Clusters and competitiveness - PRO INNO Europe

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2. Clusters as building blocks of a modern economy 2.1 Clusters and economic performance Marshall’s (1890) originalobservationthatfirmscanenjoybenefitsfromlocatingclose toothers engaged in related activities continues to find empirical support, in advanced as wellasindevelopingcountries.Itiswidelyarguedthatthebenefitshavethreemain sources:First,thereisthepotentialtoattractmorespecializedsuppliersandinteract withthem more efficiently (Amiti/Cameron, 2007). Second, there is a labor market that is deeper and provides more specialized skills. And third, there are knowledge spillovers throughdifferentchannelsthatonecanonlytapintolocally(Thompson,2006).Thereis significant empirical evidence for each of these sources to matter (Ellison/Glaeser/Kerr, 2007) withtheirrelativeweightsdrivenbycluster-specificfactors.Inbiotechnology, for example, knowledge spillovers are found to be especially important (Aharonson et al., 2007)whileinotherareastheaccesstoaspecializedlabormarketisseenascrucial (Eriksson/Lindgren, 2008). But therearecountervailingeffectsthatholdtheunfetteredpushtowardsco-locationin check. Companies are in business to make a profit when serving customers and if the costs ofservingcustomersfromadistancearetoohigh,itcanbemorebeneficialtofollowthem insteadofstayingwithrelatedcompaniesinacluster.Andcompaniesneedtolookatthe costsidetoo:Morecompaniesclosebyleadstomorecompetitionforemployees,dedicated infrastructure, and other input factors. Again, there is clear evidence that these factors matter aswell,especiallyatthelevelofnarrowindustries(Braunerhjelm/Thulin,2009; Delgado/Porter/Scott, 2008). The tendency of economic activities to co-locate depends on the specific balance between these opposing forces. On the level of national economies, between 30%and40%ofallemploymenttendstobeinindustriesthatco-locateacross regions(U.S.ClusterMappingProject,2008;EuropeanClusterObservatory,2008).The restislargelyinactivitiesthatservelocalmarketswithoutanyeffectivecompetitionfrom companieslocatedelsewhere.Asmallshareofemployeesisinactivitiesthathavetobe where specific natural resource deposits can be found. While thesizeoftheclustersectorislargelyareflectionofbroadpatternsineconomic composition at the national level, especially the degree of service-orientation the economy hasreached,thelevelofspecializationwithintheclustersectorturnsouttobeanimportant driver of economic performance. This should come as no surprise: Being in an industry that ispartoftheclustersectorindicatesthattherearesignificantbenefitsfromco-location.If aregionhasalowerlevelofspecializationinsuchanindustry,productivityinthisindustry willbelower. If a region has much of its employment in the cluster sector spread out across many industries rather than being concentrated in a few industries where it can benefit from agglomeration, its overall level of productivity and ultimately its prosperity will suffer. The evidence from quantitative studies across many countries and regions clearly bears out this positive relationship between employment in strong clusters and economic performance. Data from Europe and North America indicates that differences in the strength of clusterspecializationexplainonaveragearoundonethirdofthedifferenceinGDPper 130 CLUSTERS AND COMPETITIVENESS: THE CASE OF CATALONIA (1993-2010)
capita levelsacrossthetwogeographies(EuropeanCommission,2007;Porter,2003).The moredetailedUSdataalsoshowsthatdifferencesinspecializationareassociatedwith differences in relative wages across locations within each industry. This industry-level wage effectisonaveragetwiceasimportantastheclustercompositionofaregionaleconomyin explainingdifferencesinaverageGDPpercapita.USdataalsosuggeststhatstrongclusters receivemoreforeigndirectinvestment (Bobonis/Shatz, 2007). While none of these studies provecausality,theyareindicativeofthecloserelationshipbetweenclustersandeconomic outcomes. Figure 37. Cluster Portfolio Strength and Regional Prosperity NUTS 2 Regions in European Countries GDP per Capita (PPP adjusted), 2004 70,000 € 60,000 € 50,000 € 40,000 € 30,000 € 20,000 € 10,000 € 0% 10% 20% 30% 40% 50% 60% 70% 80% Share of Employees in Strong Clusters, 2005 Note: Strong clusters defined by LQ>2, NUTS Regions the EU-15 countries excluding Portugal and Greece. Source: European Cluster Observatory. ISC/CSC cluster codes 1.0, data set 20070510. Specialization inclustersisclearlynottheonlydriverofregionalprosperity.Intermsof locational factors, the pure size of economic activity is another candidate suggested in the literature. There are two varieties of this argument. One approach argues that cross-cluster spillovers aremoreimportantthanwithin-clusterspillovers,sothatabsolutesizeand density instead of relative specialization matter most (Bruelhart/Sbergami, 2008). Another approach goesfurtherandarguesthatabsolutesizeallowsforheterogeneity,i.e.the absence of specialization, and that this heterogeneity is critical for ’creativity’ (Florida, 2003; Jacobs,1961).Bothofthesemodelssuggesttheemergenceofaveryunequalworld,i.e.a fewprosperouslargeregions(core)andmanypoorsmallregions(periphery).Thecluster modelinsteadisconsistentwithaworldwhereallregionsofsimilarfundamentalscan reach similar levels of size and prosperity if they develop different specialization patterns. In terms of other influences, the competitiveness framework points towards the more general economic fundamentals given in the quality of the business environment and the sophistication ofcompanies(Porter,1990).Clusters,thisapproachsuggests,canamplify the strengths that the fundamentals provide but they are dependent on them and cannot substitute their weaknesses. ANNEX: CLUSTERS AND COMPETITIVENESS: FLORENCE, BOSTON, BARCELONA 131
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Clusters and competitiveness: the c
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Hernández Gascón, Joan Miquel Clu
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Acknowledgements Verymanypeople,com
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Index of tables Table 1. The local
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Figure 31. Textile distribution tre
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The term “cluster” is used to r
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The last effect of the new focus, a
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Figure 11. Map of the local industr
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Figure 14. Joint work scheme of the
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Figure 16. Main competitiveness rei
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Figure 33. The change in project de
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Catalonia was a pioneer in the use
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Cluster policy, understood as a ser
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A little theory: Marshall, Becattin
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However, the proliferation of regio
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the diversity of clusters themselve
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The first step: the competitive adv
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political environment which conditi
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Figure 2. The clusters of the futur
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1. To invest in lasting long-term c
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4.1 Introduction Following the impa
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4.2 First stage: 1993-2004 4.2.1 Me
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This working method led the members
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4.2.2 A case study: the leather tan
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added to this industry’s strong d
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Figure 9. Comparison between the pr
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Within this framework, Igualada’s
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4.2.3 Some lessons More than twenty
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Finally, and with the aim of transm
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the initial stage was selected, eli
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Table 1. The local production syste
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Table 3. Relative importance of ind
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2. Analysis of the business and str
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It should be noted that, during the
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Table 4. Types of competitiveness r
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Figure 18. Basic data for the kitch
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2. Specialised firms: normally fore
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Figure 22. Main strategic challenge
Page 82 and 83: Main actions carried out in the kit
Page 84 and 85: On the one hand, this change in men
Page 86 and 87: In 2009 the Catalan government’s
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Page 90 and 91: countries in the 1990s. However, th
Page 92 and 93: For this reason, one of the most re
Page 94 and 95: total in 2005 was 66.7%; in the Bas
Page 96 and 97: Table 6.Trends in value added by la
Page 98 and 99: There was a considerable amount of
Page 100 and 101: With regard to strategies, the anal
Page 102 and 103: Table 7. Professional profiles of e
Page 104 and 105: In terms of the positive results ac
Page 106 and 107: In 2009, after over fifteen years
Page 108 and 109: Figure 33. The change in project de
Page 110 and 111: implementing the subsequent actions
Page 112 and 113: At the same time, the Directorate G
Page 114 and 115: Cluster policy, understood as a ser
Page 116 and 117: entirely to this topic. This centre
Page 118 and 119: It hasalreadybeenmentionedthatclust
Page 120 and 121: 2. Some rationale for territorial s
Page 122 and 123: Twomainreasonsjustifythispeculiarro
Page 124 and 125: of the specific interventions to re
Page 126 and 127: Sincethesenewpoliciesarestillinthei
Page 128 and 129: 7. References Altobelli, C.andCarna
Page 130 and 131: Schmitz, H. (1999): “Collective e
Page 134 and 135: Anumberofempiricalstudieslookatallt
Page 136 and 137: and othercompaniesthatturnintoaclus
Page 138 and 139: Thelackofagenerallyaccepteddefiniti
Page 140 and 141: aswellassupportersofclusterpolicy(a
Page 142 and 143: 3.3 Implementing cluster policy to
Page 144 and 145: as a way to leverage existing agglo
Page 146 and 147: Boekholt, Patrice and Shonie McKibb
Page 148 and 149: Fritsch, Michael and Viktor Slavtch
Page 150 and 151: Porter, Michael E.: Clusters and Co
Page 152 and 153: C. Clusters: a strategic tool Anton
Page 154 and 155: The other characteristic of our pro
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Page 158 and 159: • Gaining insight into a country
Page 160 and 161: Diez, M. A. (2001): “The Evaluati
Page 164: Joan Miquel Hernández Gascón (Val
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