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INDIVIDUALS
CLUSTERS ARE
NEW FINDINGS FROM THE EUROPEAN CLUSTER MAN-
AGEMENT AND CLUSTER PROGRAM BENCHMARKING
VOL. II 2012
UPDATED REPORT
CLUSTERS ARE INDIVIDUALS
COLOPHON
AUTHORS:
Lysann Mü ller
Thomas Lämmer-Gamp
Gerd Meier zu Kôcker
Thoma s Alslev Christensen
October 2012
PUBLISHED BY:
The Danish Ministr y of Science
Innovation and High er Education
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IMPRESSION: 10 00
WEB: 978-87-92776-21-1
PRIN T: 978-87-92776 -2 2-8
INDIVIDUALS
CLUSTERS ARE
NEW FINDINGS FROM THE EUROPEAN CLUSTER MAN-
AGEMENT AND CLUSTER PROGRAM BENCHMARKING
VOL. II 2012
UPDATED REPORT
UPDATE 2012
IMPRINT
VDI/VDE Innovation + Technik GmbH (VDI/VDE-IT)
Steinplatz 1
10623 Berlin/Germany
www.vdivde-it.de
Dr. Gerd Meier zu Köcker
Head of Department „International Technology Cooperation and Clusters“
mzk@vdivde-it.de
The project was initiated by the Danish Ministry of Science, Technology and Innovation.
It was carried out by VDI/VDE Innovation + Technik GmbH on behalf of the Danish Ministry for
Science, Technology and Innovation.
© VDI/VDE Innovation + Technik GmbH (VDI/VDE-IT), Berlin, October 2012
TABLE OF CONTENTS
EXECUTIVE SUMMARY 10
1 RESULTS OF THE BENCHMARKING OF CLUSTER MANAGEMENT ORGANIZATIONS 11
1.1 Comparative Portfolio 11
1.2 General Characteristics of Cluster Management Organizations and their Clusters 14
1.2.1 Age of the Cluster Management Organization 14
1.2.2 Size of Clusters 16
1.2.3 Composition of the Clusters 18
1.2.4 Regional Concentration of Clusters 18
1.2.5 Financing of Cluster Management Organizations (Share of Public Funding in Total Budget) 20
1.3 What Makes the Difference? .............................................................................................................................22
1.3.1 Differences between Research-driven and Industry-driven clusters 22
1.3.2 Sources of Funding 24
1.3.3 Relevance of Specific Determinants 25
1.3.4 Effect of the Cluster’s Technology Field 29
1.3.5 Link between Services and SME Development 30
1.4 Excellent Cluster Management Organizations - What are their Distinctive Characteristics? 31
1.5 What Makes the Difference? Some Key Findings 36
1.6 Key Determinants for the Impact of a Cluster on Business Activities of Cluster Members....37
2 RESULTS OF THE BENCHMARKING OF CLUSTER PROGRAMS 39
2.1 Comparative Portfolio 40
2.2 Characteristics of Cluster Programs 43
2.2.1 Overall Objectives of the Cluster Programs 43
2.2.2 Strategic Focus: Establishment of New Clusters or Support of Matured Clusters 46
2.2.3 Strategic Objectives in Terms of Numbers of Clusters 49
2.2.6 Technical Details: Term and Financial Aspects of Cluster Programs 56
2.3 Key Findings ...........................................................................................................................................................57
2.3.1 Different types of cluster programs serve different purposes 57
2.3.2 Most cluster programs feature high on the government’s agenda 59
2.3.3 Coordination with other funding programs shows room for improvement 60
2.3.4 Internationalization of clusters is considered to be important, but the relevance of supporting
internationalization of clusters varies between the different programs 64
2.3.5 Program owners take over a more active role towards developing individual clusters 68
2.3.6 Cluster management excellence has become more and more important in recent years 69
2.3.7 Monitoring and evaluation is important, but difficult 69
2.3.8 Cluster policy has become more important with the EU enlargement 71
2.3.9 The European Regional Development Fund approach has led to good linkages between innovation
support programs and cluster programs 72
2.3.10 Independent from the kind of support they provide the cluster programs are equally integrated
in national policies 73
2.3.11The cluster programs’ strategic focus of either launching new clusters or supporting matured ones
towards excellence is equally integrated in the policy agendas of the EU Member States 74
2.3.12 The budget provided for cluster programs is independent from the gross domestic product p.c. of
the respective country 75
2.4 Lessons Learned and the Impact on Program Development 76
3 POLICY RECOMMENDATIONS 78
THE AUTHORS 80
Table 1: Abbreviations for the cluster programs benchmarked in this study 8
Table 2: Benchmarked clusters per country and technology area 12
Table 3: Number of research-driven and industry-driven clusters and number of those clusters that
are both driven by industry and research 24
Table 4: Number of clusters of the excellence portfolio per specific technology area 32
Table 5: Excellence indictors of the European Cluster Excellence Initiative (ECEI) 33
Table 6: Services of cluster management organizations 36
Table 7: Overview of cluster programs 41
Table 8: Overall objectives of the cluster programs 43
Table 9: Strategic Focus: Creation of new or support of existing cluster management organizations? 47
Table 10: Strategic objectives of cluster programs 49
Table 11: Strategic approach: top-down or bottom-up 52
Table 12: Instruments of cluster programs 54
Table 13: Term of cluster programs and financial aspects 56
Table 14: Overview of key findings 57
Table 15: Different categories of cluster programs 58
Table 16: Relevance of the support of international activities of clusters 64
Table 17: Instruments that are used to support international activities of clusters 65
Table 18: Lessons learned with regard to the program strategy 77
Table 19: Lessons learned with regard to the instrumentation of the program 77
INDEX OF TABLES
Figure 1: Participating countries 11
Figure 2: Year of establishment of the cluster management organization 15
Figure 3: Size of the clusters (total number of committed cluster participants) 17
Figure 4: Composition of clusters 18
Figure 5: Regional concentration of clusters 19
Figure 6: Share of public funds in total budget of cluster management organisations 21
Figure 7: Comparison of R&D- and industry-driven clusters in terms of structural factors 22
Figure 8: Comparison of R&D- and industry-driven clusters in terms of effects on cluster participants 23
Figure 9: Characteristics of clusters with a small or high share of public funding 25
Figure 10: Relevance of size and age for the effect on cluster participants 26
Figure 11: Relevance of size and age for the level of institutionalisation of the cluster 27
Figure 12: Characteristics of cluster with a high effect on business activities of SME 28
Figure 13: Structural characteristics of clusters in different technology areas 29
Figure 14: Effects and private funding of clusters in different technology areas 30
Figure 15: Effect of Spectrum and Intensity of Services on Business Activities of SME 31
Figure 16: Comparison of structural characteristics of excellent and non-excellent clusters 35
Figure 17: Comparison of effects created by excellent and non-excellent clusters 36
Figure 18: Key determinants for impact on business activities of cluster members 37
Figure 19: Participating countries 40
Figure 20: How important is the cluster program in relation to the overall national or regional
economic/industrial development strategy? 60
Figure 21: Coordination of cluster programs with other business development programs 61
Figure 22: Coordination of cluster programs with infrastructure programs (e.g. support of universities
and other educational institutions) 62
Figure 23: Coordination of cluster programs with other R&D/innovation support programs 63
INDEX OF FIGURES
Figure 24: Importance of cluster programs in relation to the overall national or regional economic /
industrial development strategy 71
Figure 25: Comparison of “older” and “younger” cluster programs with regard to the specific economic
environment, and R&D strategy as well as other funding programs 72
Figure 26: Embedment of cluster programs in the overall economic development and R&D strategy
with regard to the GDP of the respective country 73
Figure 27: Comparison of cluster programs that provide funding only and cluster programs that
provide funding and technical assistance 74
Figure 28: Comparison of cluster programs that focus exclusively on the establishment of new cluster
organization and cluster programs that focus exclusively on the further development of
already existing cluster organizations 75
Figure 29: Estimated yearly budget of the cluster programs (in Million €), (Cluster programs of
countries below EU GDP average are marked yellow. Cluster programs of countries above
EU GDP average are marked green.) 76
Box 1: Explanation of figures used to present the results of the benchmarking 13
Box 2: Overview services of cluster management organizations 38
INDEX OF BOXES
Table 1: Abbreviations for the cluster programs benchmarked in this study
ABBREVIATIONS OF CLUSTER PROGRAMS USED IN THE FIGURES
COUNTRY NAME OF PROGRAM ABBREVIATION
AUSTRIA Cluster Program Lower Austria Lower Austria
BELGIUM Competence Centres-Light Structures Belg LS
Cooperative innovation network integrated project Belg VIS
CZECH REPUBLIC Cooperation–Clusters CZ
DENMARK Innovation Networks Denmark (Innovationsnetværk Denmark) IND
ESTONIA Cluster Development Program EST
FINLAND Centre of Expertise Program (OSKE, Osaamiskeskusohjelma) OSKE
Strategic Centres for Science, Technology and Innovation
(SHOK, Strategisen huippuosaamisen keskittymät) SHOK
FRANCE Grappe d’entreprises Grappe
Les Pôles de Compétitivité PdC
GERMANY Competence Networks Germany (Initiative Kompetenznetze
Deutschland) (expired) KOM
Go-Cluster Initiative Go Cluster
Clusterpolitische Gesamtstrategie der Freien und Hansestadt
Hamburg (Cluster Policy Strategy of the Free and Hanseatic
City of Hamburg)
HH
Cluster Offensive Bayern (Bavarian Cluster Initiative) COB
Zentrales Innovationsprogramm Mittelstand – Fördermodul
Netzwerkprojekte (ZIM NEMO) (Central Innovation Program
SME – Funding Module Network Projects)
ZIM
HUNGARY Cluster Development Program of the New Széchenyi Plan HU
ICELAND Strategic Research Program for Centres of Excellence
and Research Clusters (The Icelandic Centre for Research
(Rannsóknamiðstöð ĺslands))
RANNIS
Regional Growth Agreements (Vaxtarsamningur) VAX
ITALY Innovation Clusters Piedmont Piedmont
LATVIA Cluster Program LAT
LITHUANIA InnoCluster LT LT
InnoCluster LT+ LT+
LUXEMBOURG Luxembourg Cluster Initiative Lux
NORWAY Norwegian Centres of Expertise (NCE) NCE
Arena Program (Arena-programt) ARENA
POLAND Polish Cluster Support Schemes: Support for the development
of Supra-Regional Clusters and Cluster Creation in Eastern
Poland
POL
PORTUGAL Portuguese Operational Competitiveness Program - COMPETE Compete
ROMANIA Development of business support infrastructures of national
and international interest (Competitiveness Poles) CP, RO
Support to the integration of SMEs in value chains and clusters
(Clusters) Clusters, RO
SERBIA Serbian Cluster Development Support Program Serbia
SLOVAKIA Support to innovative industrial cluster organizations SK
SPAIN Cluster Development Catalonia Spain Cat
SWEDEN Vinnväxt VINN
TURKEY Support for the Improvement of International Competitiveness
(UR-GE) URGE, TR
UNITED KINGDOM Knowledge Transfer Networks KTN
10
In economic and innovation policy the term „cluster“ is
usually used to explain geographical concentrations of eco-
nomic and innovation activities. According to conventional
wisdom clusters support economic development through
the specialization of regions in activities within which
companies gain higher productivity through accessing
external economies of scale or other comparative advan-
tages. During the past 15 years clusters and innovative
(competence) networks have gained more and more impor-
tance as an element of economic development and inno-
vation strategies of the European Union and its Member
States. The analyses in this report challenge conventional
wisdom of what drives development and innovation within
a cluster. Based on the largest international analysis of its
kind involving a simultaneous benchmarking of more than
260 cluster organizations and of cluster policies from 23
European countries it is found that the economic impacts
of clusters depend on many more factors not related to the
specialization of regions through the geographical concen-
tration of the cluster than earlier research suggests. Cluster
management excellence and the spectrum and frequency
of business-related services of the cluster organization are
important determinants for the impact of a cluster. The
analyses of cluster organizations and cluster policies also
show many other key determinants for the development
and characteristics of a cluster such as internationalization
activities, R&D activities, age, technology areas.
The overall objective is to contribute to the development of
outstanding clusters through excellent management and
excellent cluster programs. Conducted from October 2010
to September 2012 the project pays particular attention
on the characteristics of cluster management organizati-
ons and their eects on cluster development. More than
260 cluster management organizations from 16 countries
were benchmarked to base the analysis on a comprehen-
sive comparative portfolio. 34 cluster programs from 24
countries supporting most of the analyzed cluster organi-
zations were analyzed to facilitate a better understanding
of successful strategies and mutual learning between the
program owners and to develop recommendations for a
“perfect” cluster program.
The Danish Ministry of Science, Technology and Innovation
has initiated this project. The analyses were carried out by
VDI/VDE Innovation + Technik GmbH. Invaluable support
was given by the country experts of the benchmarked clu-
sters and cluster programs in this report.
EXECUTIVE SUMMARY
11
In order to understand the characteristics of cluster ma-
nagement organizations and their interaction with cluster
stakeholders in more detail, 261 cluster management orga-
nizations have been benchmarked since November 2010.
The results provide a detailed insight into cluster manage-
ment organizations and clusters in terms of the structure of
the cluster, cluster management and governance, nancing,
services provided by the cluster management organization
and achievements and recognition of the cluster manage-
ment organization.
This chapter presents the results of the benchmarking of
cluster management organizations. The comparative portfo-
lio is explained in chapter 1.1, while chapter 1.2 introduces
the ndings of the benchmarking in terms of the general
characteristics of cluster management organizations and
clusters. Chapter 1.3 analyses dierences between cluster
management organizations and clusters. Chapter 1.4 gives
an insight into excellent cluster management organizations,
while chapter 1.5 presents key determinants that decide
about the eect a cluster on business activities of cluster
participants.
1.1 COMPARATIVE PORTFOLIO
The comparative portfolio includes 261 cluster manage-
ment organizations from 17 countries (see Figure 1) co-
vering a broad range of technology areas respectively
industries (see Table 2).
1 RESULTS OF THE BENCHMARKING OF CLUSTER
MANAGEMENT ORGANIZATIONS
Figure 1: Participating countries
Iceland 4
Norway 16
Germany 74
Belgium 1
Austria 6
India 1
Latvia 2
Poland 20
France 73
Greece 1
Spain 6
Portugal 3
Sweden 11
Finland 11
12
Table 2: Benchmarked clusters per country and technology area
TECHNOLOGY
AREAS
Aviation and space
Biotechnology
Construction/building sector
Energy and environment
Food industry (non-biotech)
Health and medical science
Humanities/social sciences, media,
design, service innovation
Information and communication
Micro, nano and optical
technologies
New Materials and chemistry
Production and engineering
Transportation and mobility
TOTAL
COUNTRIES
AUS 1 1 1 1 2 6
BEL 1 1
DNK 1 1 1 4 2 2 5 5 1 2 3 3 30
ESP 1 1 1 1 1 1 6
EST 1 1
FIN 3 2 1 2 1 2 11
FRA 3 2 1 15 10 6 3 8 5 11 4 5 73
GER 2 10 7 5 5 3 13 10 6 8 5 74
GRC 1 1
IND 11
IRL 1 1
ISL 2 1 1 4
LVA 1 1 2
NOR 2 1 2 2 1 2 1 5 16
POL 2 2 4 2 3 3 1 1 1 1 20
PRT 2 1 3
SWE 2 2 1 1 2 1 1 1 11
TOTAL 8 16 5 41 24 19 19 40 22 24 27 16 261
13
Boxplot
A boxplot presents the minimal and maximal values as well as the median of the results. The median is a numerical value separating
the higher half of a sample from the lower half. The lower quartile covers the lowest 25 per cent and the upper quartile covers the
lowest 75 per cent of the data. The difference between the upper and lower quartiles is called the interquartile range. It
represents 50 per cent of the data.
Radar Chart
A radar chart is a graphical method of displaying multivariate data in the form of a two-dimensional chart of quantitative variables
represented on axes starting from the same point. In the following example the data of the benchmarked cluster is indicated by a
green line and compared to the data of the clusters in its specific technology area (orange line) and all technology areas (blue line).
Box 1: Explanation of figures used to present the results of the benchmarking
Box 1: Explanation of figures used to present the results of the benchmarking
100%
80%
60%
40%
20%
0%
Regional
International National
Total Cluster XYZ Technology area
Minimum Value
Lower Quartile Upper Quartile
Maximum Value
Interquartile range
Minimum Value
Lower Quartile Upper Quartile
Maximum Value
Interquartile range
25 percent of all values
Total:
all clusters in all
technology areas
75 percent of all values
50 percent of all values
Cluster XYZ Median
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
14
1.2 GENERAL CHARACTERISTICS OF CLUSTER
MANAGEMENT ORGANIZATIONS AND THEIR
CLUSTERS
This chapter provides an overview of the general charac-
teristics of cluster management organizations and their
clusters for each country1. The overview includes data on
• Theageofclustermanagementorganizations,
• Thesizeofclusters,
• Thecompositionofclusters,
• Theregionalconcentrationofclustersand
• Financingofclustermanagementorganizations.
1.2.1 AGE OF THE CLUSTER MANAGEMENT ORGANIZATION
The establishment of the majority of cluster management
organizations started in Austria, Germany and Finland alrea-
dy at the end of the 1990s followed by Denmark, France,
Norway, Sweden, Spain Poland and Iceland (see Figure 2).
This pattern reects the history of cluster policy in many
of these countries. While, for example, cluster policy in
Germany started in the mid-1990s resulting in a number of
support programs both from the federal and regional level,
in other countries cluster policy developed rather late at
the beginning of the 2000s, like in Sweden, or even later,
like in Iceland. As the majority of benchmarked cluster ma-
nagement organizations in their early phases relied heavily
on public funding there is a clear correlation between the
establishment and the inception of funding programs.
An interesting observation concerns the length of cluster
institutionalization processes. While the majority of clusters
in Germany were established during an eight-year period
between 1998 and 2006, and in Finland between 1999 and
2007, this process was much shorter in other countries, e.g.
in Poland just two years (2006 to 2008) or in Sweden just
one year (2005). As this pattern cannot be explained by the
inuence of funding programs (e.g. through the publishing
date of call for proposals) only – except for France where
the Pôles de compétitivité program was launched in 2005
-, it is most likely that other dynamics such as specic deve-
lopments in individual industries also had an eect on the
date of establishment.
1 In order to get meaningful results the analysis includes only countries with more than four benchmarked clusters.
15
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010
AUSTRIA
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010
DENMARK
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010
FINLAND
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010
FRANCE
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010
GERMANY
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010
ICELAND
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010
NORWAY
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010
POLAND
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010
SPAIN
SWEDEN
Figure 2: Year of establishment of the cluster management organization
16
1.2.2 SIZE OF CLUSTERS
For the purpose of this project the size of clusters was
measured in terms of numbers of cluster participants who
are committed to the work of the cluster management
organization. A committed cluster participant is a company,
R&D institution etc. who meets at least one of the following
criteria:
• Theclusterparticipanthassignedamembershipagree-
ment, a letter of intent or a similar form of written com-
mitment;
• Theclusterparticipantpaysmembershipfeeorprovides
nancial support to the cluster management on a regular
basis (this may also include inkind contributions or sta
working time);
• Theclusterparticipantcontributesactivelytothedeve-
lopment of the cluster on a regular basis, e.g. through the
participation in projects, workshops or working groups.
Figure 3 presents the composition of clusters in terms of
total number of committed cluster participants. The total
number includes participants from the following categories:
SME2 , Non-SME, R&D institutions, universities, training and
education providers, nancial intermediaries, consultants,
governmental agencies and others. The size of a cluster
does not correlate with its business and innovation potenti-
al or its utilization: it is the quality of the cluster participants
that is important.
The size of a cluster does not necessarily depend on the size
of the national economy. Although the economies of Ger-
many and Denmark are very much dierent in terms of the
numbers of economic players, clusters in these two coun-
tries have a similar size. The size of clusters in Poland is quite
small given the size of the Polish economy; but clusters may
further grow in the future given the very young history of
these clusters since the establishment of the cluster ma-
nagement organization. Eventually there is of course a size
limit set by the size of the economy as it has an inuence on
the number of players in economic sectors in which clusters
can develop. The large size of Finish clusters can be explai-
ned by the fact the majority of the benchmarked clusters
are rather coordination bodies of smaller clusters in the
same economic eld; in this particular case the funding pro-
gram “OSKE – Centre of Expertise Program”, which supports
the cluster management organizations, had a signicant
eect on the size of the clusters.
2 Based on the SME definition of the European Commission (Recommendation 2003/361/EC regarding the SME definition)
this benchmarking considers a company as a SME if it has no more than 250 employees.
17
Figure 3: Size of the clusters (total number of committed cluster participants)
AUSTRIA
DENMARK
FINLAND
FRANCE
GERMANY
ICELAND
NORWAY
POLAND
SPAIN
SWEDEN
0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800
0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800
0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800
0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800
0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800
0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800
0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800
0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800
0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800
0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800
18
1.2.3 COMPOSITION OF THE CLUSTERS
Figure 4 displays the typical composition of a cluster for
each country. With the exemption of Iceland in all countries
industry (SME and Non-SME) is the dominating stakehol-
der. Swedish clusters have the lowest share of industry (56
per cent, SME: 45 per cent) and Finnish clusters, which are
dominated by SME, the highest (86 per cent, SME: 80 per
cent). The share of industry in Icelandic clusters is only 38
per cent.
The share of R&D institutions and universities is very much
dierent between the countries. Iceland and Germany have
the highest share (R&D institutions and universities account
for 24 respectively 11 per cent of all stakeholders).
1.2.4 REGIONAL CONCENTRATION OF CLUSTERS
According to the denition of Michael E. Porter “clusters are
geographic concentrations of interconnected companies
and institutions in a particular eld”.3 The closer these players
are located to each other, the more likely is not only inter-
action between them, but also the chance of mutual trust
building between them is much higher. Modern ways of
communication, particularly structured by the internet, have
made communication much easier, but nothing beats face-
to-face interaction when it comes to the development and
implementation of projects, in particular if problems have
to be solved. Personal interaction matters in this regard, as it
contributes to the building of trust between project partners,
which is a mandatory resource for successful projects.
It was therefore analyzed how dense the regional concen-
tration of a cluster is. Figure 5 displays for each country the
percentage of cluster members located within a distance of
150 kilometers from the oce of the cluster management
organization. This distance can be easily covered by car or
train in a short period of time, which facilitates personal
interactions through frequent meetings of the cluster stake-
holders.
All clusters that were benchmarked show a high regional
density with a median value of at least 75 per cent. The con-
ditions for successful work in terms of the spatial proximity
of the cluster management organization to the members of
the cluster are in these cases favorable.
Figure 4: Composition of clusters
AUSTRIA
68%
7%
6%
3%
2%
1%
8%
2% 3%
SME
Universities
Consultants
Non-SME
Training and education providers
Governmental agencies
R&D institutions
Financials intermediaries
Others
DENMARK
59%
14%
2%
4%
2%
2%
8%
4% 5%
FINLAND
80%
6%
1% 2%
1% 2%
6%
1%
1%
FRANCE
49%
16%
6%
4%
2%
3%
7%
3%
10%
GERMANY
53%
13%
6%
5%
3%
3%
7%
3%
7%
ICELAND
16%
22%
14%
10%
11%
11%
6%
5%
5%
NORWAY
52%
12%
7%
3%
5%
3%
3%
7%
8%
POLAND
49%
12%
4%
4%
5%
6%
10%
4%
6%
SPAIN
49%
24%
4%
4%
2%
2%
6%
5% 4%
SWEDEN
45%
11%
4%
6%
4%
4%
19%
4% 3%
3 Michael E. Porter, 1998: Clusters and the New Economics of Competition, in: Harvard
Business Review, November/December 1998, p. 78
19
Figure 5: Regional concentration of clusters
AUSTRIA
DENMARK
FINLAND
FRANCE
GERMANY
ICELAND
NORWAY
POLAND
SPAIN
SWEDEN
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
20
1.2.5 FINANCING OF CLUSTER MANAGEMENT ORGANIZA-
TIONS (SHARE OF PUBLIC FUNDING IN TOTAL BUDGET)
Many cluster management organizations depend to a
large extent on public funding to finance staff and other
resources, such as office space and equipment (see Fi-
gure 6). Sources of public funding include project-based
grant funding, institutional funding or service contracts.
The sources and the share of public funding depend very
much on the clusters and their individual environments
as well on the public funding programs that support
them. Cluster management organizations can be funded
from different regional, national and European funding
programs.
The small share of public funding in the budget of Polish
cluster management organizations (median value com-
pared to other countries) is due to the fact that many of
the clusters originate from groups of companies that have
not made use of public funding programs (yet) because
they are not eligible (e.g. they do not have a legally insti-
tutionalized cluster management organization which is a
typical eligibility criterion for funding).
AUSTRIA
DENMARK
FINLAND
FRANCE
GERMANY
ICELAND
NORWAY
POLAND
SPAIN
SWEDEN
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
21
Figure 6: Share of public funds in total budget of cluster management organization
AUSTRIA
DENMARK
FINLAND
FRANCE
GERMANY
ICELAND
NORWAY
POLAND
SPAIN
SWEDEN
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
22
1.3 WHAT MAKES THE DIFFERENCE?
Clusters and their cluster management organisations are
individuals. Even though they share some characteristics as
discussed in the previous chapter, there are also signicant
dierences. What they are and what actually makes the
dierence between clusters that are individuals is presented
in this chapter.
Further insight into this will be provided by further analysis
of:
• Dierencesbetweenresearch-drivenandindustry-driven
clusters
• Sourcesoffunding
• Relevanceofspecicdeterminants
• Eectsofthecluster’stechnologyeld
• Linksbetweenservicesoftheclustermanagementorga-
nisation and SME activities
1.3.1 DIFFERENCES BETWEEN RESEARCH-DRIVEN AND
INDUSTRY-DRIVEN CLUSTERS
Research-driven clusters show dierent characteristics than
industry-driven clusters4: their nancial situation is better
than that of industry-driven clusters, they are smaller in
terms of numbers of cluster participants and in terms of
governance (clarity of roles, level of centralization of gover-
nance structure and legal organization) they show a less
distinct prole than industry-driven clusters. In contrast to
industry-driven clusters the nancial outlook in terms of
budget security of R&D-driven clusters is better (Figure 7).
4 In the context of the benchmarking cluster managers were asked to classify their clusters
as either research or industry-driven. A cluster is research-driven if strategy and activities
are mainly defined by research institutions or universities. If mainly industry defines
strategy and activities, then a cluster is classified as industry-driven.
Figure 7: Comparison of R&D- and industry-driven clusters in terms of structural factors
Age
Share of clusters highly
specialised
in their industry
Numbers of
cluster
participants
Share of cluster
participants within
150 km
Share of clusters that are
legally organised
Share of clusters
with highly centralised
governance structure
Share of clusters
with high clarity
of tasks & roles
Private
financing rate
Share of clusters with
highly assured financing
Median value
R&D driven clusters
Industrial driven clusters
0
25
50
75
100
150
175
Percentage of
median value (%)
125
23
Research-driven clusters have lesser eects on the develop-
ment of SMEs. While research-driven clusters have a higher
eect on R&D activities of research institutions (including
universities) than industry-driven clusters through their clu-
ster management organization, their eects on the industry
are rather small. In contrast, industry-driven clusters have a
larger eect through their cluster management organiza-
tion on business, R&D and international activities of SME.
They are also more successful in establishing co-operations
with companies and research institutions outside the clu-
ster. This suggests that the specic impact of a cluster on
business, R&D and international activities of the cluster
participants depends on the agenda setter: if companies set
the agenda – which is the case in industry-driven clusters
– they benet more, if research institutions set the agenda
– which is the case in research-driven clusters – they benet
more (Figure 8).
Figure 8: Comparison of R&D- and industry-driven clusters in terms of effects on cluster participants
Effect on R&D
activities of research
institutions
Share of clusters
having initiated many
successful co-operations
Share of clusters
with high media coverage
Effect on business
activities of SME
Effect on R&D
activities of SME
Effect on international
activities of SME
Median value
R&D driven clusters
Industrial driven clusters
0
25
50
75
100
125
Percentage of
median value (%)
24
The following table gives an overview of clusters per coun-
try in terms of whether they are research or industry-driven.
The vast majority is driven by industry (65% of the total
sample). There are only a few research-driven clusters (10%
of the total sample), while a quarter of the total sample is
both driven by industry and research.
COUNTRY
NUMBER OF
RESEARCH-DRIVEN
CLUSTERS
NUMBER OF CLUSTERS
THAT ARE BOTH DRIVEN BY
INDUSTRY AND RESEARCH
NUMBER OF
INDUSTRY-DRIV-
EN CLUSTERS
AUSTRIA 0 1 5
DENMARK 8 10 12
FINLAND 0 2 9
FRANCE 2 28 43
GERMANY 6 15 53
ICELAND 2 0 2
NORWAY 0 2 14
POLAND 4 3 13
SPAIN 0 1 5
SWEDEN 3 1 7
TOTAL 25 63 163
Table 3: Number of research-driven and industry-driven clusters and
number of those clusters that are both driven by industry and research
1.3.2 SOURCES OF FUNDING
In terms of structure and governance clusters with a small
share of public funding (private funding has a share of more
than 75 per cent in total funding of the cluster management
organization) and a high share of public funding (the share
of public funding in total funding of the cluster manage-
ment organization is higher than 75 per cent) are similar.
However, there are some dierences between these two
types of clusters (see Figure 9):
• Therearemoreclustersbeingmainlydrivenbyindustry
and highly specialized in a certain industry that have
a cluster management organization that is nanced to
more than 75 per cent by private means.
• Clusterswithaclustermanagementorganizationthat
is nanced to more than 75 per cent by private means
show specic characteristics of governance more often
than clusters with cluster management organizations
that are nanced to a large extent by public funds. They
have more often a dedicated legal form (e.g. registered
association or limited liability) and there are more cluster
management organizations that report a high clarity of
tasks and roles. Thus, clusters with a high share of private
funding tend to be more often highly institutionalized
than clusters with a high share of public funding.
• Clustermanagementorganizationsthatarefundedtoa
large extent by private means are often older.
25
1.3.3 RELEVANCE OF SPECIFIC DETERMINANTS
There is a strong correlation between the age and the size
of a cluster and the eect of the work of the cluster ma-
nagement organization on business and R&D activities of
SME. Clusters that are ve years or older and have more
than 50 members perform signicantly better than younger
and smaller clusters in this regard as well as in terms of the
numbers of initiated successful co-operations. This is also
reectedbythecluster’svisibilityintermsofpressandme-
dia coverage (see Figure 10). Apparently, larger and matu-
red clusters provide a much better environment for results
and impacts as an eect of activities of a cluster manage-
ment organization.
Figure 9: Characteristics of clusters with a small or high share of public funding
Share of clusters highly
specialised in their industry
Number of cluster
participants
Share of clusters
mainly driven by industry
Share of clusters
that are legally organised
Share of clusters
with high clarity of tasks & roles
Share of clusters
having a strategy
Share of cluster
participants within 150 km
Age
Median value
Public funding rate > 75 %
Private funding rate > 75 %
0
25
50
75
100
125
150
Percentage of
median value (%)
26
The older and larger a cluster is, the more institutionalized it
is in terms of having a legal form (with regard to the cluster
management organization) and clarity of tasks and roles
(e.g. through statutes or contracts) of its institutional parts
such as the cluster management organization, a steering
committee or board and a general assembly (see Figure 11).
Figure 10: Relevance of size and age for the effect on cluster participants
Share of clusters
having initiated many
successful co-operations
Share of clusters
with high media coverage
Effect on R&D
activities of SME
Effect on business
activities of SME
Median value
More than 50 participants
Less or equal 50 participants
5 years or younger
Older than 5 years
Percentage of
median value (%)
0
25
50
75
100
125
150
27
Figure 11: Relevance of size and age for the level of institutionalisation of the cluster
Assuming that clusters that are governed by a cluster ma-
nagement organization mature over time, it is not surpri-
sing that they become more and more institutionalized as
they learn like any other organization that a certain set of
rules is a necessary requirement for success. The process of
institutionalization becomes even more relevant the larger
and more heterogeneous a cluster is in terms of member-
ship. A clear and binding set of rules and institutions is
important for building and maintaining trust in large and
heterogeneous groups. The larger and more heterogeneous
a group is, the more it tends to be anonymous and thus the
more it is prone to misconduct. Institutionalization of rules
and processes counterbalances this eect and thus contri-
butes to a culture of trust in a cluster which facilitates colla-
boration between its members. As business and R&D activi-
ties in a cluster require trustfully relationships between the
partners, it is not surprising that old and large institutiona-
lized clusters show a higher impact for exampleon business
and R&D activities of SME than small and young cluster do.
Another interesting pattern is that smaller clusters tend
to specialize in a particular eld (see Figure 11). It seems
that clusters tend to be less specialized the larger they are.
In larger clusters more players are involved with a more
diversied set of interests and options for collaboration.
This translates into a more diversied development of the
technology portfolio of the cluster and – as a result – into a
lesser degree of specialization in a particular eld.
The nding that size and institutionalization have an impor-
tant eect on the development of SME is conrmed by a
further analysis of structural characteristics of clusters.
Share of clusters
highly specialiced in
their industry
Share of clusters
that are legally organised
Share of clusters with high
clarity of tasks & roles
Share of clusters with highly
centralised governance structure
Median value
More than 50 participants
Less or equal 50 participants
5 years or younger
Older than 5 years
Percentage of
median value (%)
0
25
50
75
100
125
150
28
Figure 12 shows that clusters that have a high eect on
business activities of SME are larger in terms of numbers of
members, have more often a legal form (respectively the
cluster management organization) and feature more often
a clear assignment of tasks and responsibilities of their ac-
tors compared to the median value of all analyzed clusters.
Figure 12: Characteristics of cluster with a high effect on business activities of SME
Age
Share of clusters
having a strategy
Share of clusters with
highly assured financing
Share of clusters highly
specialised in their industry
Share of clusters mailly
driven by industry
Numbers of
cluster participants
Share of cluster
participants within 150 km
Share of clusters that are
legally organised
Share of clusters with high
clarity of tasks & roles
Private
financing rate
Share of clusters
with highly centralised
governance structure
Median value
High effect on SME business development
0
25
50
75
100
125
150
Percentage of
median value (%)
29
1.3.4 EFFECT OF THE CLUSTER’S TECHNOLOGY FIELD
The characteristics of a cluster depend very much on the
technology eld it is operating in. Figure 13 displays struc-
tural characteristics of clusters from six dierent technology
elds. The dierent structural characteristics reect the cha-
racteristics of their industry sectors or technology elds. For
example, biotechnology clusters are less oriented towards
industries as still today biotechnology is very much driven
by research institutions and universities. Other examples
for specic industry characteristics are the industry sectors
of energy and environment, services as well as micro, nano
and optic. Clusters in these industries are not highly specia-
lized as they work on technologies that can also be applied
in various other industries.
Figure 13: Structural characteristics of clusters in different technology areas
Share of clusters
highly specialiced in
their industry
Share of clusters
that are legally organised
Share of clusters with high
clarity of tasks & roles
Share of clusters with highly
centralised governance structure
Median value
More than 50 participants
Less or equal 50 participants
5 years or younger
Older than 5 years
Percentage of
median value (%)
0
25
50
75
100
125
150
30
There are also dierences between clusters in dierent
technology areas when it comes to the impact of the work
of the cluster management organization and the share of
private funding of the cluster management organization
(see Figure 14).
These ndings demonstrate that the industry or technology
eld in which a cluster operates in has an important eect
both on the structural characteristics of a cluster and the
performance of a cluster management organization. This
is an important conclusion for the development of future
cluster programs. In order to support clusters according to
their specic needs cluster programs have to take the speci-
c technology foci of clusters into account.
1.3.5 LINK BETWEEN SERVICES AND SME DEVELOPMENT
A cluster management organization can inuence the
development of a cluster through the provision of targe-
ted services for its members (see Box 2 for an overview
of services). The analysis of the benchmarking results has
demonstrated that the more active a cluster management
is in this regard, the higher its impact on the development
of business activities of cluster members is. This was in
detail analyzed for SME members by calculating a composi-
te indicator for business-oriented services provided by the
cluster management organization that was put in relation
with the impact of the work of the cluster management
organization on business activities of SME. Figure 15 dis-
plays a correlation between the spectrum and intensity (in
terms of frequency) of business-oriented services and the
impact of the work of the cluster management organiza-
tion on business activities of SME. The more services are
provided (see e.g. the median value), the higher the impact
on business activities of SME is.
Figure 14: Effects and private funding of clusters in different technology areas
Private financing rate
Effect on international
activities of SME
Effect on business
activities of SME
Effect on R&D activities
of SME
Share of clusters having initiated
many successful co-operations
Median value
Energy & environment
Micro & nano & optic
Biotechnology & health
Services & non-technical innovations
Production & engineering
Information & communication
0
25
50
75
100
150
125
Percentage of
median value (%)
31
1.4 EXCELLENT CLUSTER MANAGEMENT OR-
GANIZATIONS - WHAT ARE THEIR DISTINCTIVE
CHARACTERISTICS?
Excellent management is considered to be a general prere-
quisite for successful operation in industry and the private
sector in general, in the public sector, like education, health,
environment, etc., and in public administration and govern-
mental organizations Therefore, it is obvious that excellent
management should also be considered as a main prerequi-
site for a cluster organization to achieve the highest impacts
of the cluster within a given technological, industrial, regio-
nal, and legislative framework: for the cluster participants,
for the industrial sector in general, and for the development
of regions.
Figure 15: Effect of Spectrum and Intensity of Services on Business Activities of SME
0
10
20
30
Impact on business activites of SME
Significant and
sustainable impacts for a
significant number of
cluster participants
No impacts yet
Total: all clusters in all technology areas
Business oriented composite
service indicator
01234
40
50
60
32
Out of the 261 cluster organizations that have been bench-
marked since November only 71 – less than a third – can be
considered as excellent cluster management organizations
(see Table 4). These organizations demonstrate sophistica-
ted management approaches according to the “excellence
indicators” dened by the European Cluster Excellence
Initiative (ECEI) (see Table 5 on next page) as well as a high
level of services and activities.
In terms of structural characteristics excellent clusters
respectively their management organisations have more
participants and feature more often a higher clarity of tasks
and roles in terms of governance. The age of a cluster ma-
nagement organisation as well as the regional concentrati-
on of the cluster participants within the cluster do not have
an eect on the level of excellence.
Table 4: Number of clusters of the excellence portfolio per specific technology area
TECHNOLOGY
AREAS
Aviation and space
Biotechnology
Construction/building sector
Energy and environment
Food industry (non-biotech)
Health and medical science
Humanities/social sciences, media,
design, service innovation
Information and communication
Micro, nano and optical
technologies
New Materials and chemistry
Production and engineering
Transportation and mobility
TOTAL
TOTAL 5 2 2 11 5 5 6 13 4 7 7 4 71
PERCENT OF
EXCELLENT CLU-
STERS IN THE
SPECIFIC
TECHNOLOGY
AREA
63
%
13
%
40
%
27
%
21
%
26
%
32
%
33
%
18
%
29
%
26
%
25
%
27
%
33
Table 5: Excellence indictors of the European Cluster Excellence Initiative (ECEI)
DIMENSION INDICATOR
STRUCTURE OF
THE CLUSTER
Committed Cluster Participation
Composition of the Cluster Participants
Number of Committed Cluster Participants in Total
Geographical Concentration of the Cluster Participants
TYPOLOGY,
GOVERNANCE,
COOPERATION
Maturity of the Cluster Management
Human Resources Available for the Cluster Management
Qualification of the Cluster Management Team
Life Long Learning Aspects for the Cluster Management Team
Stability and Continuity of Human Resources of the Cluster Management Team
Stability of Cluster Participation
Clarity of Roles – Involvement of Stakeholders in Decision Making Processes
Direct Personal Contacts Between the Cluster Management Team and the Cluster Participants
Degree of Cooperation within the Cluster
Integration of the Cluster Organisation in the Innovation System
FINANCING Prospects of the Financial Resources of the Cluster Organisation
Share of financial resources from private sources
STRATEGY,
OBJECTIVES,
SERVICES
Strategy Building Process
Documentation of the Cluster Strategy
Implementation Plan
Financial Controlling System
Review of the Cluster Strategy and Implementation Plan
Performance Monitoring of Cluster Management
Focus of the Cluster Strategy
Activities and Services of the Cluster Management
Performance of the Cluster Management
Working Groups
Communication of the Cluster Organisation
Cluster organisation’s web presence
ACHIEVEMENTS,
RECOGNITION
Recognition of the Cluster in Publications, Press, Media
Success Stories
Customer and Cluster Participants’ Satisfaction Assessment
34
STRUCTURE OF
THE CLUSTER
Committed Cluster Participation
Composition of the Cluster Participants
Number of Committed Cluster Participants in Total
Geographical Concentration of the Cluster Participants
TYPOLOGY,
GOVERNANCE,
COOPERATION
Maturity of the Cluster Management
Human Resources Available for the Cluster Management
Qualification of the Cluster Management Team
Life Long Learning Aspects for the Cluster Management Team
Stability and Continuity of Human Resources of the Cluster Management Team
Stability of Cluster Participation
Clarity of Roles – Involvement of Stakeholders in Decision Making Processes
Direct Personal Contacts Between the Cluster Management Team and the Cluster Participants
Degree of Cooperation within the Cluster
Integration of the Cluster Organisation in the Innovation System
FINANCING Prospects of the Financial Resources of the Cluster Organisation
Share of financial resources from private sources
STRATEGY,
OBJECTIVES,
SERVICES
Strategy Building Process
Documentation of the Cluster Strategy
Implementation Plan
Financial Controlling System
Review of the Cluster Strategy and Implementation Plan
Performance Monitoring of Cluster Management
Focus of the Cluster Strategy
Activities and Services of the Cluster Management
Performance of the Cluster Management
Working Groups
Communication of the Cluster Organisation
Cluster organisation’s web presence
ACHIEVEMENTS,
RECOGNITION
Recognition of the Cluster in Publications, Press, Media
Success Stories
Customer and Cluster Participants’ Satisfaction Assessment
35
There is a clear dierence between excellent and non-excel-
lent clusters and their management organizations in terms
of activity levels and eects. Excellent cluster management
organizations demonstrate higher service intensity than
non-excellent cluster management organizations and their
agenda is more often driven by industrial interests. In view
of the results and eects the high service intensity of excel-
lent management organizations reects in higher eects
on R&D activities of SME, business activities of SME, interna-
tional activities of SME and a larger number of cooperation
requests from parties outside the cluster (Figure 17 on next
page).
Figure 16: Comparison of structural characteristics of excellent and non-excellent clusters
Age
Share of clusters with high
clarity of tasks & roles
Share of cluster participants
within 150 km
Number of cluster
participants
Median value
Excellent clusters [71]
Non-excellent clusters [190]
0
25
50
75
100
125
150
175
200
36
Summing up the observations, it can be concluded that
size, an adequate level of governance and the provision of
services are key characteristics of excellent cluster manage-
ment organizations that yield eects on cluster develop-
ment, particularly in regard to the development of business,
R&D and international activities of SMEs. Hence, excellence
cluster organisations provide higher impact on business.
1.5 WHAT MAKES THE DIFFERENCE? SOME KEY
FINDINGS
Clusters and their cluster management organisations are
individuals. Although each individual is dierent, analysis
reveals some characteristics that are typical for specic
“groups of individuals”. This applies in particular to the
level a cluster is driven by research or industrial interests,
the level of private funding of a cluster management
organisation, size and age of the cluster respectively its
cluster management organisation, the technology eld of
the cluster and services that are provided by the cluster
management organisation to facilitate the development of
the cluster:
1) Research- and industry-driven clusters are dierent in
terms of nancial situation, size and governance – and
most important: industry-driven clusters have a higher
eect on SME development.
2) The majority of clusters are mainly driven by industry
and - not surprisingly - they also have a higher share of
private nancing than the research driven clusters.
3) There is a strong correlation between the age and the
size of a cluster and the eect of the work of the cluster
management organization on business and R&D activi-
ties of SME. Clusters that are ve years or older and have
more than 50 members perform signicantly better
than younger and smaller clusters in this regard.
4) The characteristics of a cluster depend very much on
the technology eld it is operating in. This includes
Figure 17: Comparison of effects created by excellent and non-excellent clusters
Service intensity
Share of clusters having
many cooperation requests
Share of clusters mainly
driven by industry
Effect on international
activities of SME
Effect on business
activities of SME
Effect on R&D
activities of SME
Median value
Excellent clusters [71]
Non-excellent clusters [190]
0
25
50
75
100
125
150
37
structural characteristics such as governance, being
driven by research- or industry, size and age, but also
the eect of the cluster management organisation on
business, R&D and international activities of SME.
5) There is a correlation between the spectrum and inten-
sity (in terms of frequency) of business-oriented ser-
vices provided by a cluster management organisation
and its eects on business activities of SME. The more
services are provided, the higher the impact on busi-
ness activities of SME is.
6) The older and larger a cluster is, the more institutiona-
lized it is in terms of having a legal form (with regard
to the cluster management organization) and clarity of
tasks and roles
7) Excellent cluster management organizations reveal
higher service intensity than non-excellent cluster ma-
nagement organizations and their agenda is more often
driven by industrial interests. In addition, excellent
cluster initiatives tend to have more participants and
higher clarity of tasks and roles in terms of governance.
Hence, excellence cluster organisations provide higher
impact on business.
1.6 KEY DETERMINANTS FOR THE IMPACT OF A
CLUSTER ON BUSINESS ACTIVITIES OF CLUSTER
MEMBERS
The results of the benchmarking suggest that several key
determinantsmatterintermsofacluster’simpactonthe
business activities of its members; this applies in particu-
lar to the impact on business activities of SME. Structural
factors such as size, age, governance and the type of agen-
da setter (industry or research stakeholders) have an eect
on the spectrum and intensity of services provided by the
cluster management organization and thus on the develop-
ment of business activities of SME.
Figure 18 displays the causal relationship of structural fac-
tors and agenda setters, services and eects: The impact of
a cluster in terms of SME business activities depends on the
spectrum and intensity of services provided by the cluster
management organization which in turn depends on spe-
cic characteristics of the structural factors and agenda
setters as displayed in the gure, which might be inuenced
by the specic characteristics of the technology area the
cluster is operating in.
Figure 18: Key determinants for impact on business activities of cluster members
Size
Age
Governance
Share of private funding in the total
budget of the cluster management
organization
Industry- or research-driven
Technology area of the cluster
Structural factors
Agenda setters
Spectrum and intensity of
services provided by the
cluster management
organization
Impact on
business activities
of SME
Although these determinants are general ndings who-
se relevance may depend on the individual context of a
cluster, particularly on the technology eld the cluster is
operating in, they provide guidance for the development of
cluster programs. From a general perspective the conclusi-
on of the cluster management organization benchmarking
in this regard is: the more matured in terms of age and in-
stitutionalization, the larger in terms of size of membership,
the more industry-driven a cluster is and the more active its
cluster management organization is in terms of spectrum
and intensity of service oer, the higher its eect on econo-
mic development is. This is a key message for policy makers
and program owners.
38
Box 2: Overview services of cluster management organizations
5 Sydow, Jörg/Zeichhardt, Rainer, 2009: Importance of Network Services for the Success of
Networks, in: Buhl, Claudia Martina/Meier zu Köcker, Gerd (eds.), 2009: Cluster Manage-
ment Excellence, Vol. 1: Network Services, Competence Networks Germany, Berlin, p. 20
CATEGORIES OF SERVICES EXAMPLES OF SERVICES
ACQUISITION OF THIRD-PARTY
FUNDING FOR PROJECTS (PUB-
LIC FUNDS)
• Acquisition of R&D and non-R&D projects on behalf of cluster members
• Distribution of information about funding programs
COLLABORATIVE TECHNOLOGY
DEVELOPMENT, TECHNOLOGY
TRANSFER AND R&D PROJECTS
• Organization of tasks forces/working groups
• Management of projects on behalf of cluster members
• Legal advice, e.g. on IPR
INTERNAL NETWORKING
AMONG CLUSTER MEMBERS
• Regular meetings, get-togethers, thematic events/workshops for cluster
members
• Internal newsletters, databases etc.
DEVELOPMENT OF HUMAN
RESOURCES
• Participation in the development and implementation of vocational training
or study courses together with external partners such as universities
• Training courses for cluster members
• Recruitment of staff on behalf of cluster members
DEVELOPMENT OF
ENTREPRENEURSHIP
• Consulting and coaching
• Acquisition of financing (e.g. venture capital, banks, public funds) on behalf
of entrepreneurs
MATCHMAKING AND NET-
WORKING WITH EXTERNAL
PARTNERS/PROMOTION OF THE
CLUSTER LOCATION
• Information material, website, press releases, publications
• Presentation of the cluster and its members on trade fairs or conferences
• Events/workshops to present the cluster
• Matchmaking/partnering events
INTERNATIONALIZATION OF THE
CLUSTER
• Presentation of the cluster and its members on trade fairs or conferences,
networking visits, study tours
• Offices or other permanent representations abroad
• Cooperation with export promotion agencies
Services for clusters members that are provided by the cluster management organization are an important instru-
ment to develop a cluster. They provide a basis for intensifying and/or stabilizing interaction between cluster mem-
bers, reduce the time and costs spent by cluster members through high-quality standard solutions and/or allow
cluster members to focus on their core activities.5 Table 6 gives a general overview of services that can be oered by
a cluster management organization to support the development of a cluster:
For further information about this topic please see Buhl, Claudia Martina/Meier zu Köcker, Gerd (eds.), 2009: Cluster
Management Excellence, Vol. 1: Network Services, Competence Networks Germany, Berlin,
www.kompetenznetze.de/the-service/order-service/cluster-management-excellence-volume-1-network-services
39
Cluster policy issues have appeared in scientic publications
since the 1990s.6 Until today, the question has remained,
whether there are long term impacts visible in those coun-
tries where cluster programs have been implemented. This
chapter gives an overview of 34 European cluster programs,
their objectives, activities, instruments and results.
Clusters help people engaged in the same technology eld
to network with each other, e.g. companies with compa-
nies, companies with research institutes, universities with
governments and so forth. Policies are set up to reply to
market failures. By implementing a cluster policy, national or
regional economies are able to reply to the market failure of
information asymmetries. As a consequence countries have
started to set up specic policies particularly designed to
help establishing new clusters and advancing matured ones.
Thus, governments are eager to start specic policies ai-
ming at the development of clusters –cluster programs – in
order to increase the benet for the companies, universities
and R&D institutions and other service providers within
the cluster. Quoting Boekholt and Thuriaux, cluster policies
“comprise the set of policy activities that aim to: stimulate
and support the emergence of these networks; strengthen
the interlinkages between the dierent parts of the net-
works; and increase the value added of their actions”.7 Ketels
denes cluster policy as “eorts by governments, alone or
in a collaborative eort with companies, universities, and
others, that aim to increase the competitiveness of specic
clusters by organizing government policies around them.”8
Both denitions serve as basis for the analysis presented in
this chapter.
Sure,itisoneofthegovernment’smaintasktoinspireover-
all national or regional strategies that lead to more business
deals and motivate more R&D activities, thus improving the
framework conditions for economic well-being. Fullling
these authoritative tasks, many policy makers have realized
that f. ex. installing infrastructures for the development of
clusters and further supporting them can be a good step
towards smart specialization. The concept of smart specia-
lization includes an “entrepreneurial process of discovery”9
about what the unique selling propositions with regard to
R&D and production of a specic country or region are. In
a way, this is a bottom-up policy process which may pro-
bably be best carried out by clusters and networks. It can
therefore be assumed that due to the corrective inuence
of clusters within an economy, many countries have set up
their specic cluster program.
It is hence of interest to compare the characteristics of the
current cluster programs in Europe in order to learn a. o.
which cluster program has well-developed instruments,
which one is well adjusted to its country specic economic
development strategy and which cluster programs provide
ideas for others to follow a distinct R&D strategy.
For this reason, a pan-European benchmarking exercise was
initiated of which the rst run took place in 2011 and the
second in 2012. The results of the 2011 benchmarking of
cluster programs have been updated in 2012 and are pre-
sented in this chapter. Furthermore, the data base of 2012
has been extended by more cluster programs. They have
been benchmarked with the same criteria as the programs
analyzed in 2011. As of today, 34 cluster programs of 24
countries are included in the cluster program benchmar-
king portfolio.
A group of experts of 24 European countries has evaluated
their specic national or regional cluster program.
As already stated in the introduction, nowadays policy ma-
kers and program owners are no longer facing the question
whether they should establish new clusters, but the que-
stion of how they can improve the global competitiveness
of existing clusters. How can cluster programs support
the development of clusters that can compete in a global
economy? How can cluster programs contribute to cluster
management excellence as a precondition of world-class
clusters? These questions motivated policy makers and pro-
gram owners from dierent European countries to engage
in a benchmarking of cluster programs that should facilitate
mutual learning in this respect.
Chapter 3.1 introduces the comparative portfolio, which
consists of 34 cluster programs from 24 countries. Chap-
ter 3.2 describes the characteristics of these programs in
terms of objectives, strategic focus, instruments, terms and
nancial aspects. Important key ndings from the bench-
marking are presented in chapter 3.3. The key ndings give
further insight into the dierent types of cluster programs,
2 RESULTS OF THE BENCHMARKING OF CLUSTER PROGRAMS
6 Cf.: OECD (1999). Boosting Innovation: The cluster approach. Paris: OECD Proceedings.;
Sölvell, Ö., Lindqvist, G., Ketels, Ch., (2003). The Cluster Initiative Greenbook. www.
cluster-research.org.
7 Boekholt, P., Thuriaux, B. (1999). Public policies to facilitate clusters: background,
rationale and policy practices in international perspective. In: Boosting Innovation: the
cluster approach. Paris: OECD Proceedings. p. 381.
8 Ketels, Ch. (2010). Cluster Policy: A Guide to the State of Debate. In: Hernández, J.M.,
Pezzi, A., Soy, A. (2010). Clusters and competitiveness: the case of Catalonia (1993-
2010). Government of Catalonia, Ministry of Enterprise and Labour, Directorate General
for Industry, Observatory for Industrial Foresight
9 Foray, D., David, P., Hall, B. (2009). Smart Specialization – The Concept. In: Knowledge
Economists Policy Brief No. 9. European Commission.
40
their relevance on the policy agenda and their coordination
with other funding programs, support of cluster internatio-
nalization, the role of program owners when it comes to the
development of clusters, the relevance of cluster manage-
ment excellence in the programs, monitoring and evaluati-
on practices and lessons learned by the program owners.
With this update of the cluster program benchmarking, six
countries that have joined the EU only in 2004 have been
added to the portfolio (Hungary, Czech Republic, Romania,
Lithuania,EstoniaandLatvia).Thus,intotalthebenchmar-
king exercise includes seven (+ Poland) “younger” EU mem-
ber states. It is thus of special interest, if these countries
have dierent core areas in their programs.
2.1 COMPARATIVE PORTFOLIO
The cluster program benchmarking covered 34 cluster
programs from 24 countries, which are Austria, Belgium,
Czech Republic, Denmark, Estonia, Finland, France, Germa-
ny,Hungary,Iceland,Italy,Latvia,Lithuania,Luxembourg,
Norway, Poland, Portugal, Romania, Serbia, Slovakia, Spain,
Sweden, Turkey and United Kingdom.
Figure 19: Participating countries
Iceland
Norway
United
Kingdom Germany
Belgium
Luxembourg
Austria
Italy
Estonia
Latvia
Lithuania
Poland
Czech Replublic
Slovakia
Hungary Romania
Turkey
Serbia
France
Spain
Portugal
Sweden
Finland
41
The programs cover a wide array of dierent rationales,
objectives and instruments, but have the development of
clusters through the support of cluster management orga-
nizations in common.
Table 7: Overview of cluster programs
COUNTRY NAME OF PROGRAM INTERNET
AUSTRIA Cluster Program Lower Austria www.ecoplus.at/en/ecoplus/cluster
BELGIUM Competence Centres-Light Structures Public website not yet available
Cooperative innovation network integrated project http://www.iwt.be/subsidies/vis-trajecten
CZECH
REPUBLIC
Cooperation–Clusters www.czechinvest.org
DENMARK Innovation Networks Denmark (Innovationsnetværk
Denmark)
www.innovationsnetvaerk.dk
ESTONIA Cluster Development Program www.eas.ee
FINLAND Centre of Expertise Program (OSKE, Osaamiskesk-
usohjelma)
www.oske.net
Strategic Centres for Science, Technology and
Innovation (SHOK, Strategisen huippuosaamisen
keskittymät)
www.tekes.fi
FRANCE Grappe d’entreprises www.territoires.gouv.fr/grappes-denterprises
Les Pôles de Compétitivité www.competitivite.gouv.fr
GERMANY Competence Networks Germany (Initiative Kompe-
tenznetze Deutschland) (expired)
www.kompetenznetze.de
Go-Cluster Initiative www.go-cluster.de
Clusterpolitische Gesamtstrategie der Freien und
Hansestadt Hamburg (Cluster Policy Strategy of
the Free and Hanseatic City of Hamburg)
www.bwa.hamburg.de
Cluster Offensive Bayern (Bavarian Cluster Initia-
tive)
www.cluster-bayern.de
Zentrales Innovationsprogramm Mittelstand – För-
dermodul Netzwerkprojekte (ZIM NEMO) (Central
Innovation Program SME – Funding Module Net-
work Projects)
www.zim-bmwi.de/netzwerkprojekte
HUNGARY Cluster Development Program of the New Széche-
nyi Plan
www.magzrt.hu
42
ICELAND Strategic Research Program for Centres of Excel-
lence and Research Clusters (The Icelandic Centre
for Research (Rannsóknamiðstöð ĺslands))
www.rannis.is
Regional Growth Agreements (Vaxtarsamningur) www.vaxtarsamningur.is
ITALY Innovation Clusters Piedmont www.regione.piemonte.it
LATVIA Cluster Program www.liaa.lv/lv/es_fondi/projektu_istenosana/klaste-
ru_programma/
LITHUANIA InnoCluster LT www.ukmin.lt
InnoCluster LT+ www.ukmin.lt
LUXEMBOURG Luxembourg Cluster Initiative www.clusters.lu
NORWAY Norwegian Centres of Expertise (NCE) www.nce.no
Arena Program (Arena-programt) www.arena-programt.no
POLAND Polish Cluster Support Schemes: Support for the
development of Supra-Regional Clusters and Clus-
ter Creation in Eastern Poland
www.parp.gov.pl
PORTUGAL Portuguese Operational Competitiveness Program
- COMPETE
www.pofc.qren.pt
ROMANIA Development of business support infrastructures
of national and international interest (Competitive-
ness Poles)
http://amposcce.minind.ro
Support to the integration of SMEs in value chains
and clusters (Clusters)
http://amposcce.minind.ro
SERBIA Serbian Cluster Development Support Program http://klasteri.merr.gov.rs/en/
SLOVAKIA Support to innovative industrial cluster organiza-
tions
Not yet available
SPAIN Cluster Development Catalonia www.acc10.cat/en//index.jsp
SWEDEN Vinnväxt www.vinnova.se/en/activities/vinnvaxt
TURKEY Support for the Improvement of International Com-
petitiveness (UR-GE)
www.smenetworking.gov.tr/
UNITED
KINGDOM
Knowledge Transfer Networks https://connect.innovateuk.org
43
For a detailed overview of each program in terms of ratio-
nales, objectives, instruments and results please see the
appendix to this report: “Description of Cluster Programs”.
2.2 CHARACTERISTICS OF CLUSTER PROGRAMS
This chapter provides a tabular overview of the dierent
programs in terms of
• Overallobjectivesoftheclusterprograms
• StrategicFocus:Creationofnewclustersorsupportof
existing clusters?
• Strategicobjectivesofclusterprogramsintermsofnum-
bers of clusters to be supported etc.
• Strategicapproach:top-downorbottom-up
• Instrumentsofclusterprograms
• Termofclusterprogramsandnancialaspects
2.2.1 OVERALL OBJECTIVES OF THE CLUSTER PROGRAMS
The cluster programs that have participated in the bench-
marking feature a diverse set of overall objectives. Common
to all programs is their rationale of increasing the compe-
titiveness of the national economy through the facilitation
of collaboration between companies and research stake-
holders. Most of the programs have a national perspective,
while a few focus on the promotion of regional systems of
innovation. The diverse set of overall objectives also reects
dierent types of cluster programs, each of them serving a
specic purpose.
Table 8: Overall objectives of the cluster programs
COUNTRY NAME OF THE
PROGRAM OVERALL OBJECTIVES
AUSTRIA Cluster Program Lower
Austria
• To foster innovation through cooperation of companies in the region’s fields of
economic strength
BELGIUM Competence Cen-
tres-Light Structures
• To support innovation for a large group of companies with focus on SMEs.
These projects should bring companies and knowledge providers together and
contribute to the solution of major socioeconomic challenges
Cooperative innovation
network integrated
project
• To support innovation for a group of at least 20 companies with focus on
SMEs. These projects should result in innovative solutions that can have a
short term implementation
CZECH
REPUBLIC
Cooperation–Clusters • To support the development of cooperative sectoral alliances (clusters) on
regional and national level as a tool for the stimulation of international com-
petiveness and acceleration of economic growth
• To create a favorable business climate with improved conditions for business
development and innovations and to build a sustainable competitive advan-
tage by enhancing the quality of relationships among research institutions,
universities and business sectors
DENMARK Innovation Networks
Denmark
• To strengthen innovation and research in Danish companies and thereby pro-
mote knowledge-based growth in business and industry
• To strengthen public-private interaction and knowledge sharing and develop-
ment of research and innovation between knowledge institutions and companies
ESTONIA Cluster Development
Program
• To increase the international competitiveness of entrepreneurs through
implementing the co-operation projects of a cluster
44
FINLAND OSKE – Centres of Exper-
tise Program
• To create new innovations, products, services, companies and jobs based on
top-class expertise
• To support interregional specialization and division of duties in order to cre-
ate internationally competitive centres of expertise
• To increase the attraction of regional innovation environments in order to lure
international companies, investments and leading experts to the region
SHOK – Strategic Centres
for Science, Technology
and Innovation
• To establish international Strategic Centres of Excellence in STI in key com-
petence areas with regard to future needs of the business sector and society.
The centres are expected to renew industry clusters and to create radical
innovations
FRANCE Grappe d’entreprises • To develop business clusters in economic sectors with weak R&D activity
Les Pôles de Compéti-
tivité
• To boost the competitiveness of the French economy and to help develop
growth and jobs in key markets
• To improve the attractiveness of France by providing support for high-tech
and creative activities, primarily industrial, in the various regions of France
and by that increasing international visibility
GERMANY Competence Networks
Germany
• To facilitate intensive networking between industry and science to increase
the innovation capacity and international competitiveness of German industry
• To increase international visibility of the clusters and by this market Germany
as an international innovation hub
Go-Cluster • To continue the mission of the Competence Networks Initiative
• To increase the competitiveness of German regions
• To approach the excellence status of European cluster management organiza-
tions
Cluster Offensive Bayern • To support the competitiveness of the Bavarian enterprises in selected fields
of competence
Cluster Policy Strategy of
Hamburg
• Medium and long term support of economic growth and employment
Zentrales Innovation-
sprogramm Mittelstand
– Netzwerkprojekte (ZIM
NEMO)
• Development of innovation capacities and competitiveness of SME through
the support of innovation networks
HUNGARY Cluster Development
Program of the New
Széchenyi Plan
• To develop R&D and innovation infrastructure, improve the facilities of higher
education institutes
• To motivate the cooperation of companies through clusters
• To support joint innovation investments of clusters
• To accredit innovative clusters
ICELAND Regional Growth Agree-
ments (Vaxtarsamningur)
• To promote innovation and strengthen the competitiveness of regions through
networking and cluster co-operation among firms, R&D institutions, universi-
ties, municipalities and the government
Strategic Research
Program for Centres of
Excellence and Research
Clusters
• To reinforce science and technology research, encourage successful collabo-
ration between different parties nationally, as well as internationally and actu-
ate value creation and investment in research and innovation in the economy
ITALY Innovation Clusters
Piedmont
• To identify firms’ technological needs in order to guide future regional policy
actions in support of research and innovation
• To stimulate R&D and innovation in its firms, valorizing the present assets,
developing the internationalization processes and increasing the attraction of
productive investments in the region
45
LATVIA Cluster Program • To promote cooperation between unrelated companies operating in specified
sectors and research, educational and other institutions, thus promoting
increase of export volumes and competitiveness of entrepreneurs as well as
development of new products
LITHUANIA InnoCluster LT • To stimulate the collaboration of Lithuanian industries
• To increase international competitiveness of Lithuanian industries
InnoCluster LT+ • To stimulate collaboration among Lithuanian industries and to increase inter-
national competitiveness of Lithuanian industries
• To create a favorable environment for innovative clusters and to develop
international clusters
LUXEMBOURG Luxembourg Cluster
Initiative
• To enhance the visibility of the technological excellence and the innovation
potential of cluster members
• To encourage the uptake of new technologies and the identification of poten-
tial business opportunities
NORWAY Norwegian Centres of
Expertise (NCE)
• To facilitate growth by generating and reinforcing cooperation-based innova-
tion and internationalization processes within clusters with clear ambitions
and substantial national and international growth potential
Arena Program • To strengthen the capability of regional business environments for innovation
and value creation by intensifying alliances between business environments,
educational institutions and the public sector
POLAND Polish Cluster Support • Increased competitiveness of the Polish economy through the support of the
establishment and development of clusters at the national and regional level
PORTUGAL COMPETE • To improve the sustained competitiveness of the Portuguese economy in the
context of the global market, intervening on strategic dimensions such as
innovation, scientific and technological development, internationalization,
entrepreneurship and modernization of public administration
ROMANIA Competitiveness Poles • To foster the setting up and development of innovative enterprises / activi-
ties in enterprises resulting in an increased number of suppliers and clients
on national and international markets via an integrated financing package of
projects jointly developed by enterprises, R&D organisations, NGOs and public
bodies
Clusters • To develop specific business structures (clusters) around productive activities
aiming at increasing the added value of competitive products on national and
international markets
SERBIA Serbian Cluster Develop-
ment Support Program
• To improve international competitiveneness
• To introduce a new economic development policy in accordance with the EU
standards and use the results in order to define key assumptions for fostering
competitiveness in Serbia
• Tto use clusters as a platform for new innovation policy which is under prepa-
ration
SLOVAKIA Support to innovative
industrial cluster organi-
zations
• To develop individual measures of the Innovation Strategy of the Slovak
Republic for 2007 to 2013
• To set up support mechanisms for the creation and development of innovation
structures, innovation businesses, partnership and cooperation among busi-
nesses, universities and research institutes in the fields of research, develop-
ment and innovation, and the establishment of conditions for
46
2.2.2 STRATEGIC FOCUS: ESTABLISHMENT OF NEW CLUS-
TERS OR SUPPORT OF MATURED CLUSTERS
Most programs support both the establishment of new
cluster management organizations and the further deve-
lopment of already existing matured cluster management
organizations.
Only a few programs concentrate either on the establish-
ment of new cluster organizations or the further develop-
ment of already existing matured cluster organizations.
These programs - including the German programs “Go-
Cluster” and “Cluster Oensive Bayern”, the Norwegian
programs “Norwegian Centres of Expertise” and “Arena”,
the Icelandic program “Strategic Research Program for
Centres of Excellence and Research Clusters”, the “Cluster
ProgramLowerAustria”,theFrench“PôlesdeCompétitivi-
té”,theLithuanianinitiative“InnoClusterLT”,theRomanian
“Competitiveness Poles” and the Spanish/Catalan program
“Cluster Development Catalonia” – have a dedicated strate-
gic orientation towards either setting up cluster manage-
ment organizations from scratch or towards the promotion
of particular industries that are already cluster-driven to
improve the global competitiveness of industry sectors that
are relevant for the national economy.
Although such a clear focus on such a single specic ob-
jective is certainly an advantage for a cluster program as
it supports the concentration of resources on the specic
needs of clusters, programs that both establish new cluster
organizations and further develop already existing ma-
tured cluster organizations do not have to be necessarily
ineective or inecient. In their case it depends ultimately
on how well developed the strategy and the set of instru-
ments are and if they are applied in a way that ensures the
addressing of the needs of both target groups. However,
due to the dierent needs of young and matured cluster
organizations it is most likely that more eorts by the
program owners have to be made in terms of coordination.
This may have a negative eect on the eciency and ef-
fectiveness of a cluster program, if it is not equipped with
sucient resources, particular in terms of numbers and
experience of sta.
The cluster programs of the younger EU member countries
mostly support both the establishment of new cluster
management organizations and the further development
of already existing matured cluster management organi-
zations. Romania has two cluster programs each of which
specically dedicates its eort to either the development
of new cluster organizations or the further support of the
already existing cluster management organizations.
SPAIN Cluster Development
Catalonia
• To improve the competitiveness of Catalan companies by facilitating strategic
change and upgrading their business toward more added value activities.
• To strengthen innovation through cross-sectoral cooperation projects
• To improve the professionalization of cluster managers and stimulate net-
working
SWEDEN Vinnväxt • To promote sustainable growth in regions by developing competitive research
and innovation environments within specific growth fields
TURKEY Support for the Improve-
ment of International
Competitiveness (UR-GE)
• To develop a joint action culture
• To create new exporters
• To create new export markets
• To develop consultancy services capacity of Turkish companies
UNITED
KINGDOM
Knowledge Transfer
Networks
• To stimulate technology-enabled innovation through increased knowledge
transfer, partnership formation, supply chain support and other relevant
support
47
Table 9: Strategic Focus: Creation of new or support of existing cluster management organizations?
COUNTRY NAME OF THE PROGRAM
ESTABLISHMENT
OF NEW
CLUSTER
ORGANIZATIONS
FURTHER DEVELOPMENT
OF ALREADY EXISTING
MATURED CLUSTER
ORGANIZATIONS
AUSTRIA Cluster Program Lower Austria X
BELGIUM Competence Centres-Light Struc-
tures X X
Cooperative innovation network
integrated project X X
CZECH
REPUBLIC
Cooperation–Clusters
X X
DENMARK Innovation Networks Denmark X X
ESTONIA Cluster Development Program X X
FINLAND OSKE – Centres of Expertise Pro-
gram X X
SHOK – Strategic Centres for Sci-
ence, Technology and Innovation X X
FRANCE Grappe d’enterprises X X
Les Pôles de Compétitivité X
GERMANY Competence Networks Germany X
Go-Cluster X
Cluster Offensive Bayern X
Cluster Policy Strategy of Hamburg X X
Zentrales Innovationsprogramm
Mittelstand – Netzwerkprojekte
(ZIM NEMO)
X
HUNGARY Cluster Development Program of the
New Széchenyi Plan X X
ICELAND Strategic Research Program for
Centres of Excellence and Research
Clusters (RANNIS)
X
Regional Growth Agreements (Vax-
tarsamningur) X X
48
ITALY Innovation Clusters Piedmont X
LATVIA Cluster Program X X
LITHUANIA InnoCluster LT X
InnoCluster LT+ X
LUXEM-
BOURG
Luxembourg Cluster Initiative
X X
NORWAY Norwegian Centres of Expertise
(NCE) X
Arena Program X
POLAND Polish Cluster Support X X
PORTUGAL COMPETE X
ROMANIA Competitiveness Poles X
Clusters X X
SERBIA Serbian Cluster Development Sup-
port Program
X X
SLOVAKIA Support to innovative industrial
cluster organizations
SPAIN Cluster Development Catalonia X
SWEDEN Vinnväxt X X
TURKEY Support for the Improvement of
International Competitiveness
(UR-GE)
X X
UNITED
KINGDOM
Knowledge Transfer Networks n.a. n.a.
49
2.2.3 STRATEGIC OBJECTIVES IN TERMS OF NUMBERS OF
CLUSTERS
Most programs do not have particular strategic objectives
in terms of numbers of clusters that are funded, restrictions
on thematic areas and coverage of the most important
business sectors.
If there are such strategic objectives then they are moti-
vated by the interest in a consolidated cluster landscape
(e.g. in the case of Innovation Networks Denmark it was
decided to limit the number of nationwide clusters) or in
the concentration of eorts on the most important business
sectorsoftheeconomy(e.g.LuxembourgClusterInitiative,
Innovation Networks Denmark, the Norwegian Centers of
Expertise program or the Cluster Policy Strategy of the Free
and Hanseatic City of Hamburg).
If a decision was taken to limit the number of clusters per
thematic area it was motivated by concentrating eorts on
specic clusters to increase the eciency and eectiveness
of the program and to increase the critical mass, the impact
and the quality of the individual cluster organizations. To
varying degrees this motivation has also informed the de-
cisions of program owners who have decided for strategic
limitations with regard to the total number of cluster that
should be supported.
With regard to the limitation of numbers of clusters per the-
matic area some program owners pointed out that one has
to balance between the interest in concentrating resour-
ces for the benet of eciency and eectiveness and the
potential economic benets that result from competition
between clusters in the same thematic area.
Table 10: Strategic objectives of cluster programs
COUNTRY NAME
OF THE PRO-
GRAM
When looking at the overall cluster policy of the country and
the program in particular is there a strategy/objective with
regard to cluster landscape in terms of …
… THE
TOTAL
NUMBER OF
CLUSTERS?
… LIMITATIONS
IN NUMBERS
PER THEMATIC
AREA?
… OF COVERING THE
MOST IMPORTANT
BUSINESS SECTORS
OF THE ECONOMY?
AUSTRIA Cluster Program
Lower Austria Ye s Ye s Yes
BELGIUM Competence Cen-
tres-Light Structures
No No Yes
Cooperative innova-
tion network inte-
grated project
No No Yes
CZECH
REPUBLIC
Cooperation–Clus-
ters, Czech Republic
Yes No No
DENMARK Innovation Networks
Denmark
Yes Yes Yes
ESTONIA Cluster Development
Program
No No Yes
50
FINLAND OSKE – Centres of
Expertise Program
Yes Yes Yes
SHOK – Strategic
Centres for Science,
Technology and
Innovation
No Yes Yes
FRANCE Grappe d’enterprises No No No
Les Pôles de Com-
pétitivité
Yes No Yes
GERMANY Competence Net-
works Germany
No No No
Go-Cluster No No No
Cluster Offensive
Bayern
No Yes No
Cluster Policy Strate-
gy of Hamburg
No Yes Yes
Zentrales Innovation-
sprogramm Mittel-
stand – Netzwerkpro-
jekte (ZIM NEMO)
No No No
HUNGARY Cluster Development
Program of the New
Széchenyi Plan,
Hungary
No No No
ICELAND Regional Growth
Agreements (Vaxtar-
samningur)
No No No
Strategic Research
Program for Centres
of Excellence and
Research Clusters
No No No
ITALY Innovation Clusters
Piedmont
Yes No Yes
LATVIA Cluster Program No No Ye s
LITHUANIA InnoCluster LT No Yes Ye s
InnoCluster LT+ No Yes Yes
LUXEMBOURG Luxembourg Cluster
Initiative
No No No
NORWAY Norwegian Centres of
Expertise (NCE)
Yes No Yes
Arena Program No No Yes
POLAND Polish Cluster Sup-
port
No No No
51
Table 12: Instruments of cluster programs
Table 13: Term of cluster programs and financial aspects
PORTUGAL COMPETE, Portugal Yes Yes Yes
ROMANIA Competitiveness
Poles, Romania
No Yes Yes
Clusters, Romania Yes No Ye s
SERBIA Serbian Cluster De-
velopment Support
Program
Yes No Yes
SLOVAKIA Support to innovative
industrial cluster
organizations
No No Yes
SPAIN Cluster Development,
Spain
Yes Yes Yes
SWEDEN Vinnväxt No No No
TURKEY Support for the Im-
provement of Inter-
national Competitive-
ness (UR-GE)
No No No
UNITED
KINGDOM
Knowledge Transfer
Networks
n.a. n.a. n.a.
With regard to the strategic decision whether there should
be a limit of the number of clusters per thematic area the
discussion of this pattern with some of the program owners
put a very interesting question on the table. According to
Porter “[c]lusters promote competition and cooperation.
Rivals compete intensively to win and retain customers.
Without vigorous competition, a cluster will fail”. 10 Porter’s
argument is focusing on competition between companies
within the cluster. Why should not there be also competiti-
on between the cluster management organizations when
they apply for public support? Competition for limited
public funds due to the decision of the program agency to
support only one cluster management organization in the
thematic area of XYZ puts pressure on cluster management
organizations to focus their eorts on areas and activities
where they can create the most benets for their cluster
members. A wider spectrum and a higher frequency of
services for the cluster members which in turn trigger
economic activities e.g. of SME (for further details about
the link between services and impact) would be one of the
results of such a competition. Although there are certainly
restrictions for such an approach – e.g. in larger countries
it can make economic sense to have several clusters in a
specic thematic area due to the regional concentrations
of relevant cluster stakeholders -, limiting public means to
a few eventual beneciaries would denitely encourage
cluster management organizations to think about how they
can be better than their competitors. Competition is always
good to encourage rethinking whether one is taking the
right decisions.
2.2.4 TOP-DOWN OR BOTTOM-UP
Bottom-up is the approach of program implementation
favored by the majority of the program owners (see table
11). Although setting the legal frame of the program through
funding guidelines, most programs take only general decisi-
ons in terms of which sectors or projects should be develo-
ped by cluster management organizations. In this regard the
implementation of the program is left to the cluster manage-
ment organization. Program owners agreed on the opinion
10 Michael E. Porter, 1998: Clusters and the New Economics of Competition, in: Harvard
Business Review, November 1998, p. 78
52
that cluster management organizations and their aliated
members know best which projects they should focus on
to create value or which organizational models they should
follow to ensure eciency and eectiveness of operations.
In cases where program owners answered that they follow
both a top-down and a bottom-up approach bottom-up
implementation was clearly the dominating program ratio-
nale. In these cases the top-down element was motivated
either because program owners had specic requirements
with regard to the structure of the project consortium
or they emphasized their interest in interfering in cluster
operations e.g. to motivate mergers with other clusters or a
strategic reorientation.
There are only three cluster programs, the “Cluster Oensive
Bayern”, the “Innovation Clusters Piedmont”, and “Compe-
tenceCenters–LightStructures”ofBelgiumwhichfollow
a dedicated top-down approach. Within “Cluster Oensive
Bayern” both the industry areas in which clusters are sup-
ported as well as the organizations that are responsible for
the development of the cluster were chosen by the ministry
prior to the start of the program. However, in terms of their
operations the cluster organizations act without interfe-
rence from the supervising Ministry of Economic Aairs,
Infrastructure, Transport and Technology.
The initiative “Innovative Clusters Piedmont” created 12 inno-
vation clusters from 12 technological domains by benetting
from the ERDF Regional Operational Program. The cluster
managing authorities needed to control the 12 domains
were installed through a national call for proposals in 2009.
Table 11: Strategic approach: top-down or bottom-up
COUNTRY NAME OF THE PROGRAM TOP-DOWN BOTTOM-UP
AUSTRIA Cluster Program Lower Austria X X
BELGIUM Competence Centres-Light Structures X
Cooperative innovation network integrated project X
CZECH
REPUBLIC
Cooperation–Clusters X X
DENMARK Innovation Networks Denmark X X
ESTONIA Cluster Development Program X X
FINLAND OSKE – Centres of Expertise Program X
SHOK – Strategic Centres for Science, Technology and
Innovation
X X
FRANCE Grappe d’enterprises X
Les Pôles de Compétitivité X X
53
GERMANY Competence Networks Germany n.a. n.a.
Go-Cluster n.a. n.a.
Cluster Offensive Bayern X •
Cluster Policy Strategy of Hamburg X X
Zentrales Innovationsprogramm Mittelstand – Netzwerk-
projekte (ZIM NEMO)
X
HUNGARY Cluster Development Program of the New Széchenyi Plan X X
ICELAND Regional Growth Agreements (Vaxtarsamningur) X
Strategic Research Program for Centres of Excellence and
Research Clusters
X
ITALY Innovation Clusters Piedmont X
LATVIA Cluster Program X X
LITHUANIA InnoCluster LT X
InnoCluster LT+ X
LUXEMBOURG Luxembourg Cluster Initiative X X
NORWAY Norwegian Centres of Expertise (NCE) X
Arena Program X
POLAND Polish Cluster Support X
PORTUGAL COMPETE X X
ROMANIA Competitiveness Poles X
Clusters, Romania X
SERBIA Serbian Cluster Development Support Program X
SLOVAKIA Support to innovative industrial cluster organizations X
SPAIN Cluster Development X
SWEDEN Vinnväxt X X
TURKEY Support for the Improvement of International Competitive-
ness (UR-GE)
X X
UNITED
KINGDOM
Knowledge Transfer Networks X
54
2.2.5 INSTRUMENTATION
Grant funding is the main instrument of nearly all cluster
programs, while technical assistance for capacity develop-
ment of cluster management organizations and its members
is applied by only half of the programs (see table 12).
All program owners agreed that the provision of funding is
not sucient to develop cluster management organizations
that are capable to drive the sustainable development of a
cluster. However, not all program owners provide technical
assistance for capacity development (e.g. through trainings
and consultancy services) that goes beyond internet plat-
forms and regular meetings between program owners and
clustermanagers.TheLuxembourgClusterInitiativeandthe
ClusterProgramLowerAustriadonotprovidegrantfunding
at all, but only technical assistance for cluster management
organizations through dierent workshops, working groups,
benchmarking, matchmaking but also individual services.
In most cases where programs provide technical assistance
this was done right from the start of the program being a
part of the program strategy. Programs that do not provide
technical assistance are either considering this (e.g. the Ice-
landic Strategic Research Program for Centres of Excellence
and Research Clusters) or have to rely on other institutions
that are not directly aliated with the program (e.g. the
FrenchprogramGrapped’entreprises).
The extent to which technical assistance can be provided
depends on the resources available to the programs. While
the German project “go-cluster” can rely on more than 15
people to organize trainings and workshops, other pro-
grams have smaller resources available which in turn results
into a less frequent and rather small-scale provision of
technical assistance.
COUNTRY NAME OF THE PROGRAM FUNDING
TECHNICAL ASSISTANCE (E.G.
PROVISION OF TRAINING AND
CONSULTANCY SERVICES)
AUSTRIA Cluster Program Lower Austria X
BELGIUM Competence Centres-Light Structures X X
Cooperative innovation network
integrated project
X X
CZECH
REPUBLIC
Cooperation–Clusters X
DENMARK Innovation Networks Denmark X X
ESTONIA Cluster Development Program X X
FINLAND OSKE – Centres of Expertise Program X
SHOK – Strategic Centres for Science,
Technology and Innovation
X
FRANCE Grappe d’enterprises X
Les Pôles de Compétitivité X
Table 12: Instruments of cluster programs
55
COUNTRY NAME OF THE PROGRAM FUNDING
TECHNICAL ASSISTANCE (E.G.
PROVISION OF TRAINING AND
CONSULTANCY SERVICES)
AUSTRIA Cluster Program Lower Austria X
BELGIUM Competence Centres-Light Structures X X
Cooperative innovation network
integrated project
X X
CZECH
REPUBLIC
Cooperation–Clusters X
DENMARK Innovation Networks Denmark X X
ESTONIA Cluster Development Program X X
FINLAND OSKE – Centres of Expertise Program X
SHOK – Strategic Centres for Science,
Technology and Innovation
X
FRANCE Grappe d’enterprises X
Les Pôles de Compétitivité X
GERMANY Competence Networks Germany X
Go-Cluster X
Cluster Offensive Bayern X X
Cluster Policy Strategy of Hamburg X
Zentrales Innovationsprogramm Mittel-
stand – Netzwerkprojekte (ZIM NEMO)
X
HUNGARY Cluster Development Program of the New
Széchenyi Plan
X X
ICELAND Regional Growth Agreements
(Vaxtarsamningur)
X
Strategic Research Program for Centres
of Excellence and Research Clusters
X
ITALY Innovation Clusters Piedmont X X
LATVIA Cluster Program X X
LITHUANIA InnoCluster LT X
InnoCluster LT+ X
LUXEM-
BOURG
Luxembourg Cluster Initiative X
NORWAY Norwegian Centres of Expertise (NCE) X X
Arena Program X X
POLAND Polish Cluster Support X X
PORTUGAL COMPETE X
ROMANIA Competitiveness Poles X X
Clusters X X
SERBIA Serbian Cluster Development Support
Program
X X
SLOVAKIA Support to innovative industrial cluster
organizations
X
SPAIN Cluster Development X X
SWEDEN Vinnväxt X X
TURKEY Support for the Improvement of Interna-
tional Competitiveness (UR-GE)
X X
UNITED
KINGDOM
Knowledge Transfer Networks X X
Cluster Program
Lower Austria Competence
Centres-Light
Structures, Belgium
Cooperative
innovation network
integrated project,
Belgium
Cooperation–
Clusters, Czech
Republic
Innovation Networks
Denmark Cluster Development
Program, Estonia OSKE – Centres of Exper-
tise Program, Finland SHOK – Strategic Centres
for Science, Technology and
Innovation, Finland
Grappe d’entreprises,
France Les Pôles de Compétitivité,
France
Go-Cluster, Germany
Cluster Offensive Bayern,
Germany
Zentrales Innovation-
sprogramm Mittelstand
– Netzwerkprojekte (ZIM
NEMO), Germany
Competence Networks,
Germany
Cluster Development
Program of the New
Széchenyi Plan, Hun-
gary
Regional Growth Agree-
ments (Vaxtarsamnin-
gur), Iceland
Strategic Research
Program for Centres of
Excellence and Research
Clusters, Iceland
Innovation Clusters
Piedmont, Italy
Cluster Program, Latvia
InnoCluster LT, Lithuania
InnoCluster LT+, Lithuania
Luxembourg Cluster
Initiative
Norwegian Centres of
Expertise (NCE), Norway
Arena Program, Norway
Innovative Economy Oper-
ational Program, Measure
5.1 “Support of the Devel-
opment of supra-regional
clusters”, Poland
Operational Program Devel-
opment of Eastern Poland
2007-2013, Priority 1.4
“Promotion and coopera-
tion” with Measure 1.4 “Co-
operation – cluster creation
and development”, Poland
COMPETE, Portugal
Competitiveness Poles,
Romania
Clusters, Romania
Serbian Cluster Devel-
opment Support Pro-
gram, Serbia
Support to innova-
tive industrial clus-
ter organizations,
Slovakia
Cluster Develop-
ment, Catalonia,
Spain
Vinnväxt, Sweden
Support for the
Improvement of In-
ternational Compet-
itiveness (UR-GE),
Turkey
Knowledge Transfer
Networks, UK
TERM OF THE
PROGRAM
2007-2013 2011 - ongoing 2010 - ongoing 2007-2013 2005 - ongoing 2007-2013 2007-2013 Since 2006 2009 -ongoing 2005-2012 2012-2014 2006 - ongoing 2008-2013 1997-2012 2007-2013 2010-2013
(current period)
2009-2015 2007-2013 2007-2013 2007-2013 2007-2013 2010 - ongoing 2006 - ongoing 2002 - ongoing 2007-2013 2009-2015 2007-2013 2012-2015 2012-2015 2007-2013 2011-2013 2005 - ongoing 2002-2015 2010 2005-2014
BUDGET EUR 20.5 million in total EUR 19 million p.a. EUR 15 million p.a. EUR 90 million in total EUR 8 -10 million p.a. EUR 10.4 million n. a. n.a. EUR 24 million EUR 1.5 milliard EUR 1 million p.a. EUR 6 million p.a. EUR 52.2 million EUR 1 million p.a. EUR 600 million EUR 3.8 million EUR 6.8 million EUR 90 million in total “Cluster program” (2012-2015): EUR
4.8 million (ERDF)
“Cluster development program”
(2009-2011): EUR 0,75 million (State
budget)
EUR 9.5 million in total EUR 57 million in total The Luxembourg Cluster Initiative
has no allocated budget, but bene-
fits from resources provided by Lux-
innovation, the National Agency for
Innovation and Research, to enable it
to develop its various services.
EUR 8.3 million p.a. EUR 5 million p.a. EUR 104 million EUR 11 million EUR 452 million EUR 60 million in total EUR 20 million in total EUR 1.6 million n.a. EUR 5.1 million EUR 8.8 million p.a. EUR 5 million p.a. EUR 21 Million p.a.
TYPE OF
FUNDING
Technical assistance (=
Basic Support for Cluster
Management)
Subsidies 80% of accepted
costs
Subsidies 80% of accepted
costs
Grant funding Grant funding and technical
assistance
Grant Funding Grant funding Grant funding and loans Grant funding Grant Funding Only the management agency is funded to
provide technical assistance. No funding of
individual clusters.
Grant funding and technical assistance Grant funding Only the management agency is fund-
ed to provide technical assistance. No
funding of individual clusters.
Grant funding Grant funding Grant funding Grant funding Grant Funding Grant funding Grant funding Provision of technical assistance. No
funding of individual clusters.
Grant funding and technical assis-
tance
Grant funding and technical assis-
tance
Grant funding Grant funding Public System of Incentives Grant funding Grant funding Grant funding n.a. Grant funding Grant funding and technical
assistance
Grant Funding Grant funding
DOES THE
PROGRAM
HAVE A
SPECIFIC
TECHNOLOGY
FOCUS?
No No No No No To some extent.
The following sectors are prior-
itized: biotechnology, ICT and mate-
rial technology, energy, healthcare
and environmental protection.
A project that is directly or in-
di-rectly involved with these
sec-tors will get bonus points in
the evaluation process (5% out of
100%).
No Yes No No No No No No No No No No No No No No No No No No No No No No n.a. No No No No
MAXIMUM
FUNDING
PERIOD FOR
A PROJECT
n.a. Four years Six years Up to three years Four years per period (can
be extended after a positive
evaluation)
Preliminary applications: max. 12
months
Full applications: max. 48 months
One year Five years Three years For R&D pro-jects: No, normally 5-year
projects.
For innovation platforms: 5 years (possi-
ble extension)
For the cluster management: Until the
end of the second phase of the program
2012. A third phase should begin in 2013.
n.a. There is no maximum funding period. Four years n.a. Three years There is no maximum funding
period.
Seven years Up to one year 3 years Up to 30 months Up to three years n.a. Ten years Up to five years There is no maximum funding period. There is no maximum funding period. n.a. Up to two years Up to two years Eight months n.a. One year Ten years 3 years 3 years with an option of an exten-
sion of 2 years
IS THERE A
MAXIMUM
AMOUNT OF
FUNDING AN
APPLICANT
CAN APPLY
FOR?
n.a. EUR 2.5 million, depending on
type of project
No Max. EUR 3.5 million in total Not formally. But in reality max
EUR 1 million p.a.
Preliminary applications: max. EUR
26.000
Full applications: no specific limit
set
EUR 140,000 There is no maximum amount. EUR 500,000 No n.a. There is no maxi-mum amount. EUR 350,000 n.a. EUR 500,000 There is no maximum amount of
funding.
EUR 3.4 million Max. EUR 20 million Yes. Max. EUR 0.42 million per one
cluster and max. EUR 14 thousands
for one collaboration partner.
Max. EUR 450.000 Max. EUR 11 million n.a. Max. EUR 770.500 p.a. Max. EUR 300,000 p.a. EUR 5 million There is no maximum amount. The maximum funding granted to each
of the applicant is related with the
number of project approved
Max. EUR 20 million Max. EUR 1 million EUR 25.000 n.a. No Max. EUR 1.1 million p.a. Max: EUR 1.6 mio Overall expenditure needs to fit
with programme envelope, individ-
ual budgets vary, max. currently
EUR 2.1 Million p.a., but is not
fixed
FINANCING
STRUCTURE
OF PROJECTS
60% of regional fund of
program, 28% ERDF, 12%
fees
Coordination activities 80% of
eligible costs are accepted
80% of eligible costs are
accepted
Max. 60% funding from the
program
Max. 50 % national government
co-financing
Preliminary applications: max. 75%
funding
Full applications: max. 70% funding
Entrepreneurs must provide at
least 50% of the entire amount of
self-financing.
Max. 50% from the OSKE program Max. 75% for the establishment of the
centers and for research programs carried
out by them. Max. 50 % for cluster proj-
ects by companies.
Max. 25% funding from the program For R&D projects: between 25% and 45
%
For innovation platforms: from 15% to
50%
n.a. Max. 75 % funding from the program,
share is currently decreased as clus-
ters are expected to increase the
share of private co-financing
In the initial phase the project can be
co-funded with up to 90% of eligible
costs to develop a network concept,
but the share of public funding will be
decreased in three steps in the course
of the project duration when the net-
work concept is implemented (70% →
50% → 30%).
n.a. Max. 50% funding from New Hun-
gary Development plan and private
sources
Max. 50 % funding from the pro-
gram
Max. 25% funding from the program Max. 50% funding from the program Cluster management activities: up
to 90%
Cluster services provided for collabo-
ration partners: up to 85%
Up to 50% 50%, 60%, 70% funding from the pro-
gram depending on conditions
n.a. 50% funding from the NCE program Max. 50% funding from the program Up to 100% funding from the program Up to 75% funding from the program. n.a From 25% up to 100% funding
from the program depending on
conditions
From 25% up to 100% funding
from the program depending on
conditions
Up to 50% eligible costs n.a. Max. 75% funding from the
program
Max. 50% funding from the
program
Need Analysis including train-
ing and joint consultancy for
companies
Trade Mission
Buyers’ Mission
Employment (two project staff
for each collaboration organiza-
tion for 3 years)
Consultancy (optional, after
completion of joint 3 years)
100% grant funding for core
programme, but extra income
from public and private sources
is encouraged (ranges from 0 to
100% currently).
2.2.6 TECHNICAL DETAILS: TERM AND FINANCIAL ASPECTS
OF CLUSTER PROGRAMS
Table 13 (next page) provides an overview for each clu-
ster program about its term, budget, and type of funding,
technology focus, funding periods, maximum funding and
nancing structure of projects. Like in terms of their objec-
tives cluster programs are also quite diverse with regard to
their technical details. Programs very much dier in terms
of the maximum amount of funding for a project and the
duration of funding. Only a few programs support cluster
initiatives to 100 per cent, most programs co-fund initiati-
ves to 50 or 75 per cent of the total project budget.
Table 13: Term of cluster programs and financial aspects11
11 The Cluster Policy Strategy of the Free and Hanseatic City and the Slovakian cluster program
do not feature in this overview as it is no funding program in the narrow sense. It incorporates a
wide array of different funding programs from different ministries and governance levels. For
an introduction to the Cluster Policy Strategy please see the appendix of this report.
56
57
2.3 KEY FINDINGS
The benchmarking of cluster programs has yielded twelve
key ndings which are further detailed in this chapter (see
Table 14). The key ndings provide further insight in the spe-
cic characteristics of the dierent cluster programs and give
guidance for the future development of cluster programs.
2.3.1 DIFFERENT TYPES OF CLUSTER PROGRAMS SERVE
DIFFERENT PURPOSES
There are four principle types of cluster programs. Of course,
there are overlaps between the dierent types and a pro-
gram can feature elements that are also typical of a dierent
type of program. However, the analysis of the objectives and
strategies of the dierent cluster program reveals the follo-
wing main types of cluster programs:
• I)Clusterprogramsthatfocusonregionaleconomic
development:
All programs that t into this category aim at the pro-
motion of regional growth through the development of
business-driven clusters that are internationally competi-
tive. Common to all these programs is a focus on specic
regions that are geographically limited. There are dierent
ways of setting such a limit: programs may set their geo-
graphical limit in terms of administrative borders (e.g. in
Germany the cluster programs of the federal states) or
they dene regions from an economic geography per-
spective, e.g. by referring to “functional regions”12 that do
not have to be congruent with administrative regions and
their borders. In this context the rationale of developing
regional systems of innovation13 is explicitly stressed by
some programs (the Swedish Vinnväxt, Innovation Clu-
sters Piedmont (Italy) and Cluster Development Catalonia
(Spain)).
• II)Clusterprogramsthatfocusonthedevelopmentof
nationalindustries
Characteristic of this type of cluster program is the objec-
tive of developing business-driven clusters that represent
national industries that are internationally competitive.
This type of program supports already developed regio-
nal systems of innovation in their eorts to utilize their
potential for further national and international growth.
The national cluster champions are targeted by this kind
of programs. Often rooted in a regional economic deve-
lopment rationale the programs go beyond the regional
dimension as they try to overcome regional lock-in eects
by promoting national and international collaboration
with other clusters.
• III)Clusterprogramsthatfocusonthecommercialex-
ploitationoftheR&Dpotentialofacountry’seconomy
The third type of cluster programs is characterized by a
focus on the establishment of clusters or centers of ex-
cellence that are either driven mainly by research actors
or are aimed at bridging gaps between the research and
the business sectors. Although these type of program
shares the objective of promoting economic growth with
KEY FINDINGS
1. Different types of cluster programs serve different
purposes.
2. Most cluster programs feature high on the govern-
ment’s agenda.
3. Coordination with other funding programs shows room
for improvement.
4. Internationalization of clusters is considered to be
important, but the relevance of supporting interna-
tionalization of clusters varies between the different
programs.
5. Program owners take over a more active role towards
developing individual clusters.
6. Cluster Management Excellence has become more and
more important in recent years.
7. Monitoring and evaluation is important, but difficult.
8. Cluster policy has become more important with the EU
enlargement.
9. The European Regional Development Fund Approach
has led to good linkages between innovation support
programs and cluster programs.
10. Independent from the kind of support they provide
the cluster programs are equally integrated in national
policies.
11. The cluster programs’ strategic focus of either launch-
ing new clusters or supporting matured ones towards
excellence is equally integrated in the policy agendas
of the EU Member States.
12. The budget provided for cluster programs is inde-
pendent from the gross domestic product p.c. of the
respective country.
Table 14: Overview of key findings
12 A functional region is a territorial unit resulting from the organisation of social and
economic relations in that its boundaries do not reflect geographical particularities
or historical events. It is thus a functional subdivision of territories. The most typical
concept used in defining a functional region is that of labour markets (OECD, 2002:
Redefining Territories. The Functional Regions, p. 11).
13 There is no commonly accepted definition of a regional system of innovation. Common
to all understandings is a set of interacting public and private interests, formal institu-
tions and other organizations that function according to organizational and institutional
arrangements and relationships conducive to the generation, use and dissemination of
knowledge. This set of actors produces pervasive and systemic effects that encourage
companies within the region to develop specific forms for capital that is derived from
social relations, norms, values and interaction within the community in order to rein-
force regional innovative capability and compettiveness (Doloreux, David/Parto, Saaed,
2004: Regional Innovation Systems: A Critical Review, p. 9, United Nations University
INTECH – Institute for New Technologies Discussion Paper Series, Maastricht).
58
the other types of cluster programs, it is dierent as it puts
more emphasis on the development of the research sector
in terms of the commercialization of its R&D results.
• IV)Networkprogramstosupportthecompetitiveness
ofnationalindustries
This type of program is not a cluster program in the nar-
row sense as it promotes the establishment of industry-
driven R&D networks that need not necessarily be rooted
in regional environments, but can be organized nation-
wide. However, a network created through this kind of
program may form the nucleus of a cluster.
The programs that have participated in the policy bench
marking can be structured according to the dierent
categories of programs as follows:
Table 15: Different categories of cluster programs
TYPE OF CLUSTER PROGRAM NAME AND COUNTRY OF CLUSTER PROGRAM
CLUSTER PROGRAMS THAT
FOCUS ON REGIONAL
ECONOMIC DEVELOPMENT
• Cluster Offensive Bayern (Germany)
• Cluster Strategy of Hamburg (Germany)
• Vinnväxt (Sweden)
• Arena (Norway)
• Polish Cluster Support (Poland)
• Regional Growth Agreements (Vaxtarsamningur) (Iceland)
• Cluster Program Lower Austria (Austria)
• Innovation Clusters Piedmont (Italy)
• Cluster Development Catalonia (Spain)
CLUSTER PROGRAMS THAT
FOCUS ON THE DEVELOPMENT OF
NATIONAL INDUSTRIES
• Innovation Networks Denmark
• OSKE – Centre of Expertise Program (Finland)
• Competence Networks Germany
• Go Cluster, Germany
• Norwegian Centres of Expertise (Norway)
• Polish Cluster Support (Poland)
• Grappe d’entreprises (France)
• Les Pôles de Compétitivité (France)
• Competence Centres – Light Structures (Belgium)
• Cooperative Innovation Network Integrated Project (Belgium)
• Cooperation-Clusters (Czech Republic)
• Cluster Development Program (Estonia)
• InnoCluster LT and InnoCluster LT+ (Lithuania)
• COMPETE (Portugal)
• Competitivness Poles (Romania)
• Clusters (Romania)
• Serbian Cluster Development Program (Serbia)
• Cluster Program, Latvia
• Support for the Improvement of International Competitiveness (UR-GE), Turkey
• Support to innovative industrial cluster organizations, Slovakia
• Luxembourg Cluster Initiative
CLUSTER PROGRAMS THAT
FOCUS ON THE COMMERCIAL EX-
PLOITATION OF THE R&D POTEN-
TIAL OF A COUNTRY’S ECONOMY
• Strategic Research Program for Centres of Excellence and Research Clusters
(Iceland)
• Strategic Centres of Excellence (SHOK) (Finland)
• Cluster Development Program of the New Széchenyi Plan (Hungary)
NETWORK PROGRAMS TO
SUPPORT THE COMPETITIVENESS
OF NATIONAL INDUSTRIES
• Zentrales Innovationsprogramm Mittelstand - Netzwerkprojekte (ZIM-NEMO)
(Germany)
59
Norway and Germany, but also France are good examples
of how dierent types of cluster programs with their corre-
sponding purposes are linked with each other:
• AccordingtotheprogramstrategiestheNorwegian
Arena program can act as a qualifying arena for the
Norwegian Centres of Expertise program for regional
clusters with a development potential which have not
yet developed sophisticated cooperative and strategy
fundamentals.
• ManyclustersthatarememberofGo-Cluster(Germany)
are supported by dierent regional cluster programs of
the Federal States in Germany. Furthermore, many mem-
bers of Go-Cluster are also funded by other programs of
the Federal Government such as the Zentrales Innova-
tionsprogramm Mittelstand (ZIM) of the Federal Ministry
of Economics and Technology (BMWi).14 Some clusters
of Go-Cluster are also part of the Spitzencluster-Wettbe-
werb of the Federal Ministry of Education and Research;
a program which supports leading research-driven
clusters in Germany.15 This program setting, which con-
sists of a wide array of programs both from the federal
and the regional level, complements technical assistance
for cluster development through Go-Cluster with grant
funding from other programs.
• ClustersthataremembersofInnovationNetworksDen-
mark can also participate in other innovation support
programs. There are several projects of cluster members
which are nanced by the Danish innovation consortium
scheme, which is a scheme similar to the German Zen-
trales Innovationsprogramm Mittelstand (ZIM) – Netz-
werkprojekte (ZIM-NEMO) program. Some clusters of the
Innovation Networks Denmark initiative also participate
in the three large Danish Strategic Platforms for Research
and Innovation (the Danish SPIR Clusters).
• TheFrenchprogramGrapped’entrepriseswassetupto
bridge the gap between the program Pôle de Compé-
titivité that supports R&D-driven cluster development
and the business sector through the establishment of
business-drivenclusterofGrapped’entrepriseswithlinks
to cluster of Pôle de Compétitivité.
Such linkages can create synergy eects through comple-
mentary objectives and funding lines, but in terms of over-
all eciency and eectiveness as well as less bureaucracy
special coordination eorts on behalf of the program agen-
cies may be required.
2.3.2 MOST CLUSTER PROGRAMS FEATURE HIGH ON THE
GOVERNMENT’S AGENDA
Asked how important their program features in the overall
national or regional policy context16 24 out of 32 experts
assessed its relevance as important or very important in
relation to the overall economic/industrial development
strategy (see Figure 20). Programs were rated high in terms
of importance if they were either embedded in an overall
national strategy or do matter in terms of their budget.
Being embedded in an overall national or regional strategy
seems to be a key factor for the relevance of a cluster pro-
gram as program ocials who have ranked their programs
as either medium relevant or not relevant explained their
assessment with the absence of such a strategy. Some
program ocials explained the low or medium relevance
by referring to small program budgets.
Against this backdrop the importance of a cluster program
has to be understood – in the context of this analysis – in
terms of being embedded in an overall policy strategy and
availabilityofasignicantbudget.Lowrelevanceshould
not be understood as “cluster programs do not matter
fromthegovernment’spointofview”.Allclusterprograms
that were benchmarked in this project matter from the
government’spointofviewandareconsideredasbeing
important from an economic policy point of view.
14 The Zentrale Innovationsprogramm Mittelstand (ZIM) (Central Innovation Program
SME) of the Federal Ministry of Economics and Technology supports innovation activ-
ities through three sub-programs: 1) Support of collaborative projects (ZIM-KOOP), 2)
Support of individual projects of SME (ZIM-Solo) and 3) Support of network projects
(ZIM-NEMO). For further details on the ZIM program please see www.zim-bmwi.de. For
further information about the third sub-program, Support of network projects (ZIM-
NEMO), please see also the appendix to this report.
15 Four out of the ten current Spitzencluster are member of the Go-Cluster initiative. For
more information about the Spitzencluster-Wettbewerb (Leading-edge cluster competi-
tion) please see www.bmbf.de/en/10726.php.
16 The majority of the programs that were benchmarked in this project are programs that
were initiated or are implemented by national agencies or government departments.
Exemptions from this rule include the German federal state programs Cluster Offensive
Bayern and Clusterstrategie Hamburg.
60
COORDINATION: 0= weak > 4= strong
RELEVANCE: 0= not important at all > 4 = very important
2.3.3 COORDINATION WITH OTHER FUNDING PROGRAMS
SHOWS ROOM FOR IMPROVEMENT
High relevance of the cluster program does not necessa-
rily translate into a good coordination with other funding
programs that could provide additional support for the
development of clusters through funding of business, R&D
and infrastructure (including educational infrastructure)
projects. Cluster programs seem to be much better co-
ordinated with other R&D programs (20 programs out of
33 are rated as strongly coordinated with other R&D pro-
grams) than with business and infrastructure programs (11
programs out of 33 are rated as strongly coordinated with
business and infrastructure programs) (see Figure 21-24).
Although the specic national policy context and the spe-
cic objectives of the cluster programs have to be kept in
mind when analyzing the coordination with other programs
in more detail, further attention should be paid in future
analysis to this nding, as a well-coordinated framework of
funding programs can be expected to increase the eci-
ency and eectiveness of public support measures. With a
cluster support program at the core, additional individual
R&D/innovation, business development and infrastructure
programs can address the specic needs of the dierent
actors within a cluster. In this regard strategies, instruments,
time frames and target groups of programs should be coor-
dinated and eorts should be made to limit administrative
burdens for applicants as much as possible.
Figure 20: How important is the cluster program in relation to the overall national
or regional economic/industrial development strategy?
4
3,5
3
2,5
2
1,5
1
0,5
0
IND
NCE
ARENA
KOM
COB
ZIM NEMO
HH
OSKE
SHOK
POL
VAX
RANNIS
Grappe
Lower Austria
KTN
EST
LAT
URGE, TR
CZ
HU
Piedmont
Lux
LT
LT+
Compete
Clusters, RO
CP, RO
Serbia
Belg VIS
Belg LS
Spain Cat
PdC
0= little important
4= very important
61
Figure 21: Coordination of cluster programs with other business
development programs
Coordination with business development programs
Relevance in relation to the overall economic/industrial development strategy
0
1
2
3
4
IND NCE
ARENA
KOM
COB
ZIM NEMO
OSKE
SHOK
POL
VAX
RANNIS
Grappe
Lower Austria
KTN
LAT
URGE, TR
CZ
HU
Lux
Piedmont
LT
LT+
Compete
Clusters, RO
CP, RO
Serbia
Belg LS
Belg VIS
Spain Cat
PdC
EST
COORDINATION: 0= weak > 4= strong
RELEVANCE: 0= not important at all > 4 = very important
4
3,5
3
2,5
2
1,5
1
0,5
0
IND NCE
ARENA
KOM
COB
ZIM NEMO
HH
OSKE
SHOK
POL
VAX
RANNIS
Grappe
Lower Austria
KTN
EST
LAT
URGE, TR
CZ
HU
Piedmont
Lux
LT
LT+
Compete
Clusters, RO
CP, RO
Serbia
Belg VIS
Belg LS
Spain Cat
PdC
62
Figure 22: Coordination of cluster programs with infrastructure programs
(e.g. support of universities and other educational institutions)
0
1
2
3
4
IND NCE
ARENA
KOM
COB
ZIM NEMO
OSKE
SHOK
POL
VAX
RANNIS
FR
Lower Austria
KTN
EST
LAT
URGE, TR
CZ
HU
Lux
Piedmont
LT
LT+
Compete
Clusters, RO
CP, RO
Serbia
Belg LS
Belg VIS
Spain Cat
France PdC
Coordination with infrastructure programs
Relevance in relation to the overall economic/industrial development strategy
COORDINATION: 0= weak > 4= strong
RELEVANCE: 0= not important at all > 4 = very important
63
Figure 23: Coordination of cluster programs with other R&D/innovation support programs
0
1
2
3
4
IND NCE
ARENA
KOM
COB
ZIM NEMO
OSKE
SHOK
POL
VAX
RANNIS
Grappe
Lower Austria
KTN
EST
LAT
URGE, TR
CZ
HU
Lux
Piedmont
LT
LT+
Compete
Clusters, RO
CP, RO
Serbia
Belg LS
Belg VIS
Spain Cat
PdC
Coordination with R&D/innovation programs
Relevance in relation to the overall economic/industrial development strategy
COORDINATION: 0= weak > 4= strong
RELEVANCE: 0= not important at all > 4 = very important
0
1
2
3
4
IND NCE
ARENA
KOM
COB
ZIM NEMO
OSKE
SHOK
POL
VAX
RANNIS
FR
Lower Austria
KTN
EST
LAT
URGE, TR
CZ
HU
Lux
Piedmont
LT
LT+
Compete
Clusters, RO
CP, RO
Serbia
Belg LS
Belg VIS
Spain Cat
France PdC
Coordination with infrastructure programs
Relevance in relation to the overall economic/industrial development strategy
64
2.3.4 INTERNATIONALIZATION OF CLUSTERS IS CONSID-
ERED TO BE IMPORTANT, BUT THE RELEVANCE OF SUP-
PORTING INTERNATIONALIZATION OF CLUSTERS VARIES
BETWEEN THE DIFFERENT PROGRAMS
All program owners consider internationalization of clusters
as an important objective of cluster programs. Internatio-
nal competitiveness of clusters is considered to be a key
element of maintaining and further developing the compe-
titivenessofthecountry’seconomyintheglobalcontext.
From the survey it can concluded that all program owners
agree on the importance of internationalized clusters which
has to be facilitated through support instruments that meet
the needs of the clusters. Consequently, this is reected
by program guidelines and evaluation criteria for project
proposals. However, the programs dier in terms of actual
relevance of internationalization support and instruments
that are used to facilitate internationalization of clusters.
Table 16 provides an overview of the self-assessment given
by program ocials (23 answers) in terms of the relevance
attached to the support of international activities. They
were asked to indicate how prominent the support of inter-
nationalization features in their program:
Table 16: Relevance of the support of international activities of clusters
RELEVANCE NAME OF THE PROGRAM
HIGH Norwegian Centres of Expertise
Polish Cluster Support
Grappe d’entreprises (France)
Cluster Offensive Bayern (Bavarian Cluster Initiative)
Competence Networks Germany
Go-Cluster Germany
Cluster Program, Latvia
Cluster Development Program, Estonia
Innovation Networks Denmark
Cluster Development Program of the New Széchenyi Plan (Hungary)
Cooperation-Clusters (Czech Republic)
Innovation Clusters Piedmont (Italy)
Support for the Improvement of International Competitiveness (UR-GE) (Turkey)
Luxembourg Cluster Initiative
MEDIUM Vinnväxt (Sweden)
ARENA (Norway)
OSKE – Centre of Expertise Program Finland
Strategic Research Program for Centres of Excellence and Research Clusters (Iceland)
Regional Growth Agreements (Vaxtarsamningur) (Iceland)
Competitiveness Poles (Romania)
Support to integration of enterprises in suppliers’ chains or networks (Romania)
Support to innovative industrial cluster organizations (Slovakia)
LOW ZIM NEMO – Zentrales Innovationsprogramm Mittelstand - Netzwerkprojekt
NOT AT ALL –
65
Table 17: Instruments that are used to support international activities of clusters
INSTRUMENTS TO SUPPORT INTERNATIONALIZATION
ACTIVITIES OF CLUSTERS
Name of
the pro-
gram
Training Funding Match-
making
and study
trips
Support
through
export
pro-
motion
agencies
or other
offices
abroad
Coopera-
tion with
other
funding
initiatives
CZECH
REPUBLIC
Cooperation-
Clusters X X X X
DENMARK Innovation Net-
works Denmark X X X X
ESTONIA Cluster Develop-
ment Program X X X
FINLAND OSKE – Centre of
Expertise Program
Finland
X
GERMANY Competence Net-
works Germany X X X
Cluster Offensive
Bayern (Bavarian
Cluster Initiative)
X X X X
ZIM NEMO – Zen-
trales Innova-
tionsprogramm
Mittelstand - Net-
zwerkprojekte
X
HUNGARY Cluster Develop-
ment Program of
the New Széchenyi
Plan
X X X X
ICELAND Regional Growth
Agreements
(Vaxtarsamningur)
(Iceland)
X X
Table 17 gives an overview of the instruments that are used
by the programs to support international activities of
clusters:
66
ITALY Innovation Clusters
Piedmont X X X
LATVIA Cluster Program X X X
LUXEMBOURG Luxembourg Clus-
ter Initiative X X X
NORWAY Norwegian Centres
of Expertise X X X
ARENA (Norway) X
POLAND Polish Cluster
Support X X X
ROMANIA Competitiveness
Poles, Romania X X X
Clusters, Romania X X X
SLOVAKIA Support to innova-
tive industrial clus-
ter organizations
X X
SWEDEN Vinnväxt (Sweden) X X X X X
TURKEY Support for the
Improvement
of International
Competitiveness
(UR-GE)
X X X X X
Programs that attach high relevance to internationalization
activities of clusters typically follow a dedicated strategic
international outlook in terms of their program objectives
and instruments; although, due to e.g. the short period the
program has been existing for now not in all cases this has
translated in a huge number of corresponding activities yet.
Two examples of program that have attached a high priority
on internationalization activities from the very beginning
aretheNorwegianCentersofExpertiseandtheLuxem-
bourg Cluster Initiative:
• BasedonaninternationalstrategytheNorwegian
Centers of Expertise program, for example, is directed
towards regional clusters with an international growth
potential. The focus of support is on adding value to
the innovation and internationalization in the business
sector. NCE clusters receive regular support with interna-
tionalization activities through services provided by the
program management agency Innovation Norway.
• LikewisetheLuxembourgClusterInitiativehasadedica-
ted internationalization strategy which includes:
o International Networking among the cluster
members
o Fostering the collaboration with comparable and/
or complementary clusters, both regionally and
internationally
o Participating in international technology fairs and
brokerage events
o Identifying new business and market opportunities
worldwide
o Facilitating participation in EU projects.
These two examples reect a commonality of all programs
that attach high relevance to internationalization activities
of clusters: the existence of a set of instruments to support
international activities. Specic workshops and events are
typical, but in some cases programs also make budgets for
travel expenses of the cluster management, event organiza-
tion and consultancy services available.
N.B.: Not all cluster programs have provided information on the instruments in detail.
67
Innovation Networks Denmark, the Hungarian Cluster
Development Program, the Cluster Oensive Bayern and
the Polish cluster support are examples of programs that
feature such instruments to dierent extents. In addition to
program specic instruments such as workshops the Nor-
wegian Centres of Expertise program and the Cluster Of-
fensive Bayern network their clusters with the foreign trade
agencies of their country respectively federal state to sup-
port the establishment and development of relationships to
international counterparts of the clusters. This approach is
also followed by programs that attach medium relevance to
internationalization activities such as the Norwegian ARENA
program, the Competitiveness Poles of Romania, and the
Finnish OSKE program.
The reasons why program ocials attach medium rele-
vance to internationalization activities are diverse. In some
cases the medium relevance is due to the young age of the
program (e.g. Strategic Research Program for Centres of
Excellence and Research Clusters and OSKE), but program
ocials indicated that relevance will increase in the future.
In other cases such as ARENA, Vinnväxt the overall objective
of the programs is to set up rstly regional clusters respec-
tively to create regional systems of innovation which later
then should develop into clusters that are internationally
competitive. Also in those cases program ocials indicated
that internationalization activities are already becoming
more important. However, the currently available set of sup-
port instruments appears to be smaller and less frequently
implemented in contrast to programs that attach high
relevance to international activities of clusters.
A similar nding can be stated for the program Innovation
Networks Denmark. In the past internationalization activi-
ties of clusters have not played an important role in calls
for proposals, but in 2010 it was decided by the govern-
ment that the program should support internationalization
through international collaboration projects, increased
participationinEU’sSeventhFrameworkProgram(FP7)
and other international programs and collaboration with
clusters and networks from other countries. This included
also the allocation of money for internationalization activi-
ties of Innovation Networks clusters. With the establishment
of NETMATCH in Denmark in the same year there is now
also a dedicated agency in place that supports internatio-
nalization activities of program beneciaries. NETMATCH is
also partner in the European Enterprise Network.
The importance of tailor-made internationalization support
for clusters through cluster programs is corroborated by the
ndings of a survey of international activities of clusters. 17
The survey analyzed clusters from dierent European coun-
tries including clusters that are supported in the programs
Pôles de Compétitivité, Norwegian Centres of Expertise,
ARENA and Vinnväxt. The study conrmed that interna-
tional activities of cluster managements translate in an
increased international visibility of the clusters. The study
also highlights that good cluster management can overco-
me the barriers of internationalization (e.g. lack of nancing
or capacity); particularly, if an internationalization strategy
exists for the cluster and is implemented by the cluster ma-
nagement. By being guided through an internationalization
strategy cluster managers are able to implement successful
activities for the cluster members. In turn this increases the
willingness of companies and other stakeholders such as
research institutions or government bodies to engage -
nancially in international cluster activities. The development
of international competences of cluster managements and
members of the cluster is therefore an important task that
should be at the heart of cluster programs if they want to
support the internationalization of their clusters. There is a
wide set of instruments available, but it is not the nancial
assistance for projects that matters in the rst place, but
rather the availability of technical assistance, e.g. in the form
of workshops and trainings to support strategy develop-
ment and competencies such as language or cross-cultural
competencies.
The successful internationalization of clusters does not
depend only on a professional and capable cluster ma-
nagement and on support from cluster programs. The legal
framework of a country, both the home country of the
cluster and its “target country”, may also create barriers for
internationalization. This applies in particular to areas such
as tax legislation, labor law, immigration law and company
law. Administrative burdens, e.g. in the case of the registra-
tion of a company, are also often barriers that are frequently
mentioned by cluster managers.
17 Meier zu Köcker, Gerd/Müller, Lysann/Zombori, Zita, 2011: European Clusters Go
International. Networks and Clusters as Instruments for the Initiation of International
Business Cooperation
68
2.3.5 PROGRAM OWNERS TAKE OVER A MORE ACTIVE ROLE
TOWARDS DEVELOPING INDIVIDUAL CLUSTERS
The majority of the interviewed experts conrmed that
individual professional support of cluster managements
through tailor-made services has gained more importance
in recent years. Many program owners were - as a key ele-
ment of their strategic approach to cluster development -
from the very beginning of the program pro-active in terms
of dialogue with clusters, specic criteria for support, pro-
vision of best practice and expert consulting. This includes
in particular the Swedish program Vinnväxt, the Norwegian
programs Norwegian Centres of Expertise and ARENA and
the Polish cluster support scheme. In the case of the other
programs program owners were also aware of the need of
pro-active involvement, but did not put that much empha-
size on it because it did not feature that high in terms of the
strategy of the program. However, these program owners
have become more actively involved in individual cluster
development in the recent past respectively they plan to
do so. There was no program owner who argued that there
is no need for an active role in the development of indivi-
dual clusters, but some argued that more attention should
be paid to this in the context of future program and policy
strategies.
The dierent programs have dierent sets of instruments
available to inuence the development of individual clusters:
• Regularmeetingswithclusters(bothjointmeetingswith
all clusters and bilateral meetings between clusters and
program owners) and workshops are instruments that
are frequently used by most program owners (e.g. Vinnv-
äxt, Norwegian Centres of Expertise and ARENA, Cluster
Oensive Bayern and Innovation Networks Denmark).
• InadditiontotheseinstrumentstheNorwegianpro-
grams NCE and ARENA also oer specic toolboxes for
cluster managers in order to support cluster develop-
ment. In the context of the Innovation Network Denmark
program NETMATCH is currently developing similar
toolboxes for cluster managers.
• PriortotheNGPExcellenceclusterbenchmarkingproject
benchmarking of cluster to facilitate cluster develop-
ment has been used by only two programs: the Polish
cluster support scheme and the terminated initiative
Competence Networks Germany.
• CompetenceNetworksGermanyalsooeredawidear-
ray of dierent working groups and seminars for cluster
managers. They cover topics such as sustainable nan-
cing, innovation management, quality management, IPR,
internationalization, communication and services. In this
regard the program Competence Networks Germany was
dierent compared to other cluster programs as it did
not provide funding to cluster managements, but only
tailor-made services to facilitate individual cluster deve-
lopment. With the establishment of NETMATCH in 2010
the program Innovation Networks Denmark has set up
a similar support organization. In France the association
“France Clusters” oers similar services to clusters that
aresupportedthroughtheGrapped’entreprisespro-
gram, but the services are also available to other clusters.
Several program owners highlighted that cluster managers
have to trust the program owners; otherwise the chances
of having an inuence on the development of individual
clusters are limited. Cluster managers have to consider pro-
gram owners as partners for development and vice versa.
The transparent oer of services and the transparent imple-
mentation of instruments are important for trust building.
The rationale behind a more active, dialogue and guiding
role of program owners in individual cluster development
can be summarized as follows: cluster support is no longer
about the mere establishment of clusters in the rst place,
but about developing excellent clusters that are internatio-
nally competitive and that have an impact on the national
economy.
In this regard an active involvement in the development of
individual clusters has two principal dimensions:
• First,programownersareinterestedinimprovingthe
management performance of the cluster organization
and;
• Second,programownerswanttoguideclustersinterms
of their thematic and strategic focusing.
With regard to the latter cross-fertilization of clusters (brin-
ging together clusters with complementary expertise) is also
an important rationale for an increased pro-active role of
program owners. However, yet the actual cross-fertilization
eorts in the dierent programs are not based on detailed
strategic parameters informed for example through a tech-
nological outlook of the program owners. Workshops, net-
working events and cluster manager forums, regular mee-
tings of clusters with the program agency and in some cases
dedicated calls for proposals and small funds (e.g. the French
programGrapped’entreprises,andtheFinnishOSKE–Cen-
ters of Expertise Program) are typical instruments to facilitate
inter-cluster cooperation for the benet of cross-fertilization.
69
2.3.6 CLUSTER MANAGEMENT EXCELLENCE HAS BECOME
MORE AND MORE IMPORTANT IN RECENT YEARS
Closely related to the interest of program owners in playing
a more active role towards developing individual clusters is
the increased relevance that is attached by program ow-
ners towards cluster management excellence. As already
indicated in the previous key nding: Cluster support is not
about the mere establishment of clusters in the rst place,
but about developing excellent clusters that are internatio-
nally competitive and that have an impact on the national
economy.
Therefore, the majority of program owners argued to focus
programs on cluster excellence instead of “numbers of clu-
sters”. Only clusters with a high potential of development
and high performance should be supported. From the
point of view of some program ocials this requires at the
same time continuous support of the cluster organization
to assist them with quality assurance.
In this context program owners play an important role in
the development of cluster management excellence as the
survey revealed:
• Targeted,need-focusedservicessuchasrelatedwork-
shops and seminars, benchmarking as well as a conti-
nuous strategic dialogue with cluster organizations to
question and further develop strategies and activities are
important elements in this regard as most of the inter-
viewed program owners indicated.
• Labelingofexcellentclusterorganizationswasalsore-
ferred to by several program ocials as an instrument to
promote cluster management excellence. Several pro-
grams are involved in developing such cluster excellence
labels and therefore participated in the European Clu-
ster Excellence Initiative to develop a meaningful set of
quality indicators and peer-assessment procedures for
cluster management. The intention is to develop training
materials and to set up an approach for quality labeling
of cluster management.18
• Financialsupportofclusterorganizationsshoulddepend
on their performance was often mentioned by program
ocials. Only excellent clusters should receive nan-
cial support and program owners should not hesitate
to stop funding if cluster organizations do not live up
to the agreed objectives. The Norwegian, Hungarian,
Swedish and Danish programs are good examples how
this idea can be put into practice: although they com-
mit grant funding for a certain period of years, funding
is provided by a series of installments (stage-funding).
Prior to installments beneciaries have to prove through
an evaluation that they perform according to the grant
agreement (in the Hungarian program a specic accredi-
tation systems decides on further funding). If they do not
perform, the program owner is entitled to stop funding.
Thus, the support of cluster management excellence
through program owners has two dimensions: on the one
hand they should support cluster organizations through
the provision of services targeting cluster management
excellence and on the other hand they should also execu-
te pressure on cluster managements to motivate them to
strive for cluster management excellence.
2.3.7 MONITORING AND EVALUATION IS IMPORTANT, BUT
DIFFICULT
Almost all programs have evaluation instruments and pro-
cesses in place, both with regard to the evaluation of the
program itself and the supported cluster initiatives. All pro-
gram experts consider evaluations as useful tools to impro-
ve the governance of a program and its eectiveness and
eciency. In this context many experts consider formative
evaluations as more useful than ex-post evaluations as they
provide relevant information in the course of the program
implementation which can be used for “real-time” improve-
ments of the program. In contrast to this, ex-post evaluati-
ons are considered to be of more use while planning a new
program or analyzing long-term eects of the support.
The Innovation Network Denmark program and its pro-
gram authority, the Danish Agency for Science, Technology
and Innovation, is a very good example for using annual
performance statistics and econometric impact studies for
monitoring and evaluation purposes. Since 2006 the annual
performance of the clusters that are supported through the
program is measured through quantitative data, e.g. indi-
cators on number of new services or products, number of
participating companies and research institutions, number
18 For further information on the European Cluster Excellence Initiative please see www.
cluster-excellence.eu; for specific information about the cluster management quality
label please see www.cluster-excellence.eu/quality.html.
70
of collaboration projects, usage of services (e.g. matchma-
king) oered by the cluster managements, etc.19 The results
of the annual performance assessment is not only used to
monitor the program performance from a general angle,
but also to identify specic weaknesses of the clusters
which are then addressed by targeted measures develo-
ped by the program management (e.g. training courses
or matchmaking activities). In 2011 the Danish Agency for
Science, Technology and Innovation published an impact
analysis of the program for the rst time. This econometric
analysis, which covered 1,225 companies participating in
the supported clusters, proved - just to give one example of
the results - that the participation of a company in a cluster
increases its capacity to innovate signicantly within a short
period of time (compared to companies that do not partici-
pate in a cluster).20
While in principle the measurement of outputs and results
of a cluster program is not dicult, it is challenging to
measure the economic impact of a program. This applies
both to the impact of the supported cluster initiatives - e.g.
intermsofthecluster’stotalR&Dbudgetgeneratedbyall
its members or the number of innovations that are an eect
oftheclusterinitiatives’activities-andtheoverallimpactof
the cluster support on the national economy. The challenge
of measuring impacts lies in the complexity of the huge ar-
ray of variables that decide on the actual eect of funding.
Economic impacts can be measured e.g. through econo-
metric impact analysis, but one has to be clear about the
limitations: First, economic impacts of support programs
can be measured only after a certain period of time. Nor-
mally the economic impact of activities can be measured
after 5-7 years depending on the number of participating
enterprises in the cluster with concrete registered activities.
In other cases the economic impact using econometric
impact analysis must wait longer and very probably someti-
mes until the program is already terminated. The results can
in the latter case be used to verify the economic impact of
the program, but not be used to redene the strategy of the
program.
Second, due to the complexity of impact measurement a
lot of dierent information has to be collected from the
beneciaries of the program. As surveys and interviews
always require involvement of the beneciaries in terms
of resources one has to balance the cognitive interest in
economic impacts of a program with the interest in redu-
cing the burden for the beneciaries that results from such
comprehensive analysis. In this context, Denmark may
serve as an international best-practice example for measu-
ring economic impacts of public support by utilizing central
civil and business registration systems to collect relevant
information for such analysis. Although this reduces the
burden for companies and organization involved in the ana-
lysis, it cannot fully replace specic surveys and other types
of evaluations as those databases do not contain all data in
detail that is usually required for the analysis or evaluation
of a certain program.
Another best practice example is the policy monitoring
systemofLowerAustria.TheLowerAustrianregionalGo-
vernment, Department for Economy, Tourism and Techno-
logy has developed and implemented a system of dierent
monitoringandevaluationtoolsforLowerAustria’sinnova-
tion policy to receive an understanding of the results and
the impact of state aids and further innovation support
services with the aim to improve single innovation policy
instruments as well as to coordinate the overall regional
innovation system with all involved actors/intermediaries. It
combines regional economic reports and analyses by eco-
nomic research institutes, large scale surveys among com-
panies in the region, evaluation of company projects and
last but not least the monitoring of the regional programs
implemented by intermediaries based on the Balanced
Scorecard method.
Many program ocials experienced in the course of the
program implementation that there is always room for im-
provement when it comes to monitoring and evaluation of
a program and of cluster initiatives. Although most of them
were satised with their approach and instruments they
indicated that they are in a continuous search for a system
that balances the interest in obtaining program governance-
related information with the interest in keeping the bur-
dens for beneciaries that derive from the participation in
monitoring and evaluation as low as possible. However,
none of them had a text-book-solution for the best system
available.
Benchmarking of cluster programs and cluster initiatives
was frequently indicated by program ocials as a very
good tool to support the further development of funding
schemes and activities of beneciaries. Benchmarking
provides standards for performance assessment and thus
19 Danish Agency for Science, Technology and Innovation, 2011: Innovation Network
Denmark. Performance Accounts 2011, Innovation: Analyse og evaluierung 08/2011
20 Danish Agency for Science, Technology and Innovation, 2011: The Impacts of Cluster
Policy in Denmark. An Impact Study on Behavior and Economic Effects of Innovation
Network Denmark
71
helps to identify potential for improvements and best
practice through the comparison with peers. Benchmarking
is an ideal supplement to a formative evaluation and is less
resource intensive than a fully-edged evaluation exercise.
The benchmarking approach of the NGPExcellence pro-
ject has over the years developed into a widely respected
benchmarking standard in Europe.
Benchmarking of cluster programs is a very important tool
to facilitate cross-border learning in the European Union.
Increased collaboration between policy makers on this
topic can contribute to the further development of inno-
vation and cluster policies in the European Union and thus
contribute to the maintenance and further development of
the global competitive position of the European Union and
its Member States.
2.3.8 CLUSTER POLICY HAS BECOME MORE IMPORTANT
WITH THE EU ENLARGEMENT
When looking at the cluster programs of those countries
that have entered the European Union after 2003, it can be
stated that for these “younger” EU member countries the
importance of the cluster programs has increased within
the national and/or regional economic/industrial develop-
ment strategy in comparison to those countries that joined
the EU before 2003. This can be interpreted as a very posi-
tive development, as spill-over eects from the “older” EU
memberstateshave“inamed”thenewcountries’ideas
on how to integrate cluster policy in the overall economic
strategy. Especially newly started cluster programs, such as
the Hungarian cluster program which has been integrated
from the beginning in the new overall long-term economic
development strategy, the New Széchenyi Plan, can beco-
megoodpracticeexamples.Also,Lithuaniaincorporated
cluster policy into the regular innovation policy, trying to
create a favorable environment for innovative clusters and
to develop international clusters. This holistic approach can
encourage the members of the clusters and the cluster ma-
nagement organizations as they receive more appreciation
for their work.
The gure below compares the importance of cluster
programs in relation to the overall national and regional
economic/industrial development strategy among those
countries that have entered the EU before and after 2003.
Figure 24: Importance of cluster programs in relation to the overall national or regional economic / industrial
development strategy
0
0,5
1
1,5
2
2,5
3
3,5
4
How important is the cluster program in relation to the
overall national and regional economic/industrial
development strategy?
0 = not important, 4 = very important
EU entry after 2003
EU entry before 2003
72
0
0,5
1
1,5
2
2,5
3
3,5
4
coordination
with
infrastructure
programs
coordination
with business
development
programs
relevance to
overall
economic
development
relevance to
overall R&D
strategy
0 = low, 4 = high
GDP p.c. below EU27 average
GDP p.c. above EU27 average
2.3.9 THE EUROPEAN REGIONAL DEVELOPMENT FUND
APPROACH HAS LED TO GOOD LINKAGES BETWEEN INNOVA-
TION SUPPORT PROGRAMS AND CLUSTER PROGRAMS
When looking at those cluster programs that have been laun-
ched in 2007 or later, it can be said that the coordination with
business development programs and with other infrastruc-
ture programs of the country is higher as for those cluster
programs that have been launched before 2007 (gure 25).
This can be reasoned by the fact that within the European
Regional Development Fund the support of business net-
works and clusters is one of the objectives in order to pro-
mote regional competitiveness and employment.21 Many of
the cluster programs that have started after 2007 are funded
through ERDF and thus follow a highly designated approach
with regards to the support of cluster development.
Another interesting result can be found when comparing
EU countries below and above EU GDP p.c. average. Taking
a look at the GDP p.c. of the countries whose cluster pro-
grams have been benchmarked, it appears that those coun-
tries that are below the EU GDP p.c. average evaluate their
cluster programs as better coordinated with other business
development programs and infrastructure programs. This
does not mean that these cluster programs are “better”, but
they are linked more closely to other innovation support
measures. Furthermore, these cluster programs rank higher
within the overall economic agenda of the respective coun-
tries than the cluster programs of those countries above the
EU GDP p.c. average.
Figure 25: Comparison of “older” and “younger” cluster programs with regard to the specific
economic environment, and R&D strategy as well as other funding programs
0
0,5
1
1,5
2
2,5
3
3,5
4
coordination
with
infrastructure
programs
coordination
with business
development
programs
relevance to
overall
economic
development
relevance to
overall R&D
strategy
0 = low, 4 = high
program started in 2006 or earlier
program started in 2007 or later
21 Official Journal of the European Union (2006). Regulation (EC) No 1080/2006 of the Europe-
an Parliament and of the Council of July 2006 on the European Regional Development Fund
and repealing Regulation (EC) No 1783/1999. (Article 5).
73
2.3.10 INDEPENDENT FROM THE KIND OF SUPPORT THEY
PROVIDE THE CLUSTER PROGRAMS ARE EQUALLY INTE-
GRATED IN NATIONAL POLICIES
Dierent cluster programs provide dierent kind of sup-
port. Usually, this support is either given through the provi-
sion of funding or the supply of technical assistance. Many
cluster programs provide both of these support services.
Comparing the programs that exclusively provide funding-
with those that supply technical assistance and funding,
it can be stated that in terms of coordination with other
funding programs it makes no dierence, whether a cluster
program focusses on funding only or provides funding and
technical assistance to its clusters. Both types of support al-
low the cluster programs to be coordinated equally strong
with other R&D programs, business development programs
and infrastructure programs.
Figure 26: Embedment of cluster programs in the overall economic development
and R&D strategy with regard to the GDP of the respective country
0
0,5
1
1,5
2
2,5
3
3,5
4
coordination
with
infrastructure
programs
coordination
with business
development
programs
relevance to
overall
economic
development
relevance to
overall R&D
strategy
0 = low, 4 = high
GDP p.c. below EU27 average
GDP p.c. above EU27 average
74
0
0,5
1
1,5
2
2,5
3
3,5
4
coordination
with R&D
programs
coordination
with
infrastructure
programs
coordination
with business
development
programs
relevance to
overall
economic
development
relevance to
overall R&D
strategy
0 = low, 4 = high
establishment of new cluster organizations
further development of already existing
matured cluster organizations
2.3.11 THE CLUSTER PROGRAMS’ STRATEGIC FOCUS OF
EITHER LAUNCHING NEW CLUSTERS OR SUPPORTING MA-
TURED ONES TOWARDS EXCELLENCE IS EQUALLY INTEGRAT-
ED IN THE POLICY AGENDAS OF THE EU MEMBER STATES
Cluster programs can focus on elevating new clusters or on
strengthening matured ones towards excellence, or cluster
programs can provide both services. When comparing the
cluster programs that focus exclusively on the establish-
ment of new clusters with those that focus exclusively
on the further development of matured clusters towards
excellence clusters, it can be asserted that both approaches
rankhighontherespectivecountries’innovationpolicy
agendas. This is conrmed by the gure below showing
only very slight dierences between the two groups.
Figure 27: Comparison of cluster programs that provide funding only and cluster
programs that provide funding and technical assistance
0
0,5
1
1,5
2
2,5
3
3,5
4
coordination
with R&D
programs
coordination
with
infrastructure
programs
coordination
with business
development
programs
relevance to
overall
economic
development
relevance to
overall R&D
strategy
0 = low, 4 = high
establishment of new cluster organizations
further development of already existing
matured cluster organizations
75
2.3.12 THE BUDGET PROVIDED FOR CLUSTER PROGRAMS
IS INDEPENDENT FROM THE GROSS DOMESTIC PRODUCT P.C.
OF THE RESPECTIVE COUNTRY
The cluster programs analyzed in this study dispose of at
least 1 Million Euros per year (except for Serbia). Most of
them have a budget of between 5 and 12 Million Euros per
year. Three programs come close or are above 100 Million
Euros in their yearly budget. The budget that is spent for the
cluster programs is independent from the gross domestic
product p.c. of the respective country. The gure below
shows that the countries below the EU GDP p.c. average
(marked yellow) and the countries above the EU GDP p.c.
average (marked green) are equally spread with regard to
their yearly budget of the cluster programs. However, compa-
ring the budgets of the dierent programs is rather dicult
as the objectives of the programs are very dierent from
each other, e.g. some of the cluster programs provide exten-
sive budget for R&D investment, others supply budget for the
development of cluster management organizations only.
Figure 28: Comparison of cluster programs that focus exclusively on the establishment of new cluster organization and
cluster programs that focus exclusively on the further development of already existing cluster organizations
0
0,5
1
1,5
2
2,5
3
3,5
4
coordination
with R&D
programs
coordination
with
infrastructure
programs
coordination
with business
development
programs
relevance to
overall
economic
development
relevance to
overall R&D
strategy
0 = low, 4 = high
establishment of new cluster organizations
further development of already existing
matured cluster organizations
0
0,5
1
1,5
2
2,5
3
3,5
4
coordination
with R&D
programs
coordination
with
infrastructure
programs
coordination
with business
development
programs
relevance to
overall
economic
development
relevance to
overall R&D
strategy
0 = low, 4 = high
establishment of new cluster organizations
further development of already existing
matured cluster organizations
76
2.4 LESSONS LEARNED AND THE IMPACT ON
PROGRAM DEVELOPMENT
Program ocials were asked to report the three key lessons
that they have learned since the inception of their program.
Although lessons learned are always program-specic as
the national policy and economic context and the age of
the program matter, one can nonetheless identify some ge-
neral key lessons learned that apply to all programs. Those
key lessons learned can be dierentiated into key lessons
that have been learned in terms of the program strategy
(see Table 18) and into key lessons that have been learned
in terms of instruments (see Table 19).
0,10
1,00
10,00
100,00
1.000,00
Million €
(Logarithmic scale)
Serbia
KOM
LV
VAX
LT
Lower Austria
EST
ARENA
Spain Cat
Clusters, RO
COB
NCE
ZIM NEMO
IND
LT+
Grappe
CP, RO
CZ
Piedmont
Belg VIS
POL
Belg LS
KTN
Compete
HU
PdC
Figure 29: Estimated yearly budget of the cluster programs (in Million €), (Cluster programs of countries below EU GDP
average are marked yellow. Cluster programs of countries above EU GDP average are marked green.) 22
22 Please be aware that this figure displays the budget for individual cluster programs only. It does not
show the total budget that each country spends for cluster programs.
77
The majority of program ocials reported in the survey that
they have already translated their corresponding lessons
learned into adaptations of their programs. This concerned
in particular
• Theimplementationofnewsupporttoolsandmeasures;
• Anincreasedattentiontowardsclustermanagement
excellence, e.g. through a more pro-active engagement
with cluster managements by means of dialogue or
benchmarking exercises;
• Consolidationofthesupported“clusterlandscape”and
reduction of funding rates for cluster managements.
Most cluster programs will continue in the next years wi-
thout signicant changes. In some cases parliamentary
elections and ongoing or upcoming elections may have an
impact on the program conguration.
KEY LESSONS LEARNED WITH REGARD TO THE INSTRUMENTATION OF THE PROGRAM
1. Mutual exchange between cluster managements and networks of cluster managers should be supported through adequate instruments.
2. Cluster managements should get support for the development of value-adding services that can be offered to the cluster members.
3. Cluster managements should get support with the development of cluster strategies.
4. Long-term commitment among the cluster members should be supported.
5. Internationalization of clusters should be part of the cluster strategy and be supported by the program owner.
6. Evaluation and monitoring is crucial for the success of the cluster program. Measuring economic and other types of impacts is
very difficult, but should be pursued.
7. Other funding instruments than grants should be also used to support cluster development; e.g. technical assistance or capital
investments in organizations.
8. Quality labeling of cluster organizations should feature as an integral part of cluster programs
9. The program should activate competition among the clusters benefitting from the program by setting up e.g. annual contests.
KEY LESSONS LEARNED WITH REGARD TO THE PROGRAM
STRATEGY
1. Long-term support is key when clusters should be set up sustainably
2. The cluster program should be embedded in a regional and/or national cluster policy respectively economic development strategy.
3. Funding schemes should be flexible in order to be able to adjust support to changing economic environments smoothly and quickly.
4. Clusters have different characteristics depending on their context (e.g. history of origin, emerging vs. traditional industries). This
requires different support mechanisms.
5. Funding of clusters should depend on their performance.
Table 18: Lessons learned with regard to the program strategy
Table 19: Lessons learned with regard to the instrumentation of the program
78
Clusters are individuals who need individual support for
sustainable growth and enhanced competitiveness in order
to become world-class clusters that maintain and extend
theglobalcompetitivenessoftheEuropeanUnion’secono-
my – that is the most important conclusion from the bench-
marking of 261 cluster management organizations.
Support of cluster development by means of cluster pro-
grams should therefore be more than just providing grants
for oce and sta funding of cluster management orga-
nizations. It is also about providing tailor-made technical
assistance for cluster management organizations in order
to support their eorts with the provision of needs-driven
and value-adding products and services for the cluster
members. And it is also about developing favourable frame-
work conditions in which clusters can ourish through the
coordination of cluster policies and programs with other
relevantpolicyareasandprograms.Last,butnotleast:
cluster programs should focus on the support of cluster
management excellence. Only cluster management organi-
zations that are excellently managed can develop and oer
the support to cluster members that they need to maintain
and extend their global competitiveness.
The results of the benchmarking of 34 cluster programs
from 24 countries, which are Austria, Belgium, Czech Repu-
blic, Denmark, Estonia, Finland, France, Germany, Hungary,
Iceland,Italy,Latvia,Lithuania,Luxembourg,Norway,Po-
land, Portugal, Romania, Serbia, Slovakia, Spain, Sweden,
Turkey and United Kingdom demonstrate that there are
many good cluster programs not only in the European Uni-
on Member States but also in Associated States. All these
programs support the above briey sketched objectives
forward looking cluster programs should have. However,
there is always room for improvement. In order to improve
their eectiveness and eciency these programs can both
learn from each other from the results cluster program
benchmarking and from the results of the cluster bench-
marking. Certainly, these results provide also inspiration for
many other cluster programs that have not participated in
the NGPExcellence project.
In the following seven policy recommendations are presen-
ted that are based on the ndings of the cluster and cluster
program benchmarking. They provide guidance for the
further development of cluster programs and shall contri-
bute to the evolution of outstanding clusters that are driven
by excellent cluster management organizations:
1.Improvecoordinationofclusterprogramsandother
relevantfundingprograms.Ideallythereshouldbe
onlyalimitednumberofcoordinatedclustersup-
portprograms that target dierent types of clusters.
With a limited number of cluster support programs that
support the establishment of cluster management orga-
nizations at the core of an overall cluster development
strategy additional individual R&D/innovation, business
development and infrastructure (e.g. in the educational
sector) programs can address the specic needs of the
dierent actors within a cluster. In this regard program
strategies, instruments, time frames and target groups of
programs should be coordinated and eorts should be
made to limit administrative burdens for applicants as
much as possible. Programs should also be aligned with
policies that pursue an improvement of the framework
conditions which have an impact on the development of
a cluster (e.g. educational or labour policies).
2.Tailor-madeassistanceforclustersshouldhavea
highrelevanceintheprogramstrategy. The econo-
mic impact of a cluster depends not only on its size and
maturity. It is also the technology domain of the cluster
that matters in terms of the structure, the governance
and the performance of a cluster. Cluster programs there-
fore should take the dierent frame-work conditions of
industries and technology domains into account through
assistance that is tailor-made according to the specic
needs of a cluster.
3.Programsshouldputemphasisonclustermanage-
mentexcellence. Cluster support is not about the mere
establishment of clusters, but about developing excel-
lently managed clusters that are internationally compe-
titive and that have an impact on the national economy.
In this context is it important to support cluster manage-
ment through targeted, need-focussed services such
as relevant workshops and seminars, benchmarking as
well as a continuous strategic dialogue to question and
furtherdevelopstrategiesandactivities.Labellingofex-
cellent cluster managements is another important aspect
in this context; not only because it creates more visibility
for a cluster, but also because it encourages cluster ma-
nagements to provide excellent management in order to
earn and preserve the label.
4.Clusterprogramsshoulddevelopworld-classclusters
inindustrysectorsthatareinternationallycompeti-
tive. Without limiting the attention to the development
of clusters for the purpose of regional economic deve-
lopment, there should also be programs that support
3 POLICY RECOMMENDATIONS
79
the development of clusters that are internationally
competitive. The support should focus on those indu-
striesinwhichacountry’seconomyshowspronounced
comparative advantages on the global market. Cluster
management excellence should be a key priority of such
programs.
5.Long-term,butexiblesupportofclustersisre-
quired.In order to meet the specic development
conditions of clusters support should be provided on a
long-term basis of ve to ten years. Furthermore, pro-
gram requirements and processes should not only be
less bureaucratic, but also exible enough to respond
quickly to changing economic and technology envi-
ronments in which clusters are operating in.
6.Monitoringandevaluationoftheresultsandimpacts
ofaprogramisimportantandshouldbedoneina
smartandpurposefulmanner. From the very begin-
ning the program should be based on clear targets that
can be measured through a purposeful set of indicators
that provides information relevant to the implementati-
on processes. The implementation of a program should
be accompanied by a formative evaluation which pro-
vides recommendations for program adaptation on a
continuous basis. It is important that there is a balance
between the cognitive interest of program owners and
policy makers and the burdens for beneciaries that
result from monitoring and evaluation.
7.Dierentindustrysectorsneeddierentsupportfor
internationalizationactivities. There are huge die-
rences between industry sectors when it comes to the ef-
fect of the work of cluster managements on international
activities of SME. The promotion of cluster management
activities for internationalising the cluster should there-
fore take the specic framework conditions of industry
sectors into account. Corresponding instruments should
be developed by program owners to provide need-
based support for cluster managements.
80
THE AUTHORS
THOMAS LÄMMER-GAMP is Director of the European Secretariat for Cluster Analysis (ESCA) at
VDI/VDE Innovation + Technik GmbH in Berlin, Germany. Being an expert for the development
and implementation of public funding programs, he has been working with regional and econo-
mic development policy topics for more than twelve years. Thomas has gathered his experience
at two international consultancy companies and the Saxonian State Ministry of Economic Aairs
andLabor(GermanFederalStateGovernment).Priortohiscurrentengagementheservedfor
two years as a technical advisor for international cooperation at the Department of Science and
TechnologyoftheRepublicofSouthAfrica.ThomasholdsaMaster’sdegreeinpoliticalscience,
law and sociology from the University of Göttingen.
Email: tlg@vdivde-it.de
DR. GERD MEIER ZU KÖCKER is head of the Institute for Innovation and Technology (iit Berlin)
and holds a PhD in mechanical engineering. Currently he is serving on various advisory boards,
appointed by dierent European Member States and the European Commission. Gerd has led
many innovation and cluster projects in several parts of the world, has widely written about in-
novation, cluster and technology transfer issues and is a frequent speaker on innovation policy
and cluster in Europe, North America, Africa and Asia.
Email: mzk@vdivde-it.de
DR. THOMAS ALSLEV CHRISTENSEN has been working as Head of the Department for In-
novation Policy at the Danish Ministry for Science, Technology and Innovation since 2005. He is
head of the secretariat of The Danish Council for Technology and Innovation and responsible for
Danish innovation policy programs such as the Innovation Networks Denmark Program, the Da-
nish Program for Innovation Projects, the Danish Industrial PhD Program, the Danish Incubator
Program and the Danish GTS-system (Danish RTO institutes). Thomas has previously worked at
theNordicCouncilof Ministers, the Ministryof EconomicAairs and the PrimeMinister’sOf-
ce. He has also been external associate professor at the University of Copenhagen. He holds a
Master’sdegreeineconomicsfromtheUniversityofCopenhagenandaPhDdegreeininterna-
tional economics from Copenhagen Business School.
Email: tac@.dk
LYSANN MÜLLER has been working as a consultant at the international technology coopera-
tion and cluster policy department of VDI/VDE Innovation + Technik GmbH in Berlin, Germany
since 2005. She has specialized in innovation policy and has worked as analyst of innovation
systems.BeinginvolvedwithEuropean project management forten years Lysann has grown
her professional experience in national and European R&D policy and international technology
transfer. Prior to her current engagement she was preoccupied with observing and analyzing
European legislative processes and initiatives for the Association of German Engineers in
Brussels,Belgium.LysannholdsMaster’sdegreesinLinguisticsandBusinessAdministration.
Email: lysann.mueller@vdivde-it.de