OF INVENTORS
TOTAL ‘INSIDE’ ‘OUTSIDE’ %
Sweden 10947 3644 7303 66.7
Luxembourg 382 202 180 47.1
Portugal 152 92 60 39.5
Belgium 7634 4705 2929 38.4
Ireland 801 527 274 34.2
Greece 279 211 68 24.4
Austria 7288 5662 1626 22.3
United Kingdom 37421 29683 7738 20.7
Spain 3437 2747 690 20.1
Danemark 3870 3319 551 14.2
Netherlands 16459 14309 2150 13.1
Italy 23894 21200 2694 11.3
France 50476 45390 5086 10.1
Finland 5099 4654 445 8.7
Germany 124671 115428 9243 7.4
Table 6.1.Number of inventors in the European Union (EPO 1987-1998)
Note: % = Share of international inventors, i.e. inventors reported in foreign patent docu-ments with respect to total inventors. Datasource: EPO (1998), UEST-DULBEA calculations.
FIRM COUNTRY # OF PATENTS
Procter & Gamble US 415
Exxon Chemical patents US 158
Colgate-Palmolive US 107
Imperial Chemical industries GB 123
Siemens DE 160
Shell International Research NL 74
Cerestar holding NL 53
Ludwig Institute for cancer research US 38
Bayer DE 33
Framatome Connectors international FR 35
Alcatel FR 51
DSM NL 51
Table 6.2.Top 12 EPO patenting foreign firms that employ Belgian inventors
Datasource: EPO (1998), UEST-DULBEA calculations.
Flanders
Flanders less Agfa
Wallonia
Brussels-Capital
4 76 . T e c h n o l i g i c a l o u t p u t
former period. Hence, a substantial part of the increaseobserved in Flemish patenting activities is explained bythese highly dynamic firms such as Atlas Copco Airpower,Xeikon, Innogenetics or Plant Genetic Systems.
Tables A.6.1 and A.6.2 in the appendix rank the top 50firms in terms of EPO and USPTO patenting activities. Afirst observation that emerges from the figures is the highconcentration of patents in a few firms. Indeed, the 10firms with the highest number of European patents repre-sent 39.3% of the total. For the top 50 firms, this share isof 59.7%. In terms of US patents, the concentration iseven higher: 57.9% and 79.4% for the top 10 and top 50firms respectively. This higher concentration of US patentsindicates that it is mainly the largest firms with multina-tional activities that patent outside the European market.A second observation is the relative dependence ofBelgium towards foreign multinational firms which havesubsidiaries established in Belgium. This is particularly thecase for Agfa-Gevaert, Janssen Pharmaceutica, Procterand Gamble or Monsanto Europe which represent 22.3 %of total EPO patents over the period. One may wonder
whether the outcomes of research activities performed bysome of these multinational firms are effectively exploitedin Belgium or simply brought back to the foreign mothercompany. One example is Shell Research which has aresearch facility in Belgium but does not apply for anypatents. Instead, the outcomes of R&D activities carriedout by Shell Research are patented by the Dutch mothercompany and the inventors reported in these patent doc-uments are Belgian. In addition, it may happen that suchfirms close or move away to other countries with moreattractive R&D incentives, e.g. tax credits, subsidies,which would weaken the Belgian technological position.
In regional terms, the Flemish firms listed in the top 50ranking account for 66.7% of the total counts of EPOapplications in Flanders. The corresponding share ofBrussels and Wallonia is 56.6% and 43.6% respectively.Hence, in Flanders, large companies hold a higher shareof the region patenting activities. This may partly explainthe relative weaker performance of Wallonia which hasmore SMEs with lower propensities to patent on anenlarged base as is the case for the European orAmerican markets. At the district level, Table 6.4 showsthat the share of Antwerp is 26.3% of Belgium total EPOpatents. This is due to the presence of Agfa–Gevaert in
# OF PATENTS # OF PATENTS GROWTH RATE
91-94 95-98 95-98/91-94 %
Janssen Pharmaceutica 69 109 58
Raychem 11 34 209
Plant Genetic Systems 8 33 313
Michel Van De Wiele 13 24 85
Interuniversitair Micro 10 22 120
Elektronica Centrum (IMEC)
Xeikon 0 19 -
Stichting Rega 7 18 157
Firma G.B. Boucherie 4 13 225
Heraeus Electro-Nite 2 13 550
International
Atlas Copco Airpower 0 9 -
Innogenetics 1 8 700
Sidmar 0 5 -
Flanders 497 889 79
Brussels-Capital 223 173 -22
Wallonia 172 172 0
Table 6.3.Most dynamic Flemish patenting firms (USPTO)
Data source: USPTO (1999), UEST-DULBEA calculations.
REGION # OF PATENTS %
BRUSSELS 1270 16.0
FLANDERS 4832 60.8
WALLONIA 1841 23.2
BELGIUM 7943 100.0
Antwerpen 2087 26.3
Leuven 402 5.1
Turnhout 377 4.7
Kortrijk 311 3.9
Gent 282 3.5
Brugge 245 3.1
Halle-Vilvoorde 231 2.9
Ieper 203 2.6
Hasselt 116 1.5
Roeselare 106 1.3
Maaseik 102 1.3
Other Flemish districts 370 4.7
Table 6.4.Number of EPO applications by regions (1978-1997)
Data source: EPO (1998), UEST-DULBEA calculations.
4 8 6 . T e c h n o l i g i c a l o u t p u t
this district. The next four districts, Leuven, Turnhout,Kortrijk and Ghent represent 5.1%, 4.7%, 3.9% and 3.5%respectively. Hence, the share of the five most importantFlemish districts in terms of EPO applications concentrate43.5% of Belgium patents or 71.6% of Flanders total.
6.2. EXPLAINING REGIONAL DIFFERENCES IN
INNOVATION PROFILES
In relative terms, the innovativeness of Belgian districts asmeasured by EPO patent counts per capita shown inFigure 6.4 gives a similar picture than what we observe inabsolute terms, i.e. total number of patents as shown inFigure 6.3. The only exception is the district of Ieperwhose index of innovativeness is the third highest with ascore of 246. Yet in terms of GDP per capita, the positionof Ieper is below the Belgian average. So there seems tobe no direct causal link between the wealth generated in
a specific area and its degree of innovativeness. Anotherconclusion that can be drawn from these figures is thehigher balance in terms of innovativeness betweenFlanders and Wallonia than it is the case in absoluteterms.
The composition of R&D activities is another importantfactor that explain differences in patenting activities. Forinstance according to Levin et al. (1987), the availabilityof patents as a mean to protect against imitation isexpected to have a greater influence for product R&Dthan for process R&D. The higher share of product R&Dwith respect to total R&D expenditures in Flanders maythen be another determining factor for the higher numberof patents applied for in this region. Indeed, as shown inFigure 6.5, Flanders concentrates 69% of its R&D expens-es in new products against 50% in Wallonia and 60% inBrussels-Capital. The composition of R&D activities in
Figure 6.3.Number of EPO patents (1978-1997)
# patents 1978-1997 0 to 30 30 to 50 50 to 130 130 to 2,090
Data source: EPO (1998), UEST-DULBEA calculations.
# of patents 1978-1997
2,100
1,050
210
Figure 6.4.EPO patents per capita (average 1978-1997, Belgium = 100)
patents per capita 0 to 50 (26) 50 to 100 (6) 100 to 150 (8) 150 to 284 (3)
Data source: EPO (1998), UEST-DULBEA calculations.
patents per capita
250
145
20
4 96 . T e c h n o l i g i c a l o u t p u t
terms of research and development activities is anotheruseful distinction. The question here is when does thepatent application occur in the R&D sequence? In arecent study, Cincera (1997) has estimated the impact ofR&D expenditures on patenting of international manufac-turing firms. The main conclusion of this analysis is thatfirms seem to register patents at an early stage of theR&D sequence in order to benefit from strategic advan-tages over rivals or pre-empt other firms from claiming forsimilar innovations. Yet it remains true that the develop-ment of already patented innovations into, for instance,slightly improved products adapted to the local marketleads also to patenting. One example of this kind of activ-ity are the foreign firms that have subsidiaries in Belgiumlike for instance Procter & Gamble. Figure 6.6 indicatesthat in Belgium, on average, firms devote one quarter oftheir R&D expenses to research activities. This share doesnot seem to be different between Flanders and Wallonia.
Hence, the distinction between research and developmentactivities cannot be viewed as a main source for the dif-ferences in terms of the number of patents applied bythese two regions.
The breakdown of R&D activities across personnel, invest-ment and functioning expenses reported in Figure 6.7suggests that the share that goes to capital expenses(investments in R&D) is similar across regions, about 8%.The main difference to be observed is between personneland functioning expenses. Indeed the personnel share is66% in Brussels, 60% in Flanders and 55% in Wallonia.Personnel expenses cover the wages of the researcherswhile functioning expenses include the costs incurred forthe purchase of materials, supplies and equipment whichdo not form part of the investment expenditures and aimat supporting the R&D activity. Yet, it is not clear what isthe marginal productivity of these three components with
5 0 6 . T e c h n o l i g i c a l o u t p u t
Figure 6.5.Composition of R&D: process, products and other expenses
Others Process Products
Notes : number of firms that answer to the R&D components in parenthesis ; R&D share of these firms with respect of total R&D of respondents below.
Data source : IWT.
Bxl-Cap.(57 firms)
52%
Flanders(292 firms)
92%
Wallonia(108 firms)
79%
Belgium(457 firms)
84%
0%
20%
40%
60%
80%
100%
60%
69%
50% 50%
23%
27%
23%
27%
20%
11%
21%
19%
Figure 6.6.Composition of R&D: research and development expenses
Development Research
Notes : number of firms that answer to the R&D components in parenthesis ; R&D share of these firms with respect of total R&D of respondents below.
Data source : IWT.
0%
20%
40%
60%
80%
100%
Bxl-Cap.(57 firms)
54%
Flanders(283 firms)
96%
Wallonia(105 firms)
79%
Belgium(445 firms)
87%
37%
23% 26% 25%
75%74%77%63%
Figure 6.7.Composition of R&D: investments, functioning and personnel expenses
Investment Functioning Personnel
Notes : number of firms that answer to the R&D components in parenthesis ; R&D share of these firms with respect of total R&D of respondents below.
Data source : IWT.
0%
20%
40%
60%
80%
100%
Bxl-Cap.(61 firms)
59%
Flanders(296 firms)
81%
Wallonia(114 firms)
84%
Belgium(471 firms)
79%
66%60%
55%60%
32%
8%
37%
8%
31%
9%
26%
8%
Figure 6.8.Composition of R&D: intra and extra-mural R&D expenses
Extra-muros R&D Intra-muros R&D
Notes : number of firms that answer to the R&D components in parenthesis ; R&D share of these firms with respect of total R&D of respondents below.
Data source : IWT.
0%
20%
40%
60%
80%
100%
Bxl-Cap.(65 firms)
100%
Flanders(308 firms)
98%
Wallonia(119 firms)
85%
Belgium(492 firms)
95%
85%
94%
83%90%
10%17%6%15%
respect to the output of R&D, whose part of it is patented.If we assume that inventions and innovations are moredirectly linked to the activities carried out by inventorsrather than the «raw material» used in the R&D process,then this could explain why Flanders has more patents perunit of R&D.
As far as the distinction between intra- and extra-muralR&D is concerned, here also differences between theregions are observed. As can be seen in Figure 6.8,Flemish firms seem to perform more R&D within their ownwalls than is the case in the Walloon and Brussels-Capitalregions. The share of intra-mural R&D is equal to 94% in
5 16 . T e c h n o l i g i c a l o u t p u t
Flanders against 85% in Brussels and 83% in Wallonia.Extra-mural or subcontracted R&D refers to researchactivities financed by a given firm but undertaken by insti-tutions such as other firms, universities or RTOs, e.g. sec-toral research collective centres. These kinds of relation-ships and interactions aim at facilitating innovation byexploiting the complementarities of the performing insti-tutions in terms of skills, knowledge or capabilities.
6.3. REGIONAL SPECIALISATION PATTERNS
As discussed above, the propensity to patent may varyacross technological fields. In fact, the effectiveness ofpatents as a mean to protect against imitation differswidely across industries and technological fields. Forinstance, Levin et al. (1987) found that patents are high-ly effective in industries such as drugs, organic chemicalsand pesticides, but moderately effective in such techno-logical fields as electrical equipment, instruments, rubberor textile. In order to examine this question in the Belgiancase, a Technological Revealed Comparative Advantages(TRCA) Index has been computed for each region. It fol-lows from Table A.6.3 in the appendix, that the techno-logical classes for which Flanders holds a higher share inits patent distribution as compared to Belgium are: pho-tography (IPC class G03), agriculture (A01), telecommu-nications (H04), printing (B44) and weaving (D03). InWallonia, the highest TRCA indexes are observed forweapons (F41), petroleum (C10), metallurgy and iron(B22 and C21), and biochemistry (C12) and pharmaceu-ticals (C08). Finally, heat exchange (F28), informationstorage (G11), inorganic chemistry (C01) and paper-mak-ing (D21) are the technological areas where firms locatedin the Brussels region are seen to have the most importanttechnological advantages compared to the other regions.On the whole, Flanders seems to be more specialised inthe field of instruments while Brussels and Wallonia applyrelatively more patents in the field of chemistry and phar-maceuticals. It is worth noting that these latter technolog-ical classes are precisely the ones for which patenting isthe most effective.
It is important to note that similar conclusions emergewhen this analysis is performed on a European basis. Thatis, when TRCA indexes are calculated for each Belgian
region compared to the total number of patents applied inthe 15 European Union countries. Indeed, as Table 6.5indicates, the technological classes in which the regionshave the most important advantages compared to EUcountries are not different from the ones detected in thepreceeding analysis at the Belgian level. The only excep-tion is the pharmaceuticals sector in Wallonia. Table 6.5also gives the technological classes associated with thehighest growth of patents for the whole European Unionfrom 1981-1985 to 1991-1995. Over the whole periodinvestigated, Flemish patents applied in these high grow-ing classes represent 20.5% of Flanders total against15.1% in Wallonia and 29.1% in Brussels.
Yet a main drawback of the TRCA index is that any regionor country will have a technological specialisation patternwhatever its innovative potential. For example, a countrysuch as Greece with a very low level of R&D expenditureand a low number of patents will be specialised in sometechnological fields. It is, however, clear that to a largeextent the country does not have a sufficient technologi-cal base to compete with highly industrialised countries inthese technological fields. Consequently, an alternativeway is to conceive a technological revealed comparativebase index (TRCB). As the technological base of a coun-try is constrained by the size of the country, a proxy mightbe to use the population as the weighting factor. Table 6.6gives the values obtained by applying this approach.Although the TRCA indexes put forward 37 fields of spe-cialisation in Flanders, the TRCB indexes show that theFlemish technological base is limited to 20 technologicalfields. In Wallonia, the weaker technological base leads toa more restricted technological potential, limited to 13classes. Conversely, Brussels is characterised by a relative-ly larger spectrum of technological capabilities.
5 2 6 . T e c h n o l i g i c a l o u t p u t
FLANDERS WALLONIA BRUSSELS1 Ropes & non-electric cables 22.3 0.6 Weapons 8.2 3.1 Sugar or starch industry 12.5 0.62 Weaving 20.1 5.6 Ammunition 4.3 1.5 Explosives; matches 7.2 0.43 Photo-, cinema- & electrography 14.5 15.7 Metallurgy of iron 4.1 1.6 Heat exchange 6.3 1.84 Brushware 12.2 1.1 Casting & powder metallurgy 3.5 2.2 Inorganic chemistry 5.8 4.25 Print ing 4.2 4.5 Biochemistry& genetic engineering 3.4 4.8 Instrument detai ls 5.8 0.16 Earth drilling & mining 3.1 1.7 Furnaces & ovens 3.2 0.7 Electrolytic processes 5.3 2.77 Agriculture 2.5 5.2 Crushing & treatment of grain 3.1 0.6 Metallurgy of iron 5.2 2.18 Animal and vegetable oils 2.5 2.1 Petroleum, gas and coke industries 3.0 1.9 Biochemistry& genetic engineering 4.0 5.79 Saddlery & upholstery 2.4 0.1 Metallurgy & alloys 2.9 1.1 Earth drilling & mining 3.7 1.6
10 Machines for liquids, wind, spring 2.0 0.2 Life-saving 2.9 0.6 Brushware 3.4 0.311 Combustion processes 1.9 1.2 Hydraulic engineering 2.8 1.3 Layered products 3.2 1.312 Heating, ranges & ventilating 1.8 1.7 Building 2.5 3.9 Working of metals 3.0 1.913 Hydraulic engineering 1.8 0.8 Sports & games 2.4 1.6 Organic molecular compounds 2.9 12.314 Disposal of solid waste 1.7 0.1 Baking 2.1 0.4 Paper-making 2.9 1.115 Metallurgy of iron 1.5 0.6 Headwear 2.1 0.1 Sewing & embroidering 2.4 0.316 Butchering & meat treatment 1.4 0.3 Earth drilling & mining 2.1 1.2 Casting & powder metallurgy 2.1 1.517 Doors, windows, shutters & ladders 1.4 0.9 Natural or artificial threads 2.0 0.7 Treatment of water 1.9 0.918 Communication technique 1.4 5.2 Separation of solid materials 2.0 0.3 Butchering & meat treatment 1.7 0.319 Working of plastics 1.3 2.0 Steam generation 1.9 0.2 Machines for liquids, wind, spring 1.7 0.220 Electrolytic processes 1.3 0.6 Generating vibrations 1.9 0.1 Nuclear physics & engineering 1.6 0.821 Cements & ceramics 1.3 0.8 Sugar or starch industry 1.9 0.1 Building 1.6 2.42 2 Headwear 1.3 0.1 Hand tools & manipulators 1.9 0.9 Generating vibrations 1.5 0.123 Building 1.2 1.9 Distr ibuting gases or l iquids 1.8 0.2 Working of plastics 1.5 2.52 4 Dyes, paints & polishes 1.2 1.7 Cements & ceramics 1.8 1.2 Mechanical metal-working 1.5 1.325 Tobacco 1.1 0.1 Other foods 1.7 1.5 Steam generation 1.5 0.12 6 Yarns 1.1 0.1 Electrolytic processes 1.7 0.7 Distr ibuting gases or l iquids 1.4 0.12 7 Other foods 1.1 1.0 Agriculture 1.6 3.4 Physical & chemical processes 1.4 3.328 Sports & games 1.1 0.7 Hand & travelling articles 1.6 0.5 Decorative arts 1.4 0.129 Layered products 1.0 0.4 Organic molecular compounds 1.6 5.9 Construction of roads & bridge 1.4 0.630 Domestic articles or appliances 1.0 1.8 Fert i l isers 1.5 0.2 Working cement, clay, and stone 1.4 0.331 Working of metals 1.0 0.6 Animal and vegetable oils 1.4 1.2 Sports & games 1.3 0.832 Metallurgy & alloys 1.0 0.4 Educating; cryptography 1.4 0.7 Agriculture 1.3 2.33 3 Computing & counting 1.0 1.4 Dyes, paints & polishes 1.4 2.0 Rai lways 1.3 0.43 4 Bureau accessories 1.0 0.1 Physical & chemical processes 1.4 3.1 Disposal of solid waste 1.2 0.13 5 Printed matter 1.0 0.2 Working of plastics 1.3 2.0 Skins & leather 1.2 0.136 Biochemistry & genetic engineering 1.0 1.4 Mechanical metal-working 1.3 1.1 Grinding & polishing 1.2 0.437 Baking 1.0 0.2 Working cement, clay, and stone 1.3 0.4 Organic chemistry 1.1 10.03 8 Cutt ing tools 0.9 0.3 Construction of roads & bridge 1.3 0.7 Hand & travelling articles 1.1 0.339 Controlling & regulating 0.9 0.6 Treatment of water 1.3 0.6 Life-saving 1.1 0.24 0 Fert i l isers 0.9 0.1 Cleaning 1.3 0.2 Other foods 1.1 0.94 1 Treatment of water 0.9 0.4 Working of metals 1.3 0.7 Metallurgy & alloys 1.1 0.542 Heat exchange 0.9 0.3 Domestic articles or appliances 1.3 2.2 Doors, windows, shutters & ladders 1.0 0.54 3 Water supply 0.8 0.2 Grinding & polishing 1.3 0.5 Heating, ranges & ventilating 1.0 0.944 Conveying, packing & storing 0.8 3.4 Skins & leather 1.2 0.1 Signal l ing 0.9 0.445 Electric power 0.8 1.4 Heating, ranges & ventilating 1.2 1.1 Cements & ceramics 0.9 0.846 Crystal growth 0.8 0.1 Paper-making 1.2 0.6 Wearing apparel 0.9 0.147 Jewelery 0.8 0.1 Hoisting, lifting & hauling 1.2 0.5 Furnaces & ovens 0.9 0.24 8 Drying 0.8 0.1 Electric power 1.1 1.9 Aircraft 0.9 0.349 Hoisting, lifting & hauling 0.8 0.3 Combustion processes 1.1 0.7 Animal and vegetable oils 0.9 0.75 0 Land vehicles 0.8 0.7 Ships or other waterborne vessels 1.1 0.5 Domestic articles or appliances 0.9 1.351 Life-saving 0.7 0.2 Layered products 1.1 0.4 Jewelery 0.9 0.25 2 Liquid handling 0.7 0.2 Water supply 1.1 0.3 Checking-devices 0.8 0.45 3 Checking-devices 0.7 0.3 Medical & veterinary science 1.0 5.5 Petroleum, gas and coke industries 0.8 0.554 Hand & travelling articles 0.7 0.2 Glass & mineral wool 1.0 0.5 Crystal growth 0.8 0.15 5 Basic electronic circuitry 0.7 1.0 Land vehicles 1.0 0.9 Dyes, paints & polishes 0.8 1.35 6 Wearing apparel 0.7 0.1 Inorganic chemistry 1.0 0.7 Printed matter 0.8 0.15 7 Ships or other waterborne vessels 0.6 0.3 Yarns 0.9 0.1 Conveying, packing & storing 0.7 2.85 8 Nuclear physics & engineering 0.6 0.3 Conveying, packing & storing 0.9 3.8 Measuring & test ing 0.7 4.15 9 Engineering elements or units 0.6 2.7 Doors, windows, shutters & ladders 0.9 0.5 Refrigeration or cooling 0.7 0.26 0 Organic chemistry 0.6 4.6 Electr ic techniques 0.9 1.0 Medical & veterinary science 0.7 3.7
All technological fields 1 All technological fields 1 All technological fields 1
Table 6.5.Regional TRCA compared to Europe (EPO, 1978-1995)
Notes : technological classes in bold have the highest growth rate (1981-1985 to 1991-1995) of patent applications at EU15 level;% of patents = share of patents by IPC classe with respect to the total number of patents applied by the region.
Data source : EPO (1998), UEST-DULBEA calculations.
TRCA
# OF PATENTSTRCA
# OF PATENTSTRCA
# OF PATENTS
5 36 . T e c h n o l i g i c a l o u t p u t
FLANDERS WALLONIA BRUSSELS1 Ropes & non-electric cables 16.3 0.6 Weapons 3.3 3.1 Sugar or starch industry 19.7 0.62 Weaving 14.8 5.6 Ammunition 1.7 1.5 Explosives; matches 11.1 0.43 Photo-, cinema- & electrography 10.6 15.7 Metallurgy of iron 1.6 1.6 Heat exchange 8.2 1.84 Brushware 8.9 1.1 Casting & powder metallurgy 1.4 2.2 Inorganic chemistry 8.0 4.25 Print ing 3.1 4.5 Biochemistry& genetic engineering 1.3 4.8 Instrument detai ls 8.0 0.16 Earth drilling & mining 2.3 1.7 Furnaces & ovens 1.3 0.7 Electrolytic processes 7.8 2.77 Agriculture 1.9 5.2 Crushing & treatment of grain 1.3 0.6 Metallurgy of iron 6.8 2.18 Animal and vegetable oils 1.8 2.1 Petroleum, gas and coke industries 1.2 1.9 Biochemistry& genetic engineering 4.8 5.79 Saddlery & upholstery 1.8 0.1 Metallurgy &alloys 1.1 1.1 Earth drilling & mining 4.8 1.6
10 Machines for liquids, wind, spring 1.5 0.2 Life-saving 1.1 0.6 Brushware 4.7 0.311 Combustion processes 1.4 1.2 Hydraulic engineering 1.1 1.3 Layered products 4.7 1.312 Heating, ranges & ventilating 1.3 1.7 Building 1.0 3.9 Working of metals 4.1 1.913 Hydraulic engineering 1.3 0.8 Sports & games 1.0 1.6 Organic molecular compounds 3.7 12.314 Disposal of solid waste 1.2 0.1 Baking 0.9 0.4 Paper-making 3.6 1.115 Metallurgy of iron 1.1 0.6 Headwear 0.8 0.1 Sewing & embroidering 3.4 0.316 Butchering & meat treatment 1.1 0.3 Earth drilling & mining 0.8 1.2 Casting & powder metallurgy 3.2 1.517 Doors, windows, shutters & ladders 1.1 0.9 Natural or artificial threads 0.8 0.7 Treatment of water 3.0 0.918 Communication technique 1.0 5.2 Separation of solid materials 0.8 0.1 Butchering & meat treatment 2.5 0.319 Working of plastics 1.0 2.0 Steam generation 0.8 0.2 Machines for liquids, wind, spring 2.5 0.220 Electrolytic processes 1.0 0.6 Generating vibrations 0.8 0.1 Nuclear physics & engineering 2.5 0.821 Cements & ceramics 0.9 0.8 Sugar or starch industry 0.8 0.1 Building 2.5 2.42 2 Headwear 0.9 0.1 Hand tools & manipulators 0.7 0.9 Generating vibrations 2.3 0.123 Building 0.9 1.9 Distr ibuting gases or l iquids 0.7 0.2 Working of plastics 2.3 2.52 4 Dyes, paints & polishes 0.9 1.7 Cements & ceramics 0.7 1.2 Mechanical metal-working 2.3 1.325 Tobacco 0.8 0.1 Other foods 0.7 1.5 Steam generation 2.2 0.12 6 Yarns 0.8 0.1 Electrolytic processes 0.7 0.7 Distr ibuting gases or l iquids 2.1 0.12 7 Other foods 0.8 1.0 Agriculture 0.7 3.4 Physical & chemical processes 2.1 3.328 Sports & games 0.8 0.7 Hand & travelling articles 0.6 0.5 Decorative arts 2.0 0.129 Layered products 0.8 0.4 Organic molecular compounds 0.6 5.9 Construction of roads & bridge 1.8 0.630 Domestic articles or appliances 0.8 1.8 Fert i l isers 0.6 0.2 Working cement, clay, and stone 1.8 0.331 Working of metals 0.7 0.6 Animal and vegetable oils 0.6 1.2 Sports & games 1.8 0.832 Metallurgy & alloys 0.7 0.4 Educating; cryptography 0.6 0.7 Agriculture 1.8 2.33 3 Computing & counting 0.7 1.4 Dyes, paints & polishes 0.5 2.0 Rai lways 1.8 0.43 4 Bureau accessories 0.7 0.1 Physical & chemical processes 0.5 3.1 Disposal of solid waste 1.7 0.13 5 Printed matter 0.7 0.2 Working of plastics 0.5 2.0 Skins & leather 1.7 0.136 Biochemistry & genetic engineering 0.7 1.4 Mechanical metal-working 0.5 1.1 Grinding & polishing 1.7 0.437 Baking 0.7 0.2 Working cement, clay, and stone 0.5 0.4 Organic chemistry 1.6 10.03 8 Cutt ing tools 0.7 0.3 Construction of roads & bridges 0.5 0.7 Hand & travelling articles 1.6 0.339 Controlling & regulating 0.7 0.6 Treatment of water 0.5 0.6 Life-saving 1.5 0.24 0 Fert i l isers 0.7 0.1 Cleaning 0.5 0.2 Other foods 1.5 0.94 1 Treatment of water 0.6 0.4 Working of metals 0.5 0.7 Metallurgy & alloys 1.5 0.542 Heat exchange 0.6 0.3 Domestic articles or appliances 0.5 2.2 Doors, windows, shutters & ladders 1.5 0.54 3 Water supply 0.6 0.2 Grinding & polishing 0.5 0.5 Heating, ranges & ventilating 1.5 0.944 Conveying, packing & storing 0.6 3.4 Skins & leather 0.5 0.1 Signal l ing 1.5 0.445 Electric power 0.6 1.4 Heating, ranges & ventilating 0.5 1.1 Cements & ceramics 1.5 0.846 Crystal growth 0.6 0.1 Paper-making 0.5 0.6 Wearing apparel 1.4 0.147 Jewelery 0.6 0.1 Hoisting, lifting & hauling 0.5 0.5 Furnaces & ovens 1.4 0.24 8 Drying 0.6 0.1 Electric power 0.5 1.9 Aircraft 1.4 0.349 Hoisting, lifting & hauling 0.6 0.3 Combustion processes 0.4 0.7 Animal and vegetable oils 1.3 0.75 0 Land vehicles 0.6 0.7 Ships or other waterborne vessels 0.4 0.5 Domestic articles or appliances 1.3 1.351 Life-saving 0.5 0.2 Layered products 0.4 0.4 Jewelery 1.3 0.25 2 Liquid handling 0.5 0.2 Water supply 0.4 0.3 Checking-devices 1.2 0.45 3 Checking-devices 0.5 0.3 Medical & veterinary science 0.4 5.5 Petroleum, gas and coke industries 1.2 0.554 Hand & travelling articles 0.5 0.2 Glass & mineral wool 0.4 0.5 Crystal growth 1.1 0.15 5 Basic electronic circuitry 0.5 1.0 Land vehicles 0.4 0.9 Dyes, paints & polishes 1.1 1.35 6 Wearing apparel 0.5 0.1 Inorganic chemistry 0.4 0.7 Printed matter 1.0 0.15 7 Ships or other waterborne vessels 0.5 0.3 Yarns 0.4 0.1 Conveying, packing & storing 1.0 2.85 8 Nuclear physics & engineering 0.5 0.3 Conveying, packing & storing 0.4 3.8 Measuring & test ing 1.0 4.15 9 Engineering elements or units 0.5 2.7 Doors, windows, shutters & ladders 0.4 0.5 Refrigeration or cooling 1.0 0.26 0 Organic chemistry 0.5 4.6 Electr ic techniques 0.4 1.0 Medical & veterinary science 1.0 3.7
All technological fields 0.7 All technological fields 0.4 All technological fields 1.3
Table 6.6.Regional TRCB compared to Europe (EPO, 1978-1995)
Notes : technological classes in bold have the highest growth rate (1981-1985 to 1991-1995) of patent applications at EU15 level; % of patents = share of patents by IPC classe with respect to the total number of patents applied by the region.
Data source : EPO (1998), UEST-DULBEA calculations.
TRCB
# OF PATENTSTRCB
# OF PATENTSTRCB
# OF PATENTS
5 4 6 . T e c h n o l i g i c a l o u t p u t
activities than in the districts along the Belgian border. Forthe most important districts in terms of population or GDP,this can be explained by the presence of HEIs and RTOstogether with business firms in a similar area. The tech-nological activities undertaken by these actors are comple-mentary, e.g. basic versus applied or developmentresearch, and as a result are diversified when consideredas a whole. The number of patent applications in the‘small’ diversified districts is not important and is often theresult of individual innovators. This could explain the hightechnological diversification observed in these regions. Atthe other end, the districts located far away from the cen-tre are more specialised and possess large firms whereR&D activities are concentrated in a few technologicalfields.
Another important determinant of R&D activities is thelevel of diversification of these activities or conversely thedegree of concentration. For instance, because of the risksinherent to innovative activities, firms have more opportu-nities to exploit the new knowledge or complementaritiesand/or economies of scope associated with the R&D activ-ity (Nelson, 1959). On the other hand, a region charac-terised by too much technological diversification may notreach a critical mass in terms of R&D to be successful ininnovating new goods and services. Yet at an empiricallevel, the results of the literature that has examined thesequestions are rather mixed30. Figure 6.9 shows the techno-logical diversification of Belgian districts as measured bythe Herfindhal index computed on the basis of Europeanpatents distributed across IPC classes. It appears that thecentral districts, i.e. the districts located around Brussels,are relatively more diversified in terms of technological
Figure 6.9.Herfindhal Index of technological activities
patents per capita 0,063 to 0,133 (23) 0,133 to 0,405 (16) 0,405 to 0,327 (4)
Note: the higher the Herfindhal index in a district, the lesser its level of technological diversification.Data source: EPO (1998), UEST-DULBEA calculations.
Herfindahl index of technoligical activities
0,63
0,319
0,063
5 56 . T e c h n o l i g i c a l o u t p u t
Table 6.7 gives a picture of the level of spatial concentra-tion of technological activities. The figures reported in thetable are the Herfindhal indexes which take value onewhen complete geographical concentration is observed inone district and value zero in case of equal spatial distrib-ution of patents in the technological field under consider-ation. For sake of space, only the most extreme valuesassociated with technological fields accounting for morethan 10 patents are shown. The main conclusion is thehigh concentration of photography and related activitiesin the district of Antwerp (845 patents in this field or10.6% of total patents applied in Belgium). These activi-ties are performed by one firm, Agfa-Gevaert. Otherimportant activities with high levels of concentration areprinting and telecommunications (Herfindhal indexes of.95 and .89 and 236 and 268 patents respectively). Onceagain, these activities are concentrated in Antwerp. At theother end, activities such as measuring and testing, build-ing, vehicles in general, furniture or packing and storingappear to be more equally distributed across districts.
So far the questions of geographic and technologicaldiversification/concentration have been investigated.Another interesting question to look at is the technologi-cal proximity across regions. Indeed, the more two regionsare close in terms of technological distance, the more theR&D activities of one region is likely to benefit or produceknowledge spillover effects to the other. For instance,Capron and Cincera (1998) have found that Europeanfirms do not appear to be receptive to technologicalknowledge generated by R&D activities of US andJapanese firms nor by spillovers arising from otherEuropean firms31. More specifically, to what extent do thedeficiences observed at the European level with regardsthe lack of sensitiveness of firms to knowledge flows applyto Belgium? More investigation is needed and it may beinteresting to analyse such a question at the regional levelfor European firms.
Besides technological proximities, it is also interesting toexamine to what extent the technological proximity is
IPC TECHNOLOGY CLASS H # OF PATENTS
D07 Ropes; cables other than electric 1 28
G03 Photography; cinematography; electrography; holography 0.99 845
A46 Brushware 0.95 50
B41 Printing 0.95 236
H04 Electric communication technique 0.89 268
F41 Weapons 0.88 43
F28 Heat exchange in general 0.86 37
D03 Weaving 0.85 224
H03 Basic electronic circuitry 0.85 43
G01 Measuring; testing 0.37 285
A23 Other foods or foodstuffs 0.36 83
F23 Combustion apparatus; combustion processes 0.35 37
E04 Building 0.35 187
B62 Land vehicles for travelling otherwise than on rails 0.34 46
B60 Vehicles in general 0.33 121
A63 Sports; games; amusements 0.32 67
A47 Furniture; domestic articles 0.30 140
F24 Heating; ranges; ventilating 0.30 58
B65 Conveying; packing; storing 0.29 274
Table 6.7.Spatial concentration of technological activities
Notes: Herfindhal index (H) based on the distribution of patents across IPC classes across regions. A value equal to one indicates a perfect concentration of the activity in a single district. A value equal to zero means an equally distributed activity across all the districts.
Data source: EPO (1998), UEST-DULBEA calculations.
related to spatial proximity. Table A.6.4 in the appendixreports technological proximities across Flemish districtsand Belgian regions. At regional level, Brussels is closer toWallonia than Flanders and Flanders is closer to Walloniathan Brussels. This observation is coherent with the TRCAfindings which indicated that the Dutch-speaking part ofthe country is more specialised in technologies such asinstruments, electronic components, telecommunicationsor textiles in the region of Kortrijk, while the French-speak-ing side performs relatively more R&D in organic chem-istry and pharmaceuticals and metallurgy and weapons inWallonia. At the district level, it is interesting to note thatthe closest areas in terms of technological distance arealso the nearest in term of spatial distance, e.g. Bruggeand Eeklo; Leuven and Hasselt; Leuven and Mechelen orIeper and Kortrijk.
5 6 6 . T e c h n o l i g i c a l o u t p u t
Another useful indicator to examine technological andspatial spillover effects is patent counts citations. Forinstance the paper by Jaffe et al. (1993) finds that patentssignificantly do more often cite scientific papers and otherpatents from geographically localised institutions. Yet thestudy of Clarysse et al. (1998) leads to an opposite con-clusion as far as Flemish patenting actors are concerned.Indeed, the results obtained by the authors suggest thatpatents of Flemish firms are cited by US and/or Japanesefirms but not (or little) by the Flemish actors composingthe VINS32. Here also it may be useful to deepen this kindof investigation by, for instance, considering the otherBelgian regions or European regions belonging to thesame techno-clusters as Flanders.
6Over the period 1978-1997 the number of patents
has risen in each region except at the end of the peri-od where a decline can be observed. The increase wasmuch more important in the Flemish region than inthe other two. The returns of technological activities interms of patents with respect to R&D expenses appearto be higher in Flanders. There is a relative depen-dence of Belgium towards subsidiaries of foreignmultinational firms, which might be at the source of abrain drain. In Flanders, large companies hold a high-er share of the region patenting activities. In theFlemish region, four districts concentrate a main partof patents: Antwerpen, Leuven, Turnhout and Kortrijk.As far as the distinction between intra- and extra-mural R&D is concerned, Flemish firms seem to per-form more R&D within their own walls than is the casein the Walloon and Brussels regions. On the whole,Flanders appears to be more specialised in the field ofinstruments while Brussels and Wallonia apply rela-tively more patents in the field of chemistry and phar-maceuticals. At regional level, in terms of technologi-cal distance, Flanders is closer to Wallonia thanBrussels and Brussels is closer to Wallonia thanFlanders.
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25 For instance, not all inventions are patented, nor all are patentable, and otherexisting methods in appropriating an innovation such as industrial secrecy maybe preferred. For the relevance of patent statistics as an indicator of Scienceand Technology activities, see for instance, Basberg (1987), Glisman and Horn(1988) or Archibuggi and Pianta (1992).
26 It should be noted that this decrease is of a technical nature, i.e. it does notreflect a real downwards trend. Indeed, it takes about two years for patentapplications to be integrated into the EPO database.
27 Source: See Meeusen et al. (1999).28 Source: l’Echo, 27/12/1997.29 The technical issue discussed before does not apply in the case of USPTO since
patents counts refer to granted patents and not to applications.30 See Cohen (1997) for a survey.31 The United States are mainly sensitive to their national stock of spillovers while
Japan appears to draw from the international stock.32 This result may be a consequence of using US citations for European firms, and
in this case Flemish ones. As shown in this section, Flemish firms, and espe-cially SMEs, have a low propensity to claim patents at the USPTO.
5 7
What have we learned from the analysis of the VINS ? Themain findings obtained in the present study can be expect-ed to yield some useful answers regarding the followingquestions:
• What are the actors composing the VINS and their linkswith the BIS ?
• What are the institutional differences in S&T activitiesbetween the federal state and the regional authorities ?
• What are the generic sources of the knowledge distribu-tion power ?
• What is the Belgian R&D potential compared to theEuropean regional landscape ?
• What can be said about its implications with regardscompetitiveness ?
• What characterise or differentiate the interactionsbetween the actors ?
• What is the technological performance ?
7.1. S&T LESSONS FROM THE VINS
VINS – In the analysis of NISs the focus is put upon the setof actors involved in S&T activities such as the creation, dif-fusion and absorption of new knowledge, technologies andskills as well as the design, implementation and co-ordina-tion of policies that influence the relationships in terms ofinteractions and interconnections between actors.
• The systemic approach for studying innovation and tech-nical change is still in its infancy. Whatever the nationalinstitutional frameworks, a main teaching of regionaleconomics is that national growth processes have alwaysbeen underpinned by innovative milieux and economiesof agglomeration. Consequently, the analysis of RISs iscertainly an appropriate approach to improve our knowl-edge of interactions between organisations and institu-tions and their role in the innovation process. They areindeed vital components of the performance, structure,functioning and governance of innovation systems. TheVINS is evolving towards a governance pattern that canbe classified as an interactive networked architecture. Onthe one hand, the option of Flanders to build industrialclusters and large-scale RTOs should be favourable to thenetworking of its regional innovation system. On the otherhand, initiatives in order to promote the entrepreneurialculture, the intertwining between large and indigenous
firms and the bridging institutions should hopefully leadto a highly interactive regional innovation system.
• Flemish firms account for around two thirds of BelgianR&D expenses against a quarter in Wallonia and the restin the Brussels region. The relative S&T budget contribu-tion of the different authorities to the total of Belgiumshows that the Flemish community appears to be themain contributor. This high contribution illustrates that inthe last years, regional governments have given majorspecific inflexions to the S&T policy.
• The S&T policy design and its implementation is mainlyunder the responsibility of regional authorities. Yet onemajor difference concerns the fiscal policy in favour ofinnovation, which falls within the federal responsibility.The funding of the education system and universityresearch in the Flemish region is in relative terms lessimportant than in the French-speaking side of the coun-try. As regards the support to industrial R&D, the totalbudgets of both the Flemish and French Communitiesand Walloon region are almost the same. However, morepublic R&D funds are assigned to RTOs in Flanders whichis explained by the creation of large Flemish researchcentres such as VIB, IMEC and VITO.
Education and training – The quality of humanresources is a main factor of economic growth and com-petitiveness. Past and present investments in human capitalexplain to a large extent the present and the future of coun-tries skills and competencies.
• Compared to other European countries, the educationalattainment of the young population in Belgium reveals agood performance indicator for mathematics but under-scores in science. At regional level, data show that thestudents of the Flemish Community obtain better indica-tors than those of the French Community. The indicatorobtained for higher education illustrates the very goodperformance of Belgium compared to the European aver-age. The Flemish region records a slight disadvantagewith respect to its Southern counterpart. As regards thedistribution of students in higher education according tothe different teaching categories, substantial differencesare observed among Communities. Indeed, more
SS ee cc tt ii oo nn 77S&T policy perspectives
5 8 7 . S & T p o l i c y p e r s p e c t i v e s
Flemish students choose a technical training while moreFrench-speaking students prefer teaching training.
• The Belgian distribution of the active population differs sig-nificantly from the European average. The high value ofthe indexes for the low and high qualification levels indi-cates that Belgium is characterised by a dual working force,however less apparent in Flanders. Finally, within Europe,Belgium is one of the countries with the lowest employmentrates of the population. The low-skilled working force con-centrates two thirds of the unemployed in Belgium.
Regional R&D intensity and technological bases -Given that regions have been in charge of the S&T policydesign and implementation for the past twenty years, whatis the relative position of the Flemish region as compared tothe other Belgian regions and within the European region-al landscape?
• The GDP per capita indexes show that Flanders andBrussels have been able to efficiently exploit their eco-nomic advantages while the economic base of theWalloon region has been largely affected by the declineof industrial activities. In terms of labour productivity, highindexes are observed in Flanders and notwithstanding itsweaker economic base, in Wallonia. Conversely, Brusselsis characterised by a lower productivity index despite itsfavourable central position.
• Except for government R&D, Flanders has high techno-logical indexes, especially for indicators representative ofthe innovativeness degree. Mainly thanks to its centralposition Brussels region also exhibits good indexes inbusiness R&D. Yet the output indexes are globally veryweak, which can be explained by the high commutingrate of the active population. The productivity and highereducation R&D indexes obtained for Wallonia indicatethat the region has maintained a satisfying level in somebasic components of both its transfer and absorptivecapacities.
• At a European level, regional R&D disparities appearmuch deeper than wealth ones. The regional distributionof both business and government R&D personnel, ismore concentrated than that of higher education R&D.
The higher concentration is observed for patent applica-tions. Compared to the other European regions, the dis-persion between the patents and R&D per capita scoresobtained by the Belgian regions is much lower than thecorresponding one observed across European regions.The Flemish region shows indexes that are close to thoseobserved for the Netherlands and the regions ofPiemonte, Lombardia, Niedersachsen or Alsace.
• The clustering analysis of European regions shows thatthe cluster which contains Flanders is characterised by ahigher degree of innovativeness and technological inten-sities than the European average but an unbalancedR&D mix. The regions included in this cluster present ahigh potential of endogenous development. The clusterof regions including Brussels is still characterised by animportant creative capacity. However, these regions areless well positioned with regard to the R&D mix distribu-tion as well as in terms of competitiveness. The clusterwhich includes Wallonia is characterised by low indexes oftechnological intensity and technological base whichimplies a weak creative capacity. Nevertheless they keepa significant potential with regard to the transfer andabsorptive capacities.
Technological collaborations - R&D collaborationsimply different types of actors and can take several forms.Examining these kinds of collaborations allows one to bet-ter appreciate to what extent Belgian regional and federalorganisations are engaged in world-wide research net-works.
• The Belgian participation in European R&D pro-grammes is very high compared to other MemberStates. The weight of Belgian collaborations with neigh-bouring countries is particularly important. However, interms of intra-national collaboration links, Belgium hasrelatively less collaborative links than other small coun-tries. Belgian teams do not seem to exploit sufficientlytheir complementarities and specialisation patterns. Ata regional level, Flemish firms and research centreshave a higher propensity to collaborate at Europeanlevel than their Walloon counterparts. Yet the French-speaking universities appear to be more integrated inthe European networks than their Flemish counterparts.
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In Flanders, the high participation of RTOs in pre-com-petitive research can be partially viewed as a conse-quence of the Flemish S&T policy. Regarding the tech-nological proximities between organisations, the HEIscomplement rather than substitute the industry partici-pations. At the infra-regional level, five districts concen-trate three quarters of all the participations: Brussels,Leuven, Ghent, Nivelles and Liège. Electronics andinformation technologies appear to be two mainstrengths of the Flemish S&T system at Belgian as wellas at European level.
• To what extent these results are translated to an equallyfavourable position in near-market research collabora-tions promoted by the Eureka projects? Although Belgiumhas a high participation in the total number of projects,the Belgian teams only represent a reduced number ofparticipating EU organisations and, last but not least, itsfinancial contribution is not as high as could be expected.Belgian Eureka participations are highly concentrated in afew districts, mainly located in the Flemish region.Furthermore, the Flemish participants are the main con-tractors in a significant number of research projects. Onthe whole, we observe that SMEs participate more thanlarge companies. With regard to the technological fields,the regional differences are very limited. Three techno-logical fields concentrate a large part of collaborations:information technology, environment and the medicalarea and biotechnology. In addition to the higher partici-pation of Flanders to European networks, infra-regionallinks are stronger in Flanders than in other regions. Aquestion mark is certainly the lesser propensity of bothFlemish and Walloon teams to collaborate together, intra-regional collaborations being more important than inter-regional ones.
• The data available on technological co-operationbetween enterprises in the world indicate that thealliances in which Belgian enterprises are recorded is lim-ited. The high degree of multinationalisation of the coun-try could explain this very average position. Indeed, in acountry whose economic structure is largely dominatedby foreign companies, the participation in internationalstrategic alliances could be hampered by world-widestrategies of headquarters.
Technological Output - Patenting activities are one ofthe main indicators of the success of technological activi-ties. The most important features emerging from the analy-sis of Belgian patenting activities can be summarised as fol-lows.
• The regional distribution of Belgian patents shows anincrease of European patent applications and US grantsover the period 1978-1997. Yet this increase has beenmarkedly higher in Flanders. Furthermore, the return oftechnological activities appears to be higher in thisregion. A first factor explaining this high performance ofthe Flemish region is the higher degree of innovativenessof the Flemish firms. A second factor is the high concen-tration of patenting activities in a few large Flemish firms.At a geographic level, the district of Antwerp accounts formore than one quarter of patents. Leuven, TurnhoutKortrijk and Ghent are the four next most importantFlemish districts in terms of patenting.
• Belgium, with a high part of its inventors working forextra-national firms or foreign firms with subsidiarieslocated in Belgium but that do not patent as Belgianfirms, is one of the European countries the most con-cerned by the ‘knowledge drain’ phenomenon. In a simi-lar vein, some of the top Belgian patenting firms aremultinationals which have subsidiaries located inBelgium. This raises the question of whether the R&Doutcomes of some of these multinationals are effectivelyexploited in Belgium or simply brought back to the for-eign mother company.
• Another factor that must be kept in mind when analysingpatent counts, is the composition of R&D activities. Thedistinction between the ‘R’ and the ‘D’ component ofR&D activities suggest no clear-cut differences across theregions. Belgian firms have spent on average one quarterof their R&D investments on research activities and threequarters on development. As regards the personnelaccounting component of R&D expenses, the shareobserved for the Flemish firms is somewhat higher thanin Brussels and Wallonia. Furthermore, the Flemish firmsappear to perform more R&D within their ‘own’ wallsthan is the case in Brussels or Wallonia.
6 0 7 . S & T p o l i c y p e r s p e c t i v e s
• The comparison of regional technological specialisationpattern suggests that Flanders holds a higher share of itspatent distribution in the photography, agriculture,telecommunications, printing and weaving sectors thanother regions. On the whole, the districts located in thecentral part of Belgium are more diversified in terms oftechnological activities. The presence of firms togetherwith universities or RTOs may partly explain this results.Finally, the indexes of technological proximity suggestasymmetric spillovers effects across regions since Brusselsappears to be «technologically» closer to Wallonia thanfrom Flanders and Flanders closer to Wallonia thanBrussels.
7.2. S&T POLICY PERSPECTIVES
The efficiency of RISs could be appreciated with respect tothe plurality of institutions and their capacity to deal withthe diversity of micro-level activity rather than implementingcentrally driven policy instruments. A major concern for pol-icy-makers is to remove barriers to innovative entry andensure the efficiency of market selection processes[Metcalfe (1997)]. In fact, «a system of science and tech-nology learning…must be characterised by its distributionpower as much as by its capabilities for generating newknowledge, that is to say, by the system’s ability to supportand improve the efficient functioning of procedures for dis-tributing and utilising knowledge» [David and Foray(1995)]. The focus of attention is now on the institutionalfailure instead of market failure, on the incentive structuresand their intertwining that lead to expand «the potentialspace for the use of knowledge». As in any research field,much remains to be clarified and only some issues havebeen investigated in the present study.
While the efficiency of the BIS could be improved by tar-geting actions aimed at stimulating interregional collabora-tions to improve the diffusion of knowledge, informationand good practices, at regional level, and especially in theframework of the emerging VINS, the policy focus shouldbe put on the strengthening of the knowledge infrastruc-ture. Three main types of actions deserve special attention:the development of the knowledge base, the design and theimplementation of S&T policy and the enhancement of theknowledge distribution power.
As regards the issue related to the strenghtening of theknowledge base, it is worth drawing some attention to thefollowing three main points:
• In the mid term, the public gap in R&D expendituresmight weaken the Belgian technological base so thatsome efforts should be devoted to adjust the R&D inten-sity to the European average. Although some achieve-ment in that direction can already be observed in theFlemish region, more efforts are required to diminish thepublic gap. A high level of university research and an effi-cient public technology infrastructure are prerequisites tohigh business R&D. Although Belgium is characterised bya good performance with regard to the higher educationresearch, the R&D indexes are close to the Europeanaverage, which implies that universities do not have attheir disposal similar means than those devoted by otherhighly industrialised countries to their university sector.More disturbing is the insufficient development of publicresearch laboratories and technology awareness centresthat are often recognised as playing important roles inscientific learning, in transfer sciences and in underpin-ning the infratechnology of standards and metrology[Leyden and Link (1992), Tassey (1991)]. The mismatch-es are similar for the three regions and are a main chal-lenge for the VINS as well as for the BIS. It can beacknowledged that part of the gap is closing in Flandersthanks to the creation of some institutions such as theVITO or Technopolis but there is still a long way to go inorder to have similar bridging demand-driven institutionslike those existing in France and Germany, the two mainEuropean technology leaders.
• Despite the dynamism of Belgian organisations inEuropean R&D networks, there is a clear interregionalmismatch in the way regional actors behave in interna-tional collaborations. Furthermore, there is some evi-dence of an insufficient valorisation of their S&T potentialin economic terms. Public authorities should design pro-grammes aimed at deepening and completing theacquired knowledge with special stress on downstreamcapabilities such as manufacturing and commercialisa-tion capabilities. Given that the universities of the threeregions are highly active in European pre-competitive net-works, does each region have much to gain in stimulat-
6 17 . S & T p o l i c y p e r s p e c t i v e s
ing interregional research partnerships rather than evolv-ing independently? All the analysed indicators give evi-dence that the regions are more complementary thansubstitutable so that some economies of scale and scopecould result through sharing costs, technical expertiseand risks. In an economic environment characterised bythe techno-globalisation phenomenon would it not beprofitable to regions to take advantage of their geo-graphic proximity as well as capitalising their long-stand-ing relational proximity?
• The difference of patenting activities as shown by the dis-tinction between applicants and inventors suggests theremight be important leakages of innovative outcomes,which calls for specific public actions in order to betterinternalise them. The inability of governments to reap theeconomic returns to domestic R&D leads to an indige-nous knowledge drain. In a world of increased interna-tional interdependence, both regional and federal gov-ernments should think about the best way of stimulatinginterregional spillovers. The present focus of the Flemishgovernment on the forming of both technological andeconomic clusters is certainly a good step in this direction.Then, as shown by the measures of revealed technologi-cal advantages, the country remains heavily dependenton low and medium tech industries so that public effortsshould be directed towards targeted high growth marketniches such as for instance, the Flemish initiative to pro-mote the creation of a «Flanders language valley» and a«Flanders biotechnology valley». Yet what is more impor-tant is the ability of mature industries to adopt and toassimilate the products of R&D-intensive industries. Oncemore, investments in public research infrastructures andhuman capital are likely to be more profitable than sub-sidies to industrial R&D.
With regard to the design and implementation of S&Tpolicies:
• Are there not some important grounds for a strengthen-ing of the inter-regional complementarities and compen-tencies by actions implemented by the public actors inorder to achieve the necessary critical mass in someresearch fields, to avoid duplication of research projectsand the perverse effects of unfounded technological
competition? Indeed, the observation that intra-regionalcollaborations are more important than inter-regionalones gives evidence of a spreading-out process of region-al innovation systems. This observation leads one to sug-gest that there are certainly opportunity windows fromboth federal and regional authorities aimed at stimulatingjoint inter-regional near-market research consortia. Ifthere is a rationale behind the willingness to build an effi-cient RIS, can it be expected to capture at a regional levelall the synergy effects that exist or existed at federal level?
• It would be useful to improve the fine-tuning of the S&Tpolicy mix (e.g. direct subsidies vs. favourable fiscalregimes, diffusion and adoption policies beside supplypolicies) in order to boost the leverage effect of publicintervention. For instance the stress may be put on tech-nological assimilation and adaptation instead of focusingon technological advance. Then, besides the financialinstruments to foster S&T activities, new initiatives of amore qualitative scope could be further developed. Oneexample are the initiatives of IWT to make available infor-mation and expertise or enhance networks. By referenceto the chain-linked model (Kline and Rosenberg, 1986),what can be done to improve the efficiency of the feed-back loop effects between the different stages of theinnovative process? Or given the low patent propensity ofBelgian companies, what are the measures to be taken toimprove the intellectual property rights system? Thesequestions suggest that whatever the policy mix, there is aneed to develop efficient tools for assessing the effective-ness of S&T instruments as well as the results of S&T poli-cies. Public interventions have to be adapted to the needsof research institutions so that it is vital to apprehend cor-rectly what disables the innovation propensity and the val-orisation process of innovativeness and to concentrateefforts on the resolving of bottlenecks. One example is thelack of sufficient risk capital provision to isolated inven-tors, spin-off and other innovative starting firms.33
Last but not least, the mismatches between the compo-nents of the distribution power lead to attract attention onthe need to improve the links between the creative, transferand absorptive capacities in the following fields:
6 2 7 . S & T p o l i c y p e r s p e c t i v e s
• Despite the regions, and more especially Flanders, bene-fit from a favourable European positioning for some sci-entific and technological indicators, they appear to facehigh difficulties in bridging the gap between their techno-logical performances and the economic valorisation ofresults. Some bridging institutions such as transfer tech-nology and diffusion centres and interweaving institutionscould strive to correct these institutional failures. In thisfield there are also some economies of scale and scopeto close the gap by creating common bridging institutionsspatially interconnected. At a European scale, theBusiness Innovation Relay Centres are one recent exam-ple. Other examples of bridging institutions are Brussels-Technopole created some years ago or more recently theTechnopolis Forum in Mechelen to be launched this year.
• At Belgian level, there is a significant deficit of graduatesin natural and applied sciences. Though nothing can besaid regarding the regional component of this deficit, thelow scores about the learning of science and mathemat-ics in French-speaking schools is a clear signal there issomething wrong in the absorptive process of knowledgein a part of the country. Appropriated measures should beimplemented in order to improve both accessibility andreceptivity to knowledge. More work remains to be donein order to judge whether these preliminary results are apremonitory signal that an adverse process of technologygap is in gestation.
At the eve of the XXIth century, the regional governance ofthe Belgian NIS is radically changing the institutional set-upof the country. But even if regions and communities areevolving in different directions due to their specific industri-al and cultural heritage, they still remain conditioned by theBelgian historical background. Yet as pointed out by Porter(1990) and stressed again by Freeman (1997), the increas-ing vulnerability of national states to external shocks andthe intensification of techno-global competition make therole of the home nation more important, not less. Asemphasised by Braczyk and Heidenreich (1998) in theiranalysis of regional governance structures in a globalisedworld, «theories postulating the end of nation-states neglectunjustifiably the continuing significance of national workand management patterns». Otherwise, it also remainstrue that other authors stress out the limitations of national
policies and more and more question the relevance of NISs(Humbert, 1993). For instance, in Antonelli’s (1994) pointof view, RISs are of first importance for network develop-ment and new technology systems. Moreover local infra-structures, spatial spillover effects in skills and local labourmarkets, services or more fundamentally mutual trust andpersonal relationships are essential ingredients for theemergence of RISs. At the level of federated authorithies,the main achievement of RISs rests in the development andstabilisation of regional networks through regional contactnetworks, training and research institutions or industrial andfinancial interpenetration (Braczyk and Heidenreich, 1998).
The question, then, is to know if there are still tasks andwhat are these tasks that the federated entities are able toaccomplish more efficiently than the federal state, andwhich others the federal state might still satisfy in a moreappropriate way because they transcend the regionalspaces. In the case of a federal state such as Germany(Krull and Meyer-Krahmer, 1996), one of the technologicalleading countries, we observe that there exists at federallevel intermediary bodies to ensuring the co-ordination andconsensus of the decision making of S&T activities as wellas collaborations by means of jointly financed institutionsand programmes. Nevertheless, it is worth recognising thateach country has its specificity and that the appropriate bal-ance of competence fields among decision making bodiesremains an open question. This represents an importantand complex issue to which should be devoted further stud-ies. Whatever the future evolution of the governance pat-terns of RISs, it must be kept in mind that science and tech-nology, and more generally knowledge, have no frontiers,even at the regional level.
6 37 . S & T p o l i c y p e r s p e c t i v e s
33 See for instance Debackere et al. (1998) for an analysis of the supply of riskcapital in Belgium.
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7The VINS can be labelled as evolving towards an
interactive networked innovation system. As the bridg-ing network, the BIS could gain in efficiency by target-ing actions aimed at stimulating interregional collabo-rations to improve the diffusion of knowledge, infor-mation and good practices. In the framework of theemerging VINS, the policy focus should be put on thestrengthening of the knowledge infrastructure. Threemain types of actions deserve a special attention: thestrenghtening of the knowledge base, the design andthe implementation of S&T policy and the enhance-ment of the knowledge distribution power. In an eco-nomic environment characterised by the techno-glob-alisation phenomenon it will certainly be a mistake noto take advantage of the geographic proximity as wellas not capitalising the long-standing relational prox-imity among regions. On the eve of the XXIth centu-ry, the regional governance of the Belgian NIS is rad-ically changing the institutional set-up of the countrybut even if regions and communities are evolving indifferent directions due to their specific industrial andcultural heritage, they remain largely conditioned bytheir common historical background.
6 4
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• Humbert M., 1993, «The Impact of Globalisation onEurope’s Firms and Industries», London, Pinter.
• Jaffe A.B., M. Trajtenberg, R. Henderson,1993, «Geographic Localization of KnowledgeSpillovers as Evidenced by Patent Citations», TheQuarterly Journal of Economics, 108(3), pp. 577-98.
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• Kline J., N. Rosenberg, 1986, «An Overview ofInnovation» in Landau R. and Rosenberg N. (eds), ThePositive Sum Strategy: Harnessing Technology forEconomic Growth, National Academic Press,Washington, pp. 275-305.
• Krull W., F. Meyer-Kramer, 1996, «Science,Technology, and Innovation in Germany - Changesand Challenges in 1990s», in Krull W. and Meyer-Kramer (eds), Science and technology in Germany,Cartermill, London, pp. 3-29.
• l ’Echo, 27/12/1997, «Le brevet: un outil et des ser-vices fort utiles».
• Larosse J., 1997a, Het Vlaams Innovatiesystem: eennieuw statistisch beleidskader, VTO-Studies, 1.
• Larosse J., 1997b, «Theoretische en empirischebouwstenen van het ‘Vlaams Innovatie Systeem’»,VTO-Studies, 1a.
• Levin R.C., A.K. Klevorick, R.R. Nelson, S.G.Winter, 1987, «Appropriating the Returns fromIndustrial Research and Development», BrookingsPapers on Economic Activity, 3, pp. 783-831.
• Leyden D., A. Link, 1992, Government’s Role inInnovation, Norwell, Kluwer Academic Publishers.
• Lundvall B.-A., 1992, «Introduction» in Lundvall B.-A. (ed.), National Systems of Innovation, Towards aTheory of Innovation and Interactive Learning, PinterPublishers, London, pp. 1-19.
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• Meeusen W., M. Cincera, A. Hollants, S.Suetens , P. Teir l inck, 1999, «O&O-Uitgaven enO&O-Tewerkstelling in de Vlaamse ondernemingen»,in Vlaams Indicatorenboek - Wetenschap InnovatieTechnologie, IWT and AWI (Eds), Brussels : Ministerievan de Vlaamse Gemeenschap, pp. 72-80.
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6 6
• Nelson R., 1990, «Institutions Supporting TechnicalChange in the United States», in Dosi G. et al. (eds.),Technical Change and Economic Theory, PinterPublishers, London, pp. 312-29.
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6 7
AA pp pp ee nn dd ii cc ee ssAppendices
- per capita participation index: 100*(Pi/popi)/(PE/popE)
- per researcher participation index: 100*(Pi/resi)/(PE/resE)
- distribution index: 100*(Pij/Pi)/(PEj/PEj)
- per capita collaborative links indexes: 100*(Li/popi)/(LE/popE)
- per researcher collaborative links indexes: 100*(Li/resi)/(LE/resE)
- the mutual collaboration spatial specialisation: 100*(Li1/Li)/(L1/LE)
where: Pi = number of participations of country i
popi = population of country i
resi = number of researchers of country i
Pij = number of participations of the category of actors j in the country i
Li = number of collaborative links of country i
Lil = number of collaborative links between the country i and the country l
E = subscript for Europe
Table A.5.1.Measure of Indexes
GOVERNMENT HEIs FIRMS Others RTOs
Bru Fla Wal Bru Fla Wal Bru Fla Wal Bru Fla Wal Bru Fla Wal
GOV Brussels 1
Flanders 0.4 1
Wallonia 0.6 0.7 1
HEIs Brussels 0.7 0.3 0.4 1
Flanders 0.7 0.3 0.5 1 1
Wallonia 0.7 0.4 0.5 1 1 1
FIRMS Brussels 0.5 0.4 0.3 0.3 0.4 0.4 1
Flanders 0.4 0.3 0.2 0.3 0.3 0.3 0.9 1
Wallonia 0.4 0.3 0.4 0.3 0.4 0.4 0.8 0.9 1
Others Brussels 0.6 0.3 0.4 0.8 0.8 0.8 0.5 0.4 0.3 1
Flanders 0.7 0.3 0.6 0.8 0.8 0.8 0.6 0.4 0.4 0.7 1
Wallonia 0.6 0.4 0.5 0.7 0.7 0.7 0.6 0.5 0.4 0.7 0.8 1
RTOs Brussels 0.7 0.4 0.5 0.8 0.8 0.8 0.5 0.5 0.6 0.7 0.7 0.6 1
Flanders 0.6 0.3 0.4 0.5 0.6 0.6 0.8 0.8 0.7 0.6 0.6 0.6 0.7 1
Wallonia 0.2 0.1 0.2 0.2 0.3 0.3 0.4 0.6 0.8 0.1 0.2 0.2 0.4 0.4 1
Table A.5.2.Cordis projects : Technological proximities
Note : proximity index performed as the angular separation between the vectors of participations distribution across technological key words of projects.
Data source : Cordis, UEST-DULBEA calculations.
6 8
Tabl
e A
.5.3
. TR
CA in
dex
by te
chno
logi
cal f
ield
(CO
RDIS
pro
ject
s, 1
987-
1998
)
AN
TWER
PG
HEN
TH
ALL
E-V
ILV
OO
RD
EH
ASS
ELT
Tele
com
mun
icat
ions
180
224
Res
ourc
es o
f th
e Se
a, F
ishe
ries
217
368
Aer
ospa
ce T
echn
olog
y20
224
6A
eros
pace
Tec
hnol
ogy
220
268
Med
icin
e, H
ealth
271
205
Mea
sure
men
t M
etho
ds18
726
7In
dust
rial M
anuf
actu
re13
412
4In
dust
rial M
anuf
actu
re17
516
2
Elec
tron
ics,
Mic
roel
ectr
onic
s14
618
7A
gric
ultu
re17
822
9St
anda
rds
8612
3M
ater
ials
Tec
hnol
ogy
179
153
Agr
icul
ture
141
181
Stan
dard
s16
022
9M
easu
rem
ent
Met
hods
8412
0Te
leco
mm
unic
atio
ns94
117
Mea
sure
men
t M
etho
ds11
616
6Bi
otec
hnol
ogy
164
175
Elec
tron
ics,
Mic
roel
ectr
onic
s93
119
Foss
il Fu
els
194
107
Info
rmat
ion
Proc
essi
ng12
915
6El
ectr
onic
s, M
icro
elec
tron
ics
8711
1R
esou
rces
of
the
Sea,
Fis
herie
s64
109
Ren
ewab
le S
ourc
es o
f En
ergy
181
101
Stan
dard
s10
414
9A
eros
pace
Tec
hnol
ogy
7996
Mat
eria
ls T
echn
olog
y12
710
8In
form
atio
n Pr
oces
sing
7591
Aer
ospa
ce T
echn
olog
y74
90En
viro
nmen
tal P
rote
ctio
n10
891
Info
rmat
ion
Proc
essi
ng87
105
Med
icin
e, H
ealth
109
82
Safe
ty86
87In
form
atio
n Pr
oces
sing
6983
Agr
icul
ture
8010
2Sa
fety
6262
Envi
ronm
enta
l Pro
tect
ion
9580
Indu
stria
l Man
ufac
ture
8781
Envi
ronm
enta
l Pro
tect
ion
105
89El
ectr
onic
s, M
icro
elec
tron
ics
4152
Biot
echn
olog
y61
65R
adia
tion
Prot
ectio
n71
75Te
leco
mm
unic
atio
ns57
71Bi
otec
hnol
ogy
4649
Res
ourc
es o
f th
e Se
a, F
ishe
ries
3763
Safe
ty73
74Bi
otec
hnol
ogy
6569
Res
ourc
es o
f th
e Se
a, F
ishe
ries
1830
Indu
stria
l Man
ufac
ture
6157
Mat
eria
ls T
echn
olog
y82
70Sa
fety
6768
Mea
sure
men
t M
etho
ds20
28
Mat
eria
ls T
echn
olog
y59
50M
edic
ine,
Hea
lth86
65M
edic
ine,
Hea
lth88
66A
gric
ultu
re22
28
Ren
ewab
le S
ourc
es o
f En
ergy
6536
Tele
com
mun
icat
ions
4556
Ren
ewab
le S
ourc
es o
f En
ergy
8447
Stan
dard
s18
25
Rad
iatio
n Pr
otec
tion
3335
Foss
il Fu
els
5731
Foss
il Fu
els
7843
Envi
ronm
enta
l Pro
tect
ion
2320
Foss
il Fu
els
6033
Ren
ewab
le S
ourc
es o
f En
ergy
5330
Rad
iatio
n Pr
otec
tion
00
Rad
iatio
n Pr
otec
tion
00
Coo
rdin
atio
n, C
oope
ratio
n13
617
1C
oord
inat
ion,
Coo
pera
tion
117
148
Coo
rdin
atio
n, C
oope
ratio
n52
65C
oord
inat
ion,
Coo
pera
tion
5671
Educ
atio
n, T
rain
ing
9210
2Ed
ucat
ion,
Tra
inin
g91
101
Educ
atio
n, T
rain
ing
5055
Educ
atio
n, T
rain
ing
111
123
TRCA
-BELTR
CA -E
UR
TRCA
-BELTR
CA -E
UR
TRCA
-BELTR
CA -E
UR
TRCA
-BELTR
CA -E
UR
6 9Ta
ble
A.5
.3.
TRCA
inde
x by
tech
nolo
gica
l fie
ld (C
ORD
IS p
roje
cts,
198
7-19
98) (
cont
inue
d)
KO
RTR
IJK
LEU
VEN
TUR
NH
OU
TO
THER
FLE
MIS
CH
DIS
TRIC
TS
Aer
ospa
ce T
echn
olog
y23
328
3El
ectr
onic
s, M
icro
elec
tron
ics
191
244
Rad
iatio
n Pr
otec
tion
957
1011
Aer
ospa
ce T
echn
olog
y25
831
4
Tele
com
mun
icat
ions
173
215
Info
rmat
ion
Proc
essi
ng15
418
6M
easu
rem
ent
Met
hods
319
456
Res
ourc
es o
f th
e Se
a, F
ishe
ries
142
241
Elec
tron
ics,
Mic
roel
ectr
onic
s14
117
9R
esou
rces
of
the
Sea,
Fis
herie
s90
152
Stan
dard
s27
339
1In
dust
rial M
anuf
actu
re21
019
4
Indu
stria
l Man
ufac
ture
178
165
Aer
ospa
ce T
echn
olog
y11
013
3Sa
fety
263
265
Mat
eria
ls T
echn
olog
y19
616
8
Mat
eria
ls T
echn
olog
y18
515
8A
gric
ultu
re74
95A
eros
pace
Tec
hnol
ogy
101
123
Tele
com
mun
icat
ions
9912
3
Info
rmat
ion
Proc
essi
ng12
615
2Bi
otec
hnol
ogy
8894
Indu
stria
l Man
ufac
ture
8578
Agr
icul
ture
7394
Mea
sure
men
t M
etho
ds46
65Te
leco
mm
unic
atio
ns75
93M
ater
ials
Tec
hnol
ogy
8472
Info
rmat
ion
Proc
essi
ng66
80
Stan
dard
s41
59M
edic
ine,
Hea
lth10
680
Envi
ronm
enta
l Pro
tect
ion
7765
Elec
tron
ics,
Mic
roel
ectr
onic
s57
73
Foss
il Fu
els
5027
Indu
stria
l Man
ufac
ture
8578
Ren
ewab
le S
ourc
es o
f En
ergy
102
57M
easu
rem
ent
Met
hods
4970
Envi
ronm
enta
l Pro
tect
ion
2723
Foss
il Fu
els
133
73Fo
ssil
Fuel
s83
45St
anda
rds
4462
Biot
echn
olog
y18
19M
ater
ials
Tec
hnol
ogy
8270
Elec
tron
ics,
Mic
roel
ectr
onic
s26
33En
viro
nmen
tal P
rote
ctio
n28
24
Ren
ewab
le S
ourc
es o
f En
ergy
3218
Ren
ewab
le S
ourc
es o
f En
ergy
122
68Bi
otec
hnol
ogy
2729
Biot
echn
olog
y21
23
Med
icin
e, H
ealth
2116
Mea
sure
men
t M
etho
ds46
65Te
leco
mm
unic
atio
ns20
24Sa
fety
2222
Safe
ty14
14St
anda
rds
4463
Info
rmat
ion
Proc
essi
ng18
22R
enew
able
Sou
rces
of
Ener
gy39
22
Res
ourc
es o
f th
e Se
a, F
ishe
ries
00
Rad
iatio
n Pr
otec
tion
5356
Res
ourc
es o
f th
e Se
a, F
ishe
ries
1221
Med
icin
e, H
ealth
1914
Rad
iatio
n Pr
otec
tion
00
Safe
ty55
56A
gric
ultu
re15
20Fo
ssil
Fuel
s23
12
Agr
icul
ture
00
Envi
ronm
enta
l Pro
tect
ion
5143
Med
icin
e, H
ealth
00
Rad
iatio
n Pr
otec
tion
00
Coo
rdin
atio
n, C
oope
ratio
n16
20C
oord
inat
ion,
Coo
pera
tion
107
135
Coo
rdin
atio
n, C
oope
ratio
n31
39C
oord
inat
ion,
Coo
pera
tion
1215
Educ
atio
n, T
rain
ing
4449
Educ
atio
n, T
rain
ing
114
126
Educ
atio
n, T
rain
ing
1820
Educ
atio
n, T
rain
ing
3034
TRCA
-BELTR
CA -E
UR
TRCA
-BELTR
CA -E
UR
TRCA
-BELTR
CA -E
UR
TRCA
-BELTR
CA -E
UR
Not
es :
;
% =
per
cent
age
with
res
pect
to th
e to
tal n
umbe
r of
pro
ject
s ; C
% c
umul
ated
per
cent
age.
Whe
re i
= te
chno
logi
cal f
ield
and
j =
reg
ion,
the
sum
on
j ref
ers
to th
e Be
lgia
n (B
EL) a
nd th
e Eu
rope
an (E
UR)
are
as r
espe
ctiv
ely.
Dat
a so
urce
: Co
rdis
data
base
, UES
T-D
ULB
EA c
alcu
latio
ns.
TRC
A
=[
]ij
in ij n i
j∑
[]
i,jn i
j∑j
n ij
∑
7 0
RK FIRM NAME DISTRICT # OF PATENTS % C%
1 Agfa-Gevaert ANTWERP 1302 16.4 16.42 Solvay BRUSSELS 546 6.9 23.33 Janssen Pharmaceutica TURNHOUT 252 3.2 26.44 Picanol IEPER 168 2.1 28.55 Raychem LEUVEN 166 2.1 30.66 Bekaert KORTRIJK 159 2.0 32.67 Alcatel Bell ANTWERP 142 1.8 34.48 New Holland Belgium BRUGGE 137 1.7 36.29 Centre de Recherches Métallurgiques LIEGE 134 1.7 37.810 Fina Research CHARLEROI 119 1.5 39.311 Acec CHARLEROI 82 1.0 40.412 Imec Inter Universitair Micro-Electronica Centrum LEUVEN 81 1.0 41.413 Procter & Gamble European Technical Center HALLE-VILVOORDE 77 1.0 42.414 Monsanto Europe NIVELLES 69 0.9 43.215 Smithkline Beecham Biologicals NIVELLES 68 0.9 44.116 Bell Telephone Manufacturing Company ANTWERP 67 0.8 44.917 Pumptech ANTWERP 60 0.8 45.718 Cockerill Sambre LIEGE 58 0.7 46.419 G.B. Boucherie ROESELARE 53 0.7 47.120 Innogenetics GHENT 53 0.7 47.721 Sofitech ANTWERP 52 0.7 48.422 Dow Corning CHARLEROI 51 0.6 49.023 Ford New Holland BRUGGE 51 0.6 49.724 Plant Genetic Systems GHENT 51 0.6 50.325 Michel Van De Wiele KORTRIJK 49 0.6 50.926 UCB NIVELLES 49 0.6 51.627 Soremartec ARLON 48 0.6 52.228 Heraeus Electro-Nite International MAASEIK 47 0.6 52.829 Fabrique Nationale Herstal LIEGE 43 0.5 53.330 Katholieke Universiteit Leuven LEUVEN 42 0.5 53.831 Diamant Boart Stratabit BRUSSELS 34 0.4 54.232 Hamon-Sobelco BRUSSELS 32 0.4 54.733 Bayer Antwerpen ANTWERP 31 0.4 55.034 Staar BRUSSELS 30 0.4 55.435 La Région Wallonne NAMUR 29 0.4 55.836 Rega Stichting LEUVEN 28 0.4 56.137 Redco HALLE-VILVOORDE 27 0.3 56.538 Volvo Car Sint-Truiden HASSELT 26 0.3 56.839 Atlas Copco Airpower ANTWERP 24 0.3 57.140 Recticel BRUSSELS 24 0.3 57.441 Xeikon ANTWERP 24 0.3 57.742 Université Catholique de Louvain NIVELLES 23 0.3 58.043 Raffinerie Tirlemontoise BRUSSELS 21 0.3 58.344 Metallurgie Hoboken-Overpelt ANTWERP 20 0.3 58.545 Vlaamse Instelling Voor Technologisch Onderzoek (V.I.T.O.) TURNHOUT 20 0.3 58.846 Alcatel Bell-SDT CHARLEROI 16 0.2 59.047 International Institute of Cellular And Molecular Pathology BRUSSELS 16 0.2 59.248 Université Libre de Bruxelles BRUSSELS 16 0.2 59.449 Sidmar GHENT 15 0.2 59.650 Champion Spark Plug Europe THUIN 14 0.2 59.7
Table A.6.1.Top 50 firms by districts (EPO applications, 1978 - 1997)
Notes : Rk = rank ; % = percentage of the total number of patents ; C% cumulated percentage.Data source: EPO (1998), UEST-DULBEA calculations.
7 1
RK FIRM NAME DISTRICT # OF PATENTS % C%
1 Agfa-Gevaert ANTWERP 897 22.0 22.02 Solvay BRUSSELS 433 10.6 32.63 Janssen Pharmaceutica TURNHOUT 335 8.2 40.84 Bekaert KORTRIJK 127 3.1 43.95 Picanol IEPER 125 3.1 47.06 Glaverbel CHARLEROI 120 2.9 49.97 Raychem LEUVEN 98 2.4 52.38 Staar BRUSSELS 80 2.0 54.39 Centre de Recherche Métallurgiques LIEGE 77 1.9 56.210 Labofina CHARLEROI 69 1.7 57.911 UCB NIVELLES 58 1.4 59.312 Dow Corning CHARLEROI 42 1.0 60.313 Michel Van de Wiele KORTRIJK 42 1.0 61.314 Plant Genetic Systems GHENT 42 1.0 62.415 Metallurgie Hoboken Overpelt ANTWERP 36 0.9 63.316 Fabrique Nationale Herstal LIEGE 35 0.9 64.117 Stichting Rega LEUVEN 34 0.8 65.018 Confiserie Leonidas BRUSSELS 33 0.8 65.819 Firma G.B. Boucherie ROESELARE 33 0.8 66.620 Interuniversitair Micro Elektronica Centrum (IMEC) LEUVEN 33 0.8 67.421 Fina Research CHARLEROI 30 0.7 68.122 ACEC (Ateliers de Constructions Electriques de Charleroi) CHARLEROI 29 0.7 68.823 Monsanto Europe NIVELLES 29 0.7 69.524 Champion Spark Plug Europe HALLE-VILVOORDE 28 0.7 70.225 Cockerill Sambre LIEGE 25 0.6 70.826 Texaco Belgium BRUSSELS 25 0.6 71.427 Soremartec - Ferrero Ardennes ARLON 25 0.6 72.128 Leuven Research & Development LEUVEN 22 0.5 72.629 Smith Kline RIT NIVELLES 20 0.5 73.130 Diamant Boart Stratabit BRUSSELS 19 0.5 73.631 Hamon Sobelco BRUSSELS 18 0.4 74.032 Xeikon ANTWERP 18 0.4 74.433 Dresser Europe BRUSSELS 16 0.4 74.834 Heraeus Electro-Nite International ANTWERP 15 0.4 75.235 Recticel BRUSSELS 15 0.4 75.636 Centre d'Etude de l'Energie Nucleaire (C.E.N.) – BRUSSELS 14 0.3 75.9
Studiecentrum voor Kernenergie (S.C.K)37 Ire-Celltarg-Medgenix CHARLEROI 13 0.3 76.238 Electrochemische Energiecoersie (Elenco) TURNHOUT 12 0.3 76.539 Faco LIEGE 11 0.3 76.840 Klippan LEUVEN 11 0.3 77.141 Omnichem NIVELLES 11 0.3 77.342 PRB BRUSSELS 11 0.3 77.643 Innogenetics GHENT 10 0.2 77.844 International Sanitary Ware Manuf. OUDENAARDE 10 0.2 78.145 Sidmar GHENT 10 0.2 78.346 Atlas Copco Airpower ANTWERP 9 0.2 78.647 Compagnie Neerlandaise de l'Azote BRUSSELS 9 0.2 78.848 Continental Pharma BRUSSELS 9 0.2 79.049 Redco HALLE-VILVOORDE 9 0.2 79.250 Ateliers Houget Duesberg Bosson VERVIERS 8 0.2 79.4
Table A.6.2. Top 50 firms by districts (USPTO, 1978 - 1998)
Notes : Rk = rank ; % = percentage of the total number of patents ; C% cumulated percentage.Data source : USPTO (1999), UEST-DULBEA calculations.
7 2
Tabl
e A
.6.3
.M
ost i
mpo
rtan
t pat
ent c
lass
es (I
PC c
lass
ifica
tion)
and
tech
nolo
gica
l rev
eale
d co
mpa
rativ
e ad
vant
ages
(TRC
A) o
f Bel
gian
reg
ions
Not
es: R
k =
ran
king
, # =
num
ber
of p
aten
ts, %
= s
hare
of p
aten
ts in
IPC
clas
ses
with
res
pect
to r
egio
nal t
otal
pat
ents
, C%
= c
umul
ated
sha
re.
Dat
a so
urce
: EP
O (1
998)
, UES
T-D
ULB
EA c
alcu
latio
ns.
FLA
ND
ERS
WA
LLO
NIA
BRU
SSEL
S-C
API
TALE
Rk
IPC
CLA
SSES
#%
C%
TRC
AIP
CC
LASS
ES#
%C
%TR
CA
IPC
CLA
SSES
#%
C%
TRC
A
1G
03Ph
otog
raph
y83
617
.317
.31.
6C
08Ph
arm
aceu
tical
s12
36.
76.
71.
4C
08Ph
arm
aceu
tical
s19
415
.315
.33.
1
2A
01A
gric
ultu
re24
95.
222
.51.
3A
61M
edic
al s
cien
ce10
45.
612
.31.
2C
07O
rgan
ic c
hem
istr
y13
710
.826
.01.
9
3H
04Te
leco
mm
.24
35.
027
.51.
5C
07O
rgan
ic c
hem
istr
y88
4.8
17.1
0.8
A61
Med
ical
sci
ence
685.
431
.41.
2
4C
07O
rgan
ic c
hem
istr
y22
54.
732
.10.
8C
12Bi
oche
mis
try
874.
721
.81.
5C
01In
orga
nic
chem
istr
y65
5.1
36.5
4.6
5B4
1Pr
intin
g22
44.
636
.81.
6B6
5Pa
ckin
g75
4.1
25.9
1.2
B01
Phys
ical
and
che
mic
al
564.
440
.92.
2
proc
esse
s an
d ap
para
tus
6D
03W
eavi
ng
223
4.6
41.4
1.6
G01
Inst
rum
ents
744.
029
.91.
1B2
9Pl
astic
s44
3.5
44.4
1.6
7A
61M
edic
al s
cien
ce19
44.
045
.40.
9E0
4Bu
ildin
g60
3.3
33.2
1.4
G01
Inst
rum
ents
393.
147
.40.
9
8G
01In
stru
men
ts17
23.
649
.01.
0A
01A
gric
ultu
re58
3.2
36.3
0.8
B65
Pack
ing
372.
950
.40.
8
9B6
5Pa
ckin
g16
23.
452
.31.
0B2
2M
etal
lurg
y51
2.8
39.1
3.7
E04
Build
ing
332.
653
.01.
1
10C
12Bi
oche
mis
try
139
2.9
55.2
0.9
C21
Iron
462.
541
.62.
8G
11In
form
atio
n st
orag
e 31
2.4
55.4
4.0
11F1
6En
gine
erin
g11
02.
357
.51.
1H
01El
ectr
ic e
lem
ents
442.
444
.01.
2C
12Bi
oche
mis
try
292.
357
.70.
7
12H
01El
ectr
ic e
lem
ents
102
2.1
59.6
1.0
B01
Phys
ical
and
che
mic
al
402.
246
.21.
1C
25El
ectr
olyt
ic o
r el
ectr
opho
retic
29
2.3
60.0
2.3
proc
esse
s an
d ap
para
tus
proc
esse
s; a
ppar
atus
the
refo
r
13E0
4Bu
ildin
g94
1.9
61.5
0.8
F41
Wea
pons
402.
248
.34.
0F2
8H
eat
exch
ange
in g
ener
al28
2.2
62.2
4.7
14B2
9Pl
astic
s92
1.9
63.4
0.9
F16
Engi
neer
ing
372.
050
.41.
0E2
1Ea
rth
drill
ing;
min
ing
272.
164
.31.
4
15A
47Fu
rnitu
re;
dom
estic
84
1.7
65.2
1.0
B60
Vehi
cles
in g
ener
al36
2.0
52.3
1.3
A47
Furn
iture
; do
mes
tic a
pplia
nces
241.
966
.21.
1
appl
ianc
es
16C
11D
eter
gent
s; c
andl
es78
1.6
66.8
1.2
H02
Gen
erat
ion
of e
lect
ric
331.
854
.11.
2D
21Pa
per-
mak
ing;
pro
duct
ion
of
211.
767
.83.
9
pow
erce
llulo
se
17B6
0Ve
hicl
es in
gen
eral
761.
668
.41.
0A
47Fu
rnitu
re;
dom
estic
32
1.7
55.8
1.0
C23
Wor
king
or
trea
tmen
t of
met
als
191.
569
.31.
5
appl
ianc
es
18E2
1M
inin
g76
1.6
69.9
1.0
C09
Pain
ts32
1.7
57.6
1.1
A01
Agr
icul
ture
181.
470
.70.
3
19C
09Pa
ints
751.
671
.51.
0C
10Pe
trol
eum
, gas
and
32
1.7
59.3
3.1
F16
Engi
neer
ing
181.
472
.10.
7
coke
20H
02G
ener
atio
n of
ele
ctric
73
1.5
73.0
1.1
B29
Plas
tics
311.
761
.00.
8B3
2La
yere
d pr
oduc
ts16
1.3
73.4
2.4
pow
er
TO
TAL
4832
TO
TAL
1841
TO
TAL
1271
7 3
Tabl
e A
.6.4
. Te
chno
logi
cal p
roxi
miti
es b
etw
een
dist
ricts
and
reg
ions
‘(EP
O –
197
8 - 1
997)
Not
e : p
roxi
mity
inde
x pe
rfor
med
as
the
angu
lar
sepa
ratio
n be
twee
n th
e ve
ctor
s of
pat
ents
dist
ribut
ion
acro
ss IP
C te
chno
logi
cal f
ield
s.D
ata
sour
ce :
EPO
(199
8), U
EST-
DU
LBEA
cal
cula
tions
.
VEU
RN
E1
TUR
NH
OU
T0.
041
TON
GER
EN0.
190.
061
TIEL
T0.
100.
080.
221
SIN
T-N
IKLA
AS
0.04
0.03
0.19
0.10
1
RO
ESEL
AR
E0.
080.
030.
130.
120.
041
OU
DEN
AA
RD
E0.
090.
300.
340.
210.
100.
111
OO
STEN
DE
0.06
0.31
0.40
0.19
0.23
0.05
0.35
1
MEC
HEL
EN0.
170.
100.
350.
120.
130.
080.
150.
091
MA
ASE
IK0.
130.
100.
130.
660.
050.
030.
130.
190.
181
LEU
VEN
0.15
0.29
0.22
0.18
0.11
0.09
0.23
0.20
0.45
0.24
1
KO
RTR
IJK
0.15
0.06
0.35
0.37
0.09
0.15
0.31
0.16
0.20
0.17
0.16
1
IEPE
R0.
010.
010.
030.
230.
010.
080.
030.
020.
020.
040.
030.
731
HA
SSEL
T0.
080.
160.
370.
280.
150.
120.
320.
340.
330.
260.
420.
300.
051
HA
LLE-
VIL
VOO
RD
E0.
060.
100.
250.
110.
110.
060.
190.
110.
260.
140.
150.
220.
020.
271
GH
ENT
0.10
0.26
0.12
0.14
0.09
0.07
0.22
0.15
0.12
0.12
0.33
0.17
0.03
0.21
0.13
1
EEK
LO0.
210.
090.
140.
310.
060.
200.
130.
120.
050.
140.
130.
140.
040.
170.
100.
161
DIK
SMU
IDE
0.05
0.01
0.31
0.19
0.11
0.08
0.11
0.17
0.05
0.02
0.02
0.35
0.34
0.14
0.04
0.03
0.03
1
DEN
DER
MO
ND
E0.
220.
180.
400.
260.
100.
150.
600.
310.
260.
140.
150.
460.
140.
420.
270.
210.
160.
181
BRU
GG
E0.
160.
090.
050.
260.
060.
170.
050.
050.
050.
120.
090.
060.
030.
110.
070.
110.
940.
010.
041
AN
TWER
P0.
020.
050.
040.
050.
310.
020.
050.
100.
070.
060.
110.
060.
010.
070.
040.
060.
030.
010.
090.
02
1
AA
LST
0.11
0.43
0.40
0.18
0.12
0.10
0.57
0.45
0.25
0.09
0.20
0.30
0.04
0.43
0.21
0.25
0.16
0.11
0.58
0.04
0
.10
1
FLA
ND
ERS
0.11
0.31
0.19
0.25
0.36
0.15
0.23
0.25
0.23
0.21
0.35
0.34
0.23
0.28
0.23
0.28
0.27
0.12
0.28
0.25
0
.88
0.
30
1
BRU
SSEL
S0.
080.
620.
180.
200.
080.
090.
340.
260.
310.
180.
320.
230.
020.
310.
170.
300.
110.
050.
250.
09
0.1
2
0.56
0
.34
1
WA
LLO
NIA
0.21
0.48
0.33
0.37
0.16
0.14
0.50
0.39
0.46
0.37
0.52
0.38
0.05
0.50
0.31
0.55
0.32
0.08
0.50
0.27
0
.13
0.
60
0.4
5
0.75
1
BELG
IUM
0.15
0.46
0.25
0.31
0.33
0.16
0.35
0.32
0.33
0.27
0.44
0.38
0.19
0.38
0.27
0.39
0.30
0.12
0.36
0.27
0
.73
0.
47
0.9
4
0.62
0
.70
1
VEU
RNE
TURN
HO
UT
TON
GER
ENTI
ELT
SIN
T-N
IKLA
ASROES
ELAR
E
OU
DEN
AAR
DE
OO
STEN
DE
MEC
HEL
ENMA
ASEI
KLEU
VENKO
RTRI
JKIE
PERH
ASSE
LT
HAL
LA-V
ILVO
ORD
EG
HEN
TEE
KLO
DIK
SMU
IDE
DEN
DER
MO
ND
EBRU
GG
EANTW
ERP
AAL
STFLAN
DER
SBRU
SSEL
S
WAL
LON
IABELG
IUM
7 4
1/ Het Vlaams Innovatiesysteem: een nieuw statistisch beleidskader
1annex/ Theoretische en empirische bouwstenen van het ‘Vlaams Innovatie Systeem’
2/ Innovatiestrategieën bij Vlaamse industriële ondernemingen
3/ Octrooien in Vlaanderen: technologie bekeken vanuit een strategisch perspectief
deel 1: Octrooien als indicator van het technologiesysteem
4/ De impact van technologische innovaties op jobcreatie en jobdestructie in Vlaanderen
5/ Strategische verschillen tussen innovatieve KMO’s : Een kijkje in de zwarte doos
6/ Octrooien in Vlaanderen: technologie bekeken vanuit een strategisch perspectief
deel 2: Analyse van het technologielandschap in Vlaanderen
7/ Diffusie van belichaamde technologie in Vlaanderen: een empirisch onderzoek op basis van input/outputgegevens
7 annex/ Methodologische achtergronden bij het empirisch onderzoek naar de Vlaamse technologiediffusie
8/ Schept het innovatiebeleid werkgelegenheid?
9/ Samenwerking in O&O tussen actoren van het “VINS”
10/ Octrooien in Vlaanderen: technologie bekeken vanuit een strategisch perspectief
deel 3: De internationale technologiepositie van Vlaanderen aan de hand van octrooiposities
deel 4: Sporadische en frequent octrooierende ondernemingen : profielen
11/ Technologiediffusie in Vlaanderen. Enquêteresultaten - Product- en diensteninnovatie : evolutie 1992-1994-1997
12/ Technologiediffusie in Vlaanderen. Enquêteresultaten - Hoogtechnologische producten : evolutie 1992-1994-1997
13/ Technologiediffusie in Vlaanderen. Enquêteresultaten - Procesautomatisering : evolutie 1992-1994-1997
14/ Technologiediffusie in Vlaanderen. Methodologie en vragenlijst
15/ Financiering van innovatie in Vlaanderen. Het aanbod van risicokapitaal.
16/ Product- en diensteninnovativiteit van Vlaamse ondernemingen. Enquêteresultaten 1997
17/ Adoptie van procesautomatisering en informatie- en communicatietechnologie in Vlaanderen. Enquêteresultaten 1997
18/ Performantieprofiel en typologie van innoverende bedrijven in Vlaanderen.
Waarin verschillen innoverende bedrijven van niet-innoverende bedrijven. Enquêteresultaten 1997
19/ De werkgelegenheidsimpact van innovatie: is de aard van de innovatie-strategie belangrijk?
20/ Samenwerking in O&O tussen actoren van het “VINS”
deel 2: Samenwerking in een aantal specifieke technologische disciplines
RR ee ee dd ss vv ee rr ss cc hh ee nn ee nnReeds verschenen bij het IWT-observatorium (voorheen VTO) :
7 5
RR ee ee dd ss vv ee rr ss cc hh ee nn ee nnReeds verschenen bij het IWT-observatorium :
21/ Clusterbeleid: Een innovatie instrument voor Vlaanderen?
Reflecties op basis van een analyse van de automobielsector
22/ Benchmarken en meten van innovatie in KMO’s
23/ Samenwerkingsverbanden in O&O en kennisdiffusie
24/ Financiering van innovatie in Vlaanderen. De venture capital sector in internationaal perspectief
25/ De O&O-inspanningen van de bedrijven in Vlaanderen - De regionale uitsplitsing van de O&O-uitgaven en
O&O-tewerkstelling in België 1971-1989
26/ De O&O-inspanningen van de bedrijven in Vlaanderen - Een perspectief vanuit de enquête voor 1996-1997
27/ Identificatie van techno-economische clusters in Vlaanderen op basis van input-outputgegevens voor 1995
28/ The Flemish Innovation System : an external viewpoint
Henri Capron
Henri Capron is professor at the Université Libre de Bruxelles. He is affiliated to DULBEAand is head of the Spatial Economics and Technology Unit. He has a business and man-agement engineering degree, a master degree in econometrics and a Ph.D. inEconomics. His current work focuses on regional development strategies and evaluation,technology policies and the economics of innovation. His publications are mainly con-centrated in these fields. He is currently involved in studies and expertises for regional,national and European institutions.
Michele Cincera
Michele Cincera is affiliated to DULBEA and the Spatial Economics and Technology Unitat the Université Libre de Bruxelles since 1993. After his master in Econometrics in 1995,he has carried out a Ph.D thesis entitled « Technological and Economic performances ofInternational firms ». He has also held visiting positions at Berkeley university and CREST-INSEE in Paris. Since 1998, he is a lecturer at the department of Economics at ULB andat Solvay business school. His research interests embrace the quantitative assessment ofinnovative activities and outcomes of Belgian and international companies as well as thestudy of National Innovation Systems.
Biography
Wat
is h
et
W a t i s h e t
Het Vlaams Instituut voor de Bevordering van het Wetenschappelijk-Technologisch
Onderzoek in de Industrie (IWT) is een autonome overheidsinstelling, opgericht in 1991
door de Vlaamse regering, voor de ondersteuning van de industriële O&O in Vlaanderen.
Hiervoor beschikt het IWT over verschillende financieringsinstrumenten waarmee jaarlijks
een 4 mld BF financiële steun wordt verleend.
Daarnaast is er ook dienstverlening aan de Vlaamse bedrijven op het gebied van
technologietransfert, partner search, voorbereiding van projecten in Europese program-
ma’s, enz....
Mede door deze activiteiten bouwt het IWT zich uit tot een kenniscentrum inzake O&O
en innovatie in Vlaanderen.
Het Innovatie-Wetenschap-Technologie (IWT) Observatorium is een
afdeling van het IWT gericht op beleidsondersteuning d.m.v. beleids-
indicatoren en beleidsstudies. Het IWT-Observatorium organiseert tech-
nologie-enquêtes en verzamelt indicatoren over O&O- en innovatie-
inspanningen van de bedrijven in Vlaanderen.
De belangrijkste opdracht van het IWT-Observatorium is echter de
organisatie van innovatiestudies, met steun van externe onderzoeks-
groepen, voor de verdieping van de kennis over het Vlaams
Innovatiesysteem, bench-marking met buitenlandse (beleids)ervaring,
introductie van nieuwe inzichten uit de innovatietheorie, ontsluiting van
de gegevens van gespecialiseerde enquêtes en databanken.
Tot eind 1998 stond het IWT-Observatorium bekend onder de naam
Vlaams Technologie Observatorium (VTO).