UFU, Alm.del - 2015-16 - Endeligt svar på spørgsmål 168: Spm. om ministeren vil fremsende relevante evalueringer af Globaliseringspuljen 2007-12, til Uddannelses- og forskningsministeren

Uddannelses- og Forskningsudvalget 2015-16
UFU Alm.del
Offentligt

Effects of participation in

EU framework programmes

for research and technological

development

– for researchers, institutions and

private companies in Denmark

Research and Innovation: Analysis and Evaluation 3/2015

UFU, Alm.del - 2015-16 - Endeligt svar på spørgsmål 168: Spm. om ministeren vil fremsende relevante evalueringer af Globaliseringspuljen 2007-12, til Uddannelses- og forskningsministeren

Effects of participation in

EU framework programmes

for research and technological

development

– for researchers, institutions and

private companies in Denmark

Research and Innovation: Analysis and Evaluation 3/2015

UFU, Alm.del - 2015-16 - Endeligt svar på spørgsmål 168: Spm. om ministeren vil fremsende relevante evalueringer af Globaliseringspuljen 2007-12, til Uddannelses- og forskningsministeren

Published by

Ministry of Higher Education and Science

Bredgade 40

1260 Copenhagen K

Denmark

Telephone: +45 33929700

E-mail: [email protected]

www.ufm.dk

Cover

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Layout

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Free text

Publication can be downloaded at ufm.dk/publikationer or ufm.dk/en/publications

ISBN: 978-87-93151-65-9

ISBN: (electronic publication): 978-87-93151-64-2

ISSN: 2246-6762

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Contents

Foreword

Executive Summary

Purpose of this report

Main findings

Conclusion

1. Introduction

1.1. EU’s Sixth and Seventh Framework Programmes for Research

1.2. Horizon 2020 – EU’s Eighth Framework Programme

2. Overall Danish participation in FP6 and FP7

2.1. Main findings

2.2. Overview of Danish participation in FP6 and FP7

2.3. Types of participating organisations

2.3.1. Danish universities

2.3.2. Danish private companies

2.3.3. Danish research and technology organisations (RTOs)

2.4. Danish participation in FP6 and FP7 by region

2.5. The development of Danish participation in FP6, FP7

and Horizon 2020

2.6. Danish participation in ERC excellence projects (FP7)

2.7. Danish participation in Marie Curie mobility projects (FP7)

2.8. Denmark compared to other countries

2.9. Denmark’s international collaborators

3. Importance of FP6/FP7 – perceived effects

3.1. Main findings

3.2. Methodology

3.3. Effects for universities and GTS institutes

3.4. Effects for universities

3.5. Effects for private companies

4. Economic impact on FP6/FP7-participating companies

4.1. Main findings

4.2. Characteristics of participating companies

4.3. Impact assessment

4.3.1. The matching sample

4.3.2. Results

4.4. Why the missing statistical difference in impact?

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

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5. Private companies’ use of FP6, FP7 and the Danish

national research and innovation system

5.1. Main findings

5.2. The companies’ use of the Danish research and innovation system

5.3. The most popular Danish research and innovation schemes

5.4. The entrance to the Danish research and innovation system

5.5. Conclusion

6. Bibliometric performance analysis of publications from

Danish researchers linked to FP6 and FP7

6.1. Main findings

6.2. Results

6.2.1. Publication performance FP6 and FP7

6.2.2. Benchmark analyses

6.2.3. Bibliometric analysis of publication sets linked to

programme themes under FP6 and FP7 programmes

6.3. Methods

7. The individuals participating in FP6 and FP7

7.1. Main findings

7.2. Characteristics of the individuals participating in FP6 and FP7

7.2.1. Gender balance

7.2.2. Age

7.2.3. Field of science

7.2.4. Citizenship

7.2.5. Career

7.2.6. Sector

7.3. Methods

7.3.1. Collection of data on individual level

7.3.2. Method for comparison – selection of

comparable individuals

8. Annexes

8.1. Annex 1 – Participation of Denmark and

private companies in FP6 and FP7

8.2. Annex 2 – Individual participation

8.2.1. Age

8.2.2. Field of science

8.2.3. Career

8.2.4. Sector

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

Foreword

An international outlook is essential for research and innovation projects to have a

high impact. EU’s framework programmes for research and technological develop-

ment therefore play an important role for the Danish research community and busi-

ness environment. This means not only EU funding of research and development

activities in Denmark but also the opportunity to cooperate with excellent foreign

research and innovation environments, and thereby to have access to new know-

ledge and new markets.

Competition for EU funding is tough, but there are positive measurable effects

coming out of the participation in EU projects. The impact of scientific publications

linked to EU’s earlier framework programmes is outstanding and above the inter-

national performance levels. This should give researchers an extra incentive to look

into the possibilities for cooperation that are funded by Horizon 2020, EU’s 8th

framework programme for research and innovation.

Another crucial element in addressing societal challenges and creating growth

and jobs is collaboration among various actors in research and innovation projects.

Cooperation among universities, GTS institutes and the business community is an

important characteristic of the EU framework programmes. This is even more the

case with the increased focus on innovation and market opportunities in Horizon

2020.

A constant focus is needed on bridging the gap between research and commer-

cial markets through innovative new solutions. EU’s framework programmes also

provide an excellent opportunity for Danish companies in this context. Between a

quarter and a third of the Danish participants in EU’s framework programmes come

from the private sector. Those participating are active in the European or global

markets; they increase revenue at a fast pace, and they employ intensively highly-

skilled workers.

Horizon 2020 provides funding to the innovation leaders. However, with a

stronger focus on the commercial exploitation and delivery of solutions to end

users, the programme has now become even more relevant for companies within

manufacturing and services. To a much higher degree than previously, researchers

have to reach out to the private sector. If they want to succeed, they have to design a

common approach for how to address major societal challenges within, for example,

the bioeconomy or health and demographic development. I therefore expect an

increase in the participation of private companies in Horizon 2020.

Continued funding of research and innovation activities needs to be backed

up by knowledge about the outcome of these activities. This report gives unique

knowledge about the effects of Danish projects funded by previous EU framework

programmes. It also shows a number of valuable and interesting effects that partici-

pation in European research and development projects has had for Danish research-

ers and companies. I hope that this report will encourage the Danish research and

business communities to increase their participation in Horizon 2020.

Esben Lunde Larsen

Minister of Higher Education and Science

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

Executive Summary

Purpose of this report

Danish institutions and companies have participated 1,646 times in 1,125 grants in

EU’s Sixth Framework Programme for Research, Technological Development and

Demonstration (FP6) and 2,754 times in 2,011 grants in EU’s Seventh Framework

Programme for Research and Technological Development (FP7). On an annual ba-

sis, Danish researchers and firms have received EUR 79 million per year from FP6

and EUR 151.5 million per year from FP7.

The purpose of this report is both to describe this participation and to study the

effects that FP6/FP7 participation has had for Danish institutions, researchers and

companies, both with regard to experienced effects and measurable effects. FP7’s

successor, EU’s Framework Programme for Research and Innovation (Horizon

2020), has a budget of almost EUR 80 billion. This has grown substantially in both

nominal and real figures compared to FP6 and FP7. Researchers, institutions and

companies are invited to take the effects described in this report into consideration

when considering participating in Horizon 2020.

This report analyses the effects of participating Danish institutions and compa-

nies in three parts: 1) What effects do representatives from universities, GTS insti-

tutes and companies experience following their participation in FP6 and FP7?, 2)

What economic effect can be measured for private companies participating in FP6/

FP7?, 3) What is the scientific impact of FP6- and FP7-linked publications?

This report describes the overall participation of Danish institutions and compa-

nies; private companies’ use of FP6, FP7 and the Danish research and innovation

(R&I) system, and the individuals participating in FP6 and FP7.

Main findings

A very interesting and somewhat surprising finding of the bibliometric analysis is

the outstanding performance level of the FP6- and, in particular, the FP7-linked

publications. The publications are above (and in some cases far above) international

performance levels, when looking at citations. This analysis shows that FP7-linked

publications have a higher impact than even publications linked to The Danish

Council for Independent Research and The Danish National Research Foundation.

Another main finding from the bibliometric analysis is that it is not only publica-

tions linked to the European Research Council (ERC) that have a high impact but

also publications linked to strategic programmes under both FP6 and FP7, such as

health and environment.

The main FP6/FP7 participants in Denmark are universities and research institu-

tions, followed by private companies and, finally, public authorities. Three Danish

universities (University of Copenhagen, Aarhus University and Technical University

of Denmark) alone account for almost one third of total EU contribution to Den-

mark from FP6 and half of total EU contribution from FP7.

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

The Danish share of total EU contribution from the EU framework programmes

has been stable at 2.37 per cent from FP6 and 2.36 per cent from FP7. The yearly

nominal contribution rose by more than 90 per cent from FP6 to FP7 – from EUR

79 million annually in FP6 to EUR 151.5 million annually in FP7. EU contribution

from Horizon 2020 to Denmark was 2.30 per cent in the first year of Horizon 2020.

Participants from institutions based in the Capital Region received almost two-

thirds of total EU contribution to Denmark from both FP6 and FP7. However the

Central and North Denmark Regions increased their share of EU contribution to

Denmark in FP7.

With regard to the gender balance, we can see that the proportion of men partici-

pating in both FP6 and FP7 is higher than the proportion of men within research in

general. The higher proportion of men in FP6 and FP7 is most likely related to the

fact that natural science and technical science, which both have a higher proportion

of men than other sciences, are overrepresented in FP6 and FP7 compared to hu-

manities, for example.

With regard to internationalisation, the percentage of foreigners from Danish

institutions and companies participating in FP6 or FP7 is higher than the general

level of foreign researchers in Denmark. The PhD students are the group with the

largest share of foreigners participating in FP6/FP7, also compared to PhD students

in Denmark in general. 11 per cent of participating researchers and 42 per cent of

participating PhD students in highly-skilled positions are foreigners.

FP6/FP7 companies are highly unusual companies compared to the average

Danish company. On average, they gain about 40 per cent of their revenue through

exports, grow revenue at a fast pace and employ intensively highly-skilled workers.

Large companies participate frequently in FP6/FP7. The largest share of partici-

pants is found in the following industries: manufacturing, professional, scientific

and technical activities.

EU programmes are an integral part of the overall landscape for public funding

of research and innovation in Danish companies, as half of the companies partici-

pating in FP6 and FP7 have also participated in the Danish research and innovation

(R&I) system.

Companies participating in FP6 and FP7

do not significantly outperform compa-

rable non-participating companies. Typically, these companies have already suc-

ceeded in establishing international ties and breaking through into international

markets. Regardless of participation in FP6/FP7 projects, they are well-functioning

companies that do not seem to rely crucially on a particular funding body of pub-

lic-private research partnership projects.

The main finding from the survey analysis is that Danish companies perceive

funding of activities that would not otherwise have been implemented as the most

important effect, closely followed by cooperation with foreign universities and re-

search organisations and access to new knowledge. Small companies experience

greater effects than medium-sized companies and large companies. As many as half

of the participating companies say they have launched new products or services as a

result of their participation in FP6 and FP7 projects.

Horizon 2020 has a greater focus on funding activities that will create jobs and

growth in Europe. However, the first figures from Horizon 2020 show that Danish

companies participate less in projects financed by Horizon 2020 than those fi-

nanced by FP6 and FP7, but it is too early to identify a trend.

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

Building new European networks is the most important effect of participating in

FP6/FP7 for GTS institutes and universities, closely followed by funding of activities

that otherwise would not have been implemented, and cooperation with excellent

foreign research and innovation environments. Differences in the perception of the

most important effects between universities and GTS institutes seem quite small,

which could indicate that universities and GTS institutes experience similar effects

despite differing main objectives in their normal activities.

Conclusion

Overall it can be concluded that researchers benefit from positive effects in the form

of bibliometric impact. The scientific impact of FP6- and, in particular, FP7-linked

publications is outstanding. Companies themselves experience substantial effects,

though these are not statistically significant when compared to similar non-partici-

pating companies. Universities and GTS institutes also experience considerable ef-

fects, in particular regarding new European networks and funding of activities that

would not otherwise have been funded.

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

1. Introduction

The purpose of this report is both to describe participation in FP6 and FP7 and to

study the effects this participation has had for Danish institutions, individual re-

searchers and companies, with regard to experienced effects and measurable effects.

The report focuses on universities, GTS institutes and private companies, as these

are the three major groups participating in FP6 and FP7. Other participants, such as

hospitals, university colleges, non-governmental organisations (NGOs) and public

bodies such as municipalities, also play an important role in the projects they partic-

ipate in.

Danish institutions and companies have participated 1,646 times in 1,125 grants

in EU’s Sixth Framework Programme for Research, Technological Development and

Demonstration (FP6) and 2,754 times in 2,011 grants in EU’s Seventh Framework

Programme for Research and Technological Development (FP7). On an annual ba-

sis, Danish researchers, companies and other participating entities have received

EUR 79 million per year from FP6 and EUR 151.5 million per year from FP7 for

their participation in EU projects.

Danish participation in FP6 and FP7 was previously studied by Technopolis in

2010

, where the financial, scientific and commercial benefits of Danish participa-

tion were assessed and the strategies employed in relation to framework programme

participation were identified. Therefore, this study does not assess the benefits

occurring directly from project participation, but the effects of participation on the

institution or company. The study found that most of the outputs sought and pro-

duced through FP projects were research outputs (such as publications, conferences

and trained personnel) and that there is far less activity in relation to the production

of innovation outputs (such as new products, patents and licenses). This was to be

expected, given the pre-competitive nature of the research carried out within the

framework programmes.

The European Commission evaluates the framework programmes on a regular ba-

sis. Both ex-post evaluations of FP6

and an interim evaluation of FP7, as well as an-

nual monitoring reports on FP7

, are available. These look at the implementation of

the framework programmes, including excellence in research, participation of small

and medium-sized companies, outreach and communication to European citizens

and leverage effects on overall EU research and innovation efforts. The interim eval-

uation of FP7 finds, amongst other things, that the European Research Council ap-

pears to have been successful in reaching its objectives of excellence and attracting

top researchers. The Expert Group finds, however, that the involvement of industry,

especially SMEs, in FP7 is “far from optimal”

Chapter 2 of this report describes the Danish participation in terms of how much

funding has been awarded to Danish participants, the types of Danish participants

http://ec.europa.eu/research/evaluations/pdf/archive/fp7-evidence-base/national_impact_

studies/evaluation_of_danish_participation_in_fp6_and_fp7_-_main_report.pdf

http://ec.europa.eu/research/reports/2009/pdf/fp6_evaluation_final_report_en.pdf

https://ec.europa.eu/research/evaluations/index_en.cfm?pg=home

page 68, https://ec.europa.eu/research/evaluations/pdf/archive/other_reports_studies_and_

documents/fp7_interim_evaluation_expert_group_report.pdf#view=fit&pagemode=none

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

that have participated, and how Denmark has fared in the competition for funds

over time and compared to other countries.

Chapter 3 sheds light on what effects Danish universities, GTS institutes and Dan-

ish companies perceive to be the most important to them from their participation in

projects funded by FP6 and FP7. This is done by means of a survey analysis.

Chapter 4 is an impact assessment of company participation in FP6 and FP7 pro-

jects. Using detailed employer-employee-linked data spanning from 2000 to 2012,

the participating companies are described relative to other companies. Then a five-

year forward-looking impact assessment of company participation in projects initi-

ated between 2002 and 2008 is performed.

Chapter 5 looks at the participation of Danish companies in FP6/FP7 and how

this participation is linked to their participation in the Danish R&I funding system.

Chapter 6 analyses the impact of Danish scientific publications that are linked to

FP6 or FP7 funding. In order to look at the impact, we have identified citations be-

longing to scientific publications with at least one Danish author. These results are

compared to the results of the bibliometric analyses from the previous evaluations

of the Danish National Research Foundation (DNRF) and the Danish Council for In-

dependent Research (DFF). Finally the analyses also explore the impact at the level

of programme themes under FP6 and FP7.

Chapter 7 analyses the characteristics of individuals participating in FP6 and FP7.

Detailed employer-employee-linked data spanning from 2000 to 2012 are used to

describe participating individuals in projects relative to other comparable individu-

als in the general population working with research and development (R&D).

1.1.

EU’s Sixth and Seventh Framework Programmes for Research

The EU’s Sixth Framework Programme for Research, Technological Development

and Demonstration (FP6) ran from 2002 to 2006 and had a total budget of almost

EUR 18 billion, while the Seventh Framework Programme for Research and Tech-

nological Development (FP7) ran from 2007 to 2013 with a budget of more than

EUR 50 billion. The two framework programmes thus differed considerably in both

length of programme period and budget size. Also, competition has increased: over

the years, the European Union has become larger and the Danish proposers collab-

orate and compete with legal entities from more and more member states and coun-

tries associated with the framework programmes.

FP6 and FP7 had different structures, but they built on each other. The main

objectives of FP6 were to contribute to the creation of the European Research Area

(ERA) and to strengthen the competitiveness of the European economy. Not all ar-

eas of science and technology were covered. FP6 consisted, among other things, of

seven priority thematic areas as well as a specific programme to address the struc-

tural weaknesses of European research. The thematic areas with the largest budgets

were: Information society technologies; Life sciences, genomics and biotechnology

for health, and Sustainable development, global change and ecosystems.

FP7 consisted of four specific programmes, with COOPERATION covering seven

key thematic areas. FP7 had the aim of responding to Europe’s needs in terms of

jobs and competitiveness, and maintaining leadership in the global knowledge econ-

omy. FP7 introduced the European Research Council, which funds basic research,

and included new measures to ensure greater participation from industry and to

strengthen the international dimension in the programmes. The individual areas

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

with the largest budgets were: Information and Communication Technologies; the

European Research Council, and Health.

EU research framework programmes are based on open calls for proposals. EU

funding of the successful applications comes in the form of an EU contribution to

the participants’ project-related costs, based on specific reimbursement rates. There

are a number of different project types or “funding schemes” in EU framework pro-

grammes, such as collaborative research projects, networks of excellence, and co-

ordination and support projects. These differ in the number of participants, budget

size, EU contribution and main purpose.

In tables 1.1 and 1.2, the overall structure of FP6 and FP7 is outlined:

TABLE 1.1

STRUCTURE OF FP6

Integrating and strengthening the ERA

Life sciences, genomics and biotechnology for health

Information society technologies

Nanotechnologies and nanosciences, knowledge-based

multifunctional materials and new production processes and devices

Aeronautics and space

Food quality and safety

Sustainable development, global change and ecosystems

Citizens and governance in a knowledge-based society

Structuring the ERA

Research and innovation

Human resources and mobility

Research infrastructures

Science and society

TABLE 1.2

STRUCTURE OF FP7

COOPERATION

Health

Food, Agriculture and Fisheries,

and Biotechnology

Information and Communication

Technologies

Nanosciences, Nanotechnologies,

Materials and new Production

Technologies

Energy

Environment

(including Climate Change)

Transport

(including Aeronautics)

Socio-economic Sciences and

Humanities

Space

Security

IDEAS

European Research

Council

PEOPLE

Marie-Curie Actions

CAPACITIES

Research Infrastructures

Research for the benefit

of SMEs

Regions of Knowledge

Research Potential

Science in Society

Support for the coherent

development of research

policies

International

Cooperation

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

1.2.

Horizon 2020 – EU’s Eighth Framework Programme

With Horizon 2020 the EU’s research and innovation programme has been substan-

tially changed. Compared to FP6 and FP7, more emphasis is placed on innovation

and close-to-market solutions. There is a political wish to focus on job creation in a

time of financial crisis. Participants have to demonstrate to a much larger extent in

their applications that their projects will have an impact on jobs and growth.

Horizon 2020 focuses on three main pillars: Excellent Science, Industrial Leader-

ship and Societal Challenges, with the last pillar covering seven thematic areas.

The overall structure can be seen in table 1.3.

TABLE 1.3

STRUCTURE OF HORIZON 2020

Excellent Science

European Research Council

Future and Emerging Tech-

nologies

Marie Skłodowska-

Curie-Actions

Research Infrastructures

Industrial Leadership

Leadership in Enabling &

Industrial Technologies

- Information and communica-

tion technologies

- Nanotechnologies

- Advanced materials

- Biotechnology

- Advanced manufacturing

and processing

- Space

- Access to Risk Finance

- Innovation in SMEs

Societal Challenges

Health, demographic change

and wellbeing

Food security, sustainable agriculture,

marine and maritime and inland water

research and bioeconomy

Secure, clean and efficient energy

Smart, green and integrated transport

Climate action, environment, resource

efficiency and raw materials

Europe in a changing world-

inclusive, innovative and reflective

societies

Secure societies – Protecting freedom

and security of Europe and its citizens

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

2. Overall Danish partici-

pation in FP6 and FP7

This chapter presents a detailed overview of the Danish participation in FP6 and

FP7. The purpose of this chapter is to provide a detailed view of the Danish partici-

pation in FP6 and FP7 in terms of participants, EU contribution, development over

time, and collaborative links with other countries, in order to provide an insight into

the Danish participation across the two framework programmes and put it into per-

spective in relation to the current framework programme, Horizon 2020.

Moreover, the analysis looks at different types of participants and geographic

spread in FP6 and FP7), as well as the development of the Danish participation

throughout the two framework programmes. The analysis also takes a closer look at

Danish participation in two specific programmes of FP7, namely the European Re-

search Council (ERC) and Marie Curie Actions, a mobility programme.

Furthermore, the collaborative links between Danish participants and participants

from other countries in FP6 and FP7 are presented. Finally, the analysis includes a

comparison of the participation of Denmark and other countries in the two frame-

work programmes.

2.1.

Main findings

The Danish share of total EU contribution from the EU framework programmes

has been stable at 2.37 per cent from FP6 and 2.36 per cent from FP7. However,

in absolute terms, there was an increase in EU contribution to Denmark of almost

168 per cent from EUR 396.1 million in FP6 to EUR 1,060.6 million in FP7. Danish

institutions participated 1,646 times in 1,125 FP6 projects and 2,754 times in 2,011

projects under FP7.

The three most successful Danish universities (University of Copenhagen, Aarhus

University and Technical University of Denmark) alone account for a large part of

the total EU contribution to Denmark: almost one third of total EU contribution

from FP6 and half of total EU contribution to Denmark from FP7.

The participation of private companies rose from FP6 to FP7. The Danish private

companies’ share of the total number of Danish participants increased (27 per cent

in FP6 and 29 per cent in FP7), but their share of EU contribution is slightly less (21

per cent in FP6 and 24 per cent in FP7) meaning that their average EU funding is

slightly less than, for example, for the universities.

439 successful applicants from private companies obtained EUR 81.3 million

from FP6, one fifth of the total EU contribution to Denmark, while 801 successful

applicants received EUR 255.3 million from FP7, equal to one quarter of the Danish

total from FP7.

Participants from institutions based in the Capital Region received almost two-

thirds of total EU contribution to Denmark from both FP6 and FP7. The Central

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

and North Denmark Regions however increased their share of EU contribution to

Denmark in FP7.

FP7 introduced the European Research Council (ERC), which supports top-level

investigator-driven frontier research across all fields. During FP7, Denmark ob-

tained 83 ERC grants. Most grants were obtained by University of Copenhagen (33

ERC grants), Aarhus University (25) and Technical University of Denmark (11).

Danish institutions participated in 384 Marie Curie Actions (PEOPLE), involving

433 Danish participants in total. This makes the PEOPLE programme the largest

single programme in terms of number of participants from Denmark in FP7.

The countries with which Denmark collaborates the most in FP6 and FP7 projects

are Germany, the United Kingdom and France. Danish institutions and companies

also collaborate extensively with participants from the Nordic countries in both

framework programmes. There are relatively fewer projects in FP7 than in FP6 with

participants from both Denmark and one of the countries that acceded to the EU as

part of the 2004 and 2007 enlargements.

2.2.

Overview of Danish participation in FP6 and FP7

The EU framework programmes for research and innovation are based on open calls

for proposals. This subanalysis examines the Danish participation in FP6 and FP7,

and partly Horizon 2020, which is the result of these calls for proposals. The term

”EU contribution” refers to the funding from the framework programmes awarded

to research and development activities.

The Danish share of total EU contribution from FP6 and FP7 is almost the same.

However, there are big differences in the size of the budgets of the two framework

programmes and, as a result, the Danish contribution from FP7 in absolute terms

is much larger than for FP6. The EU contribution from the framework programmes

rose by around 169 per cent from FP6 to FP7. As shown in table 2.1, the total EU

contribution to Denmark from FP6 was EUR 396.1 million, equal to 2.37 per cent of

the total EU contribution from the programme, while in FP7 Denmark took home

EUR 1,060.6 million, equal to 2.36 per cent of the total EU contribution distributed

from that programme. This corresponds to a 168 per cent increase of EU contribu-

tion to Denmark in absolute terms.

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

TABLE 2.1

EU CONTRIBUTION TO DENMARK FROM FP6, FP7 AND HORIZON 2020

FP6

Total number of participations

Danish participations

Total number of projects

Projects with Danish participation

Total EU contribution (EUR m)

EU contribution to Denmark

(EUR m)

Average yearly EU contribution

to Denmark (EUR m)

Share of EU contribution

to Denmark (per cent)

74,583

1,646

10,107

1,125

16,697

396.1

2.37 %

FP7

133,615

2,754

25,238

2,011

44,917

1,060.6

151.5

2.36 %

Horizon 2020

(as of March 2015)

17,118

376

3765

286

6,621

154,4

154.4

2.30 %

One year into Horizon 2020, the Danish share of total EU contribution is EUR 152.4

million, equalling 2.30 per cent as of March 2015.

Tables 2.2 and 2.3 show the Danish participation in FP6 and FP7 per thematic

area, while tables 8.1 and 8.2 in Annex 1 present a detailed overview of the Danish

participation. The Danish share of total EU contribution is, in relative terms, high-

est in the area of food quality and safety under FP6. Under FP7, the largest share

of EU contribution from a specific thematic area is within energy research, with a

Danish share of 5.42 per cent of total funding received by 164 participants in 92 pro-

jects. In terms of total EU contribution, health research in FP7 is where Denmark

reached the largest amount of funding: almost EUR 137 million. Food research is

the thematic area of FP7 from which Denmark has its second largest share of total

EU contribution (4.56 per cent).

The European Research Council (ERC) was established with FP7 and funds ex-

cellent investigator-driven frontier research across all fields. Funding from ERC, at

EUR 146.3 million, accounts for almost 14 per cent of total EU contribution to Den-

mark from FP7.

Furthermore, funding supporting the mobility of researchers (the so-called Marie

Curie actions) rose considerably from FP6 to FP7. Danish institutions and private

enterprises took home EUR 40.3 million from the FP6 Human Resources and Mo-

bility programme, equal to around 10 per cent of total EU contribution to Denmark

from FP6, whereas Denmark obtained EUR 152.2 million in funding from the Marie

Curie Actions (PEOPLE) programme, corresponding to 14.4 per cent of total EU

contribution to Denmark from FP7.

Sources: The European Commission’s Common Research Data (eCORDA) warehouse. For

FP6: eCORDA Contracts database. Publication date: 6 June 2008. For FP7: eCORDA FP7 grant

agreements and participants’ database. Extraction date: 15 October 2014. For Horizon 2020:

eCORDA Horizon 2020 consolidated proposals and applicants database. Publication date: 4

March 2015.

Includes roughly the results of one call year per programme under Horizon 2020.

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

TABLE 2.2

THE PARTICIPATION OF DENMARK IN FP6 (2002-2006)

Specific

Programme

Priority Area

All Countries

EC financial

contribution

(EUR m)

Life sciences, genomics and

biotechnology for health

Information society tech-

nologies

Nanotechnologies and

nanosciences, knowl-

edge-based multifunctional

materials and new produc-

tion processes and devices

Aeronautics and space

Food quality and safety

Sustainable development,

global change and ecosys-

tems

Citizens and governance in a

knowledge-based society

Policy support and anticipat-

ing scientific and technolog-

ical needs

Horizontal research activities

involving SMEs

Specific measures in support

of international cooperation

Support for the coherent

development of research &

innovation policies

Support for the coordination

of activities

Integrating and strenghten-

ing the ERA total

Research and innovation

STRUCTURING

THE ERA

EURATOM

Total

Human resources and mo-

bility

Research infrastructures

Science and society

Structuring the ERA total

Euratom

2,339.60

3,799.50

Projects

with DK

participation

150

134

Denmark

EC financial

contribution

(EUR m)

80.3

48.6

DK Partners

203

199

1,539.00

1,068.60

751.6

107

138

25.7

4.4

52.9

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

INTEGRATING AND STRENGTHENING THE ERA

2,306.50

244.2

177

317

83.7

4.9

601.7

485.2

351.6

115

157

123

20.2

10.9

5.3

13.8

288

13,789.40

225.4

1,693.20

725.2

77.8

2,721.60

185.7

16,696.60

900

158

219

1,125

1,380

172

257

1,646

0.1

342

5.3

40.3

4.9

2.5

1.1

396.1

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

TABLE 2.3

THE PARTICIPATION OF DENMARK IN FP7 (2007-2013)

Priority Area

All Countries

EU Contri-

bution

(EUR m)

Health

Food, Agriculture and Fisher-

ies, and Biotechnology

Information and Communica-

tion Technologies

Nanosciences, Nanotechnol-

ogies, Materials and new Pro-

duction Technologies – NMP

Energy

Environment

(including Climate Change)

Transport

(including Aeronautics)

Socio-economic sciences and

Humanities

Space

Security

General Activities

Joint Technology Initiatives (JTI)

COOPERATION total

European Research Council

IDEAS total

Marie Curie Actions

PEOPLE total

Research Infrastructures

Research for the benefit of

SMEs

Regions of Knowledge

Research Potential

Science in Society

Support for the coherent de-

velopment of research policies

International Cooperation

CAPACITIES total

Fusion Energy

Nuclear Fission and Radiation

Protection

EURATOM total

EURATOM

Total

CAPACITIES

IDEAS PEOPLE

COOPERATION

4,791.70

1,850.70

7,877.00

Projects

with DK

participation

202

176

218

Denmark

EU Contri-

bution to DK

(EUR m)

136.6

84.4

105.7

DK Partners

265

285

297

3,238.60

1,707.40

1,719.30

2,284.20

579.6

713.3

1,295.50

312.7

1,966.40

28,336.30

7,673.50

4,777.40

1,528.40

1,249.10

126.7

377.7

288.4

28.3

173.4

3,772.00

5.2

352.8

358.1

44,917.20

152

130

1,256

384

130

272

2,011

223

164

175

157

1,819

433

217

392

2,754

81.6

92.5

50.8

26.7

15.4

12.5

14.3

1.1

51.1

672.7

146.3

152.2

34.5

37.8

3.2

12.1

0.2

0.7

88.4

0.1

0.9

1,060.60

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

2.3.

Types of participating organisations

Participants in FP6 and FP7 are divided into a number of organisation types: the

Higher Education Sector (HES), which includes all Danish universities and Univer-

sity Colleges; Research Organisations (REC), which includes the Danish research

and technology organisations (GTS institutes, RTO), and Private for profit Com-

panies (PRC), which includes both large companies and small and medium-sized

enterprises (SMEs). Public institutions (PUB) include ministries, regions and mu-

nicipalities, as well as university hospitals. Other (OTH) includes participants which

could not be ascribed to one of the above-mentioned categories.

In 2007, many governmental research institutions

were merged with the univer-

sities as a result of the University Reform in 2007, and from then on they appeared

in the statistics under the Higher Education Sector instead of Research and Tech-

nology Organisations. Therefore, participation by organisation type is not entirely

comparable from FP6 to FP7, which is why we also take a closer look at the partici-

pation of both universities and GTS institutes.

As shown in figures 2.1-2.4, most of the Danish participation is composed of or-

ganisations from the Higher Education Sector (HES). It is interesting to note that

Danish HES participation rose from 41 per cent in FP6 to 49 per cent in FP7, while

their share of EU contribution to Denmark rose equally from 50 per cent to 57 per

cent. The participation of the Danish private companies rose slightly from 27 per

cent in FP6 to 29 per cent in FP7, while their share of EU contribution is relatively

lower, but rose from 21 per cent in FP6 to 24 per cent in FP7. In other words, private

companies typically receive less funding on average than participants from universi-

ties. This can partly be ascribed to the fact that fewer private companies coordinate

FP6 and FP7 projects than universities. The coordinator would often receive the

largest share of funding among the participants in an FP6 or FP7 project.

Figures 2.5 and 2.6 show the Danish participation in Horizon 2020 by participant

type. It should be noted that the HES category is relatively large and the PRC cate-

gory relatively small compared to FP7, both in terms of number of participants and

EU contribution. Under FP7, universities and other participants from the HES cat-

egory were involved in FP7 more than 1,300 times, while private companies partic-

ipated around 800 times. Under Horizon 2020 (March 2015), 206 participants are

from HES and 89 from private companies, out of a total of 376 Danish participants.

In sum, the share of EU contribution to participants from the public sector, and es-

pecially the universities, has risen from FP6 to Horizon 2020 (as of March 2015).

Figures 2.1-2.6 show the Danish participation in FP6, FP7 and Horizon 2020 by

participant type, calculated on the number of participations and on the basis of EU

contribution awarded

Sektorforskningsinstitutioner

FP6 participant data is divided into 14 participant types. For the purpose of this section, we

have aligned the FP6 categories of participants to the same 5 categories used in FP7, in order to

make the FP6 categories of participants comparable to those of FP7.

FP6 data: A large number of participants under the participant type “OTH” (Other) are in

reality SMEs: 87 participants out of a total of 310 participants are from industry. 56 of these

partners are SMEs. As a result, there are participants from industry under both of the categories

“IND” (Industry) and “OTH” (Other). The organisation type assigned to the individual partici-

pants has not been altered for the purpose of this report.

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

FIGURE 2.1

FP6: PARTICIPANTS BY

ORGANISATION TYPE

19%

11%

PUB

HES

27%

41%

PRC

REC

OTH

FIGURE 2.2

FP6: EU CONTRIBUTION BY

ORGANISATION TYPE

20%

PUB

HES

21%

50%

PRC

REC

OTH

FIGURE 2.3

FP7: PARTICIPANTS BY

ORGANISATION TYPE

11%

PUB

HES

29%

49%

PRC

REC

OTH

FIGURE 2.4

FP7: EU CONTRIBUTION BY

ORGANISATION TYPE

24%

PUB

HES

57%

PRC

REC

OTH

FIGURE 2.5

H2020 (MARCH 2015): PARTICIPANTS BY

ORGANISATION TYPE

23%

FIGURE 2.6

H2020 (MARCH 2015): EU CONTRIBUTION

BY ORGANISATION TYPE

18%

61%

15%

PUB

HES

PRC

REC

OTH

11%

PUB

HES

55%

PRC

REC

OTH

Participant types:

PUB = Public body (excluding research and education), HES = Higher or secondary education, PRC

= Private for profit companies, REC = Research organisations and OTH = Other.

2.3.1. Danish universities

As can be seen in tables 2.4 and 2.5, the Danish universities obtained a total of EUR

164.4 million in FP6, while they received EUR 603.4 million in FP7. Thus, the uni-

versities have received about 3.7 times more EU funding in FP7 compared to FP6.

As can be seen in figures 2.1 and 2.3, the universities’ relative share of the Danish

participation has increased from around 41 per cent in FP6 to 49 per cent in FP7.

The universities’ share of participation in FP7 is approximately one and a half times

larger than the overall Danish share of participation in FP6. However, as mentioned

in section 2.2., this can partly be ascribed to the merger of governmental research

institutions with universities in 2007.

The number of coordinators from universities is much higher in FP7 than in FP6,

rising from 93 in FP6 to 389 in FP7 (tables 2.4 and 2.5). This is mainly due to the

establishment of the European Research Council (ERC) under the so-called IDEAS

programme, and the increased number of Danish coordinators of Marie Curie Ac-

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

tions under the PEOPLE programme. As individual researchers are the main appli-

cants for the projects under these programmes, they are counted as coordinators.

This applies to 78 ERC projects and 215 Marie Curie Actions with Danish participa-

tion. However, even when removing these two specific programmes, there still is a

considerable increase in the number of coordinators from FP6 to FP7.

Most significantly, University of Copenhagen (KU) has 5.8 times as many coordi-

nators in FP7 as in FP6. This corresponds to almost half of all the projects the uni-

versity participates in. Aarhus University (AU) has 5.3 times as many coordinators

in FP7 compared to FP6. The remaining Danish universities have also doubled or

more than doubled their number of coordinators from FP6 to FP7.

The Technical University of Denmark (DTU) participated most frequently in

projects with Danish participation both in FP6 and FP7. In FP6, DTU accounted for

the largest share of participation, but in FP7 it was University of Copenhagen that

had the largest share of EU contribution. The IT University experienced the largest

increase in participation among all universities from FP6 to FP7. The university’s

starting level of EUR 0.3 million is however quite low. All universities except one

have increased their participation and contribution of European funds from FP6 to

FP7. Roskilde University is the only Danish university which has not seen a signifi-

cant increase in either participation or funding.

The participation of Danish universities in Horizon 2020 is shown in table 2.6.

It may be noted that University of Copenhagen has been very successful at the be-

ginning of the new framework programme and accounts for more than half of total

EU contribution to Danish universities. Moreover, the share of EU contribution of

University of Copenhagen is more than that of Aarhus University and Technical

University of Denmark combined. The participation of Danish universities is most

prominent under the Excellent Science pillar of Horizon 2020, which now covers

both the European Research Council and Marie Skłodowska-Curie actions, where

the universities’ share of total EU contribution is more than 90 per cent of total EU

contribution to Denmark. University of Copenhagen is home to more than 50 per

cent of the total Danish share of the Excellent Science pillar, while the Technical

University of Denmark is the university that receives the largest share of total EU

contribution to Denmark under the Societal Challenges pillar, at around 14 per cent.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

TABLE 2.4

THE DANISH UNIVERSITIES IN FP6

University

Copenhagen Business School

Technical University of Denmark

IT University of Copenhagen

University of Copenhagen

Roskilde University

University of Southern Denmark

Aalborg University

Aarhus University

Total

Participations

192

145

591

EU contribution

Coordinators

(EUR)

3,359,259

52,457,819

310,277

41,227,184

2,922,439

16,662,517

18,685,049

28,791,479

164,416,021

Share of total

EU cont. to DK

universities

2.04 %

31.91 %

0.19 %

25.07 %

1.78 %

10.13 %

11.36 %

17.51 %

100 %

TABLE 2.5

THE DANISH UNIVERSITIES IN FP7

University

Copenhagen Business School

Technical University of

Denmark

IT University of Copenhagen

University of Copenhagen

Roskilde University

University of Southern

Denmark

Aalborg University

Aarhus University

Total

Participations

409

397

136

269

1,348

EU contribution

Coordinators

(EUR)

186

389

11,276,858

186,622,062

4,493,705

191,354,641

3,520,468

31,404,808

49,081,685

125,689,930

603,444,156

Share of total

EU cont. to DK

universities

1.90 %

30.90 %

0.70 %

31.70 %

0.60 %

5.20 %

8.10 %

20.80 %

100 %

TABLE 2.6

THE DANISH UNIVERSITIES IN HORIZON 2020 (MARCH 2015)

University

Copenhagen Business School

Technical University of Denmark

IT University of Copenhagen

University of Copenhagen

Roskilde University

University of Southern Denmark

Aalborg University

Aarhus University

Total

Participations

204

EU contribution

Coordinators

(EUR)

102

2,667,546

21,123,478

551,834

40,280,049

579,439

3,836,416

6,623,458

16,371,032

92,033,252

Share of total

EU cont. to DK

universities

3.53 %

27.92 %

0.73 %

53.24 %

0.77 %

5.07 %

8.75 %

21.64 %

100 %

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

2.3.2. Danish private companies

The total number of participations of private companies in FP6 was 439. Almost

twice as many private companies participated in FP7, with a total of 801. The total

EU contribution to Danish private companies from FP6 was EUR 81.3 million, while

the EU funding from FP7 to Danish businesses was EUR 255.3 million. In table 2.7,

we have divided the private companies into large enterprises and small and medi-

um-sized enterprises (SMEs)

. For a detailed view of the participation of Danish

private companies in FP6 and FP7, please see Annex 1, tables 8.3 and 8.4.

The overall Danish share of EU contribution for large enterprises has decreased

slightly from FP6 to FP7, going from 7.33 per cent to 6.79 per cent. However, in to-

tal EU contribution the funding has increased from EUR 29 million in FP6 to EUR

72 million in FP7 in the case of large enterprises. The overall share of EU contribu-

tion to Danish SMEs increased by 5 percentage points from 10.84 per cent in FP6 to

15.87 per cent in FP7. The rise is even more prominent when looking at the total EU

contribution to SMEs, evolving from EUR 42.9 million in FP6 to EUR 168.3 million

in FP7.

The number of successful SME applicants almost doubled from FP6 to FP7, while

the large enterprises went from 136 participants in FP6 to 238 participants in FP7.

The number of Danish coordinators also experienced an increase, both for large

enterprises and SMEs, between the two framework programmes. One reason for the

large number of SME coordinators in FP7 can be ascribed to the fact that FP7 in-

cluded a fine-tuned programme particularly targeted at small and medium-sized en-

terprises, namely the Research for the Benefit of SMEs programme. Half of those 33

SMEs that coordinated a project within FP7 were funded under the Research for the

Benefit of SMEs programme (see Annex 1, tables 8.3 and 8.4). The Research for the

Benefit of SMEs programme of FP7 was the successor to the Horizontal research ac-

tivities involving SMEs programme of FP6, which included the project type CRAFT

(Co-operative Research Project) with a number of similarities to the SME projects

under FP7. The Horizontal research activities involving SMEs programme of FP6 is

home to 10 of 25 Danish participations with an SME as the coordinator.

The Danish participation from private companies is strongest within the the-

matic areas of energy and nanotechnologies, both in FP6 and FP7. The Danish

industry share of the FP6 programme Nanotechnologies and Nanosciences, Knowl-

edge-Based Multifunctional Materials and New Production Processes and Devices

totals almost 36 per cent of EU contribution to Denmark of that particular pro-

gramme (cf. tables 8.3 and 8.4 in Annex 1).

The eCORDA FP6 and FP7 data do not indicate whether or not the participant is an SME. For

the purpose of section 2.4 (The participation of Danish private companies in FP6 and FP7) we

have manually checked all partners under the participant types of FP6 as well as the “PRC” cat-

egory (Private companies) of FP7 with the Central Business Register, CVR, website (www.cvr.

dk) (data checked in January-February 2015). After cleaning the FP6 data, the total number of

private companies is 439 with a total EU contribution of EUR 81.3 million. We were unable to

characterise 46 of these private companies as either SMEs or large enterprises. In the FP7 data-

set the total of private companies is 801 with a total EU contribution of EUR 255.3 million. We

were unable to characterise 47 of these private companies as either SMEs or large enterprises.

Therefore, these 93 private companies are not included in table 2.7.

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

TABLE 2.7

PRIVATE COMPANIES IN FP6 AND FP7

FP6

Large

enterprises

Participants

136

Coordinators

EU contribution

(EUR)

29,047,725

EU contribution

(EUR)

42,947,390

Share of EU contribu-

tion to DK of FP6

7.33 %

Share of EU contribu-

tion to DK of FP6

10.84 %

SMEs

Participants

257

Coordinators

FP7

Large

enterprises

Participants

238

Coordinators

EU contribution

(EUR)

71,994,336

EU contribution

(EUR)

168,287,885

Share of EU contribu-

tion to DK of FP6

6.79 %

Share of EU contribu-

tion to DK of FP6

15.87 %

SMEs

Participants

516

Coordinators

2.3.3. Danish research and technology organisations (RTOs)

The participation of Danish RTOs also increased significantly from FP6 to FP7. The

total EU contribution from FP7 is almost seven times higher for the RTOs compared

to FP6, while the number of successful applicants in the same category is 3.5 times

higher from FP6 to FP7.

Most markedly, as table 2.8 shows, Danish Technological Institute went from

having 11 projects and an overall participation of EUR 1.7 million in FP6 to 59 pro-

jects in FP7 and an EU funding amounting to EUR 27.8 million. Further, Danish

Technological Institute is the project coordinator of 13 out of the 17 projects coor-

dinated by Danish RTOs in FP7. The Technological Institute’s share of the overall

EU contribution to GTS institutes in FP7 is a little more than half of the total. The

EU contribution to Danish Technological Institute, Alexandra Institute and DHI

together constitutes more than 80 per cent of the total EU contribution to Danish

RTOs.

It is noticeable that Alexandra Institute went from 1 project in FP6 to 13 projects

in FP7, including one project as coordinator. DHI doubled their number of partici-

pations, while their share of EU contribution tripled from FP6 to FP7. Conversely,

FORCE Technology participated in 9 FP6 projects and was thereby the Danish RTO

with third most participations, while in FP7 FORCE Technology only participated

three times, making it the RTO with the least number of participations in FP7. Agro-

Tech is the only Danish RTO that neither participated in FP6 nor in FP7. The share

of RTOs of total EU contribution to Denmark was 1.6 per cent from FP6 and 4 per

cent from FP7.

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

TABLE 2.8

THE PARTICIPATION OF DANISH RTOs IN FP6 AND FP7

FP6

Research and Technology

Organisation

Alexandra Institute

Bioneer

DBI – Danish Institute of Fire and

Security Technology

DFM – Danish Institute of

Fundamental Metrology

DELTA – Danish Electronics, Light

& Acoustics

DHI – Water and Environment

FORCE Technology

DTI – Danish Technological Insti-

tute

Total

EU contribution

Coordinators

(EUR)

105,587

276,318

77,587

2,812,906

1,345,283

1,737,422

6,355,102

Share of total

EU cont. to DK

RTOs

1.7 %

4.3 %

1.2 %

44.3 %

21.2 %

27.3 %

100 %

Participations

FP7

Research and Technology

Organisation

Alexandra Institute

Bioneer

DBI – Danish Institute of Fire and

Security Technology

DFM – Danish Institute of

Fundamental Metrology

DELTA – Danish Electronics, Light

& Acoustics

DHI – Water and Environment

FORCE Technology

DTI – Danish Technological Insti-

tute

Total

EU contribution

Coordinators

(EUR)

5,089,602

2,476,022

1,727,200

1,165,349

1,736,546

8,221,854

952,887

21,797,989

43,167,450

Share of total

EU cont. to DK

RTOs

11.8 %

5.7 %

4.0 %

2.7 %

4.0 %

19.0 %

2.2 %

50.5 %

100 %

Participations

122

2.4.

Danish participation in FP6 and FP7 by region

Table 2.9 shows the participation of Denmark in FP6 and FP7 by region. Unsurpris-

ingly, the Capital Region of Denmark, which is home to four of the eight Danish uni-

versities and many research-intensive private companies, is the region receiving the

largest EU contribution from the framework programmes. It can be noticed that in

the Central Denmark Region three times as many partners have taken the respon-

10 This includes all participants from the Danish regions, based on the Nomenclature of Units for

Territorial Statistics (NUTS) classification. Thus, the regions mean not only the administrative

bodies participating (such as the Zealand Region), but all participants from the specific region.

Information on data: Not all participants in the FP6 and FP7 datasets have been assigned a

NUTS code. Therefore, we have manually assigned a NUTS code to those participants with

missing NUTS information.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

sibility of coordinating projects in FP7 compared to FP6. However, it is worth not-

ing that in FP7, 74 of the coordinators from the Central Denmark Region are from

Aarhus University, and that 62 of these projects are single-applicant grants (ERC

grants and Marie Curie Action projects). Both the Central Denmark Region and the

North Denmark Region increased their relative share of EU contribution among the

regions of Denmark. On the other hand, the share of EU contribution to the Zealand

Region dropped from around 4 per cent in FP6 to only 1.5 per cent of the total Dan-

ish EU contribution in FP7.

In FP7, university participation constitutes around half of the total number of

participations in the Capital Region of Denmark (48 per cent) and the Central Den-

mark Region (55 per cent), compared to 34 per cent and 41 per cent in FP6, while

it is more than half in the North Denmark Region (60 per cent), compared to 54

per cent in FP6, and less than half in the Region of Southern Denmark (38 per cent

versus 41 per cent in FP6). The Zealand Region stands out as the region with least

university participation: Roskilde University constitutes one fourth (25 per cent) of

the total number of participations of Zealand in FP7 (20 per cent in FP6).

TABLE 2.9

THE PARTICIPATION OF DENMARK IN FP6 AND FP7 BY REGION

FP6

Region

Capital Region of Denmark

Central Region Denmark

North Denmark Region

Region Zealand

Region of Southern Denmark

Greenland

Total

Participations

1,061

238

112

149

1,646

Coordinators

140

210

EU contribution

(EUR)

264,333,375

58,185,492

25,563,903

16,335,163

31,621,800

86,300

396,126,034

Share of total

EU cont. to DK

66.7 %

14.7 %

6.5 %

4.1 %

8.0 %

0.0 %

100 %

FP7

Region

Capital Region of Denmark

Central Region Denmark

North Denmark Region

Region Zealand

Region of Southern Denmark

Greenland

Total

Participations

1,764

485

226

215

2,754

Coordinators

354

503

EU contribution

(EUR)

692,622,678

197,710,088

76,108,804

15,690,901

78,276,273

188,250

1,060,596,995

Share of total

EU cont. to DK

65.3 %

18.6 %

7.2 %

1.5 %

7.4 %

0.0 %

100 %

2.5.

The development of Danish participation in FP6, FP7 and

Horizon 2020

Tables 2.10, 2.11 and 2.12 show the Danish versus total EU contribution for all coun-

tries over the years in FP6 (2002-2006), FP7 (2007-2013) and in Horizon 2020

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

(until March 2015). As can be seen, the Danish EU contribution from FP6 and FP7

fluctuates over the years.

It can be noted that most of the funds are distributed in the middle of the pro-

gramme periods. This is due to the fact that only a few calls for proposals have

deadlines in the beginning or the end of the programme period. It can be noted that

the immediate Danish EU contribution from FP7 after the first year was relatively

low, and increased along the programme period, ending with a share of the total

EU contribution of 2.36 per cent. As mentioned earlier, the Danish share of total

EU contribution was almost the same in both framework programmes, while the

actual amount of EU contribution from FP7, given the size and duration of the pro-

gramme, was far more than the double. The first Horizon 2020 proposals data were

made available in November 2014 and contained only a small number of calls, while

the update in March 2015 contains on average one concluded evaluation round per

thematic area.

TABLE 2.10

THE DEVELOPMENT OF DENMARK’S PARTICIPATION IN FP6

Year

Participations

EU contribution to

Denmark (EUR)

Total EU

contribution (EUR)

DK share of total

contribution

Unspecified

6,014,418.40

145,283,923

4.14 %

2003

168

44,426,878.10

1,794,984,070

2.48 %

2004

425

91,352,663.60

4,391,441,661

2.08 %

2005

435

101,875,959.20

4,450,152,468

2.29 %

2006

418

104,060,839.40

4,880,101,220

2.13 %

2007

150

48,395,275.00

1,034,643,172

4.68 %

Total

1646

396,126,033.70

16,696,606,514

2.37 %

TABLE 2.11

THE DEVELOPMENT OF DENMARK’S PARTICIPATION IN FP7

Year

Participa-

tions

EU contri-

bution to

Denmark

(EUR)

Total EU

Contribu-

tion (EUR)

DK share of

total

EU contribu-

tion

2007

2008

341

2009

392

2010

411

2011

461

2012

485

2013

486

2014

106

Total

2754

27,817,678

104,155,432

137,513,735

143,114,090

162,178,313

206,963,605

220,055,013

58,799,129

1,060,596,995

1,748,654,830 5,062,843,149 5,389,520,539 6,207,495,142 7,181,377,801 7,873,387,844 8,943,319,350 2.510.586.803 44,917,185,458

1.59 %

2.06 %

2.55 %

2.31 %

2.26 %

2.63 %

2.46 %

2.34 %

2.36 %

11 Year = date of grant signature

12 Year = date of grant signature

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

TABLE 2.12

THE DEVELOPMENT OF DENMARK’S PARTICIPATION IN HORIZON 2020

Year

Participations

EU contribution to Denmark (EUR m)

Total EU contribution (EUR m)

DK share of total EU contribution

2014 (November)

118

48.6

2,229

2.18 %

2015 (March)

376

152.4

6,621

2.30 %

2.6.

Danish participation in ERC excellence projects (FP7)

The European Research Council (ERC) was introduced along with FP7 in 2007. The

ERC supports investigator-driven frontier research across all fields, on the basis of

scientific excellence. ERC grants are among the most prestigious in FP7 and now in

Horizon 2020.

The three main grants are the ERC Starting Grant (up to EUR 1.5 million per

project, for researchers with 2-7 years of experience past PhD), ERC Consolidator

Grant (up to EUR 2 million per project, for researchers with 7-12 years past PhD)

and the ERC Advanced Grant (up to EUR 2.5 million, for experienced research-

ers with a significant track record within the last 10 years). The ERC Consolidator

Grant scheme was introduced in 2013. In 2012 and 2013, the ERC Synergy Grant

supported groups of principal investigators with a maximum EU contribution of up

to EUR 15 million. Proof of Concept was introduced in 2011 and is a grant of up to

EUR 150,000, which is open to researchers who have already been awarded one of

the other ERC grants.

The most successful host institutions in attracting ERC grants are University of

Copenhagen and Aarhus University. Until 2011 both universities had obtained the

same number of grants. However, in the last years of FP7, the applications of Uni-

versity of Copenhagen were very successful and finally obtained a total of 33 ERC

grants. Technical University of Denmark has achieved 11 ERC grants in FP7 and is

thereby third among the Danish institutions. All Danish universities have obtained

at least one ERC grant, except Roskilde University. Furthermore, researchers at a

number of other research institutions, namely Danish Cancer Society, Statens Se-

rum Institut (SSI) and Geological Survey of Denmark and Greenland (GEUS), have

received ERC grants.

13 Year (month) = eCORDA release. The release year is not necessarily the same as the year of

grant signature.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

TABLE 2.13

ERC GRANTEES TO DENMARK (FP7)

Institution

University of

Copenhagen

Aarhus University

Technical University of

Denmark

University of Southern

Denmark

Copenhagen Business

School

Danish Cancer Society

IT University of

Copenhagen

Capital Region of

Denmark

SSI (Statens Serum In-

stitut)

Aalborg University

Geological Survey

of Denmark and

Greenland (GEUS)

Danish Meteorological

Institute

Total

Starting

Grant

Consolidator

Grant

Advanced

Grant

Synergy

Grant

Proof of

Concept

Total

33 (34*)

(1*)

83 (85*)

*University of Copenhagen and Danish Meteorological Institute participate as partners in the very large Synergy

Grant project ICE2ICE. The total number of coordinators with a Danish host institution is 83.

**The number of ERC grantees is connected to the host institution at the time of main list (acceptance of funding

to the proposal). The number of ERC grantees that potentially have transferred to a different institution (in Den-

mark or abroad) is therefore not reflected in the above figures.

2.7.

Danish participation in Marie Curie mobility projects (FP7)

This section focuses on the FP7 mobility programme, the Marie Curie Actions. The

Marie Curie Actions are the successor to the FP5 Marie Curie Fellowships and FP6

Human Resources and Mobility programme. Marie Curie Actions seek to make

Europe more attractive for researchers and to establish a “brain circulation” within

the EU Member States and Associated Countries. It means that, first and foremost

researchers must change country. Beside transnational mobility, the Marie Curie

Actions also aim to foster inter-sectoral mobility between academic and private sec-

tors. The Marie Curie Actions follow a bottom-up approach, i.e. research fields are

chosen freely by applicants. All domains of research are eligible.

In table 2.14, the most successful Danish institutions in host-driven actions under

the Marie Curie programme have been listed

. Not surprisingly, the three largest

Danish universities (Technical University of Denmark, University of Copenhagen

and Aarhus University) are involved in most Marie Curie Actions. Most participa-

14 The Marie Curie programme can be divided into individual-driven actions and host-driven

actions. For the purpose of this analysis, we focus on the host-driven actions. The host-driven

actions are IAPP: Industry-Academia Partnerships & Pathways; ITN: Initial Training Networks;

COFUND: Cofunding of national pro-grammes, and IRSES: International Research Staff Ex-

change Scheme.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

tions are within the Initial Training Networks, which support collaboration between

academic and non-academic institutions in different countries. The total number of

Danish institutions that have participated (once or several times) in a host-driven

Marie Curie Action under FP7 is 65. Among these were 45 private companies.

TABLE 2.14

TOP 10: DANISH INSTITUTIONS WITH MOST PARTICIPATIONS IN HOST-DRIVEN MARIE

CURIE ACTIONS (COFUND, IAPP, IRSES, ITN)

Institution

Technical University of Denmark

University of Copenhagen

Aarhus University

University of Southern Denmark

Aalborg University

Carlsberg A/S

Qiagen Aarhus A/S

Novozymes A/S

Copenhagen Business School

Rambøll Danmark A/S

COFUND

IAPP

IRSES

ITN

Total

2.8.

Denmark compared to other countries

While this analysis mainly focuses on Denmark, it is interesting to look at Danish

participation from a comparative perspective. The participation of Denmark has

been high, but relatively stable from FP6 to FP7 in relative terms. However, this has

not been the case for other countries. Tables 2.15 and 2.16 show the participation of

Denmark and other Nordic countries as well as a selection of other countries, meas-

ured by number of participations and coordinators, EU contribution and share of

total EU contribution.

All Scandinavian countries and Finland experienced a slight drop in share of EU

contribution from FP6 to FP7. This is particularly true for Sweden and Finland,

where the share of EU contribution dropped from FP6 to FP7. However, other coun-

tries experienced an increase in the share of EU contribution. This is most signifi-

cant for the Netherlands, where the share rose from 6.63 per cent in FP6 to 7.41 per

cent in FP7, and Switzerland, where the share of EU contribution rose by more than

60 per cent from FP6 to FP7. If we look at the EU contribution per citizen, Denmark

is in the lead among the Nordic countries in both FP6 and FP7. However, Denmark

receives less EU contribution per citizen in FP7 than the Netherlands, and signifi-

cantly less than Switzerland.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

TABLE 2.15

DANISH PARTICIPATION IN FP6 COMPARED TO OTHER COUNTRIES

Partici-

pations

1,646

2,648

1,300

1,440

4,080

2,866

1,995

1,957

74,583

Coordina-

tors

210

330

149

156

677

454

209

285

10,106

EU Contri-

bution

(EUR m)

396

677

284

342

1,108

710

465

426

16,697

Share of EU

Contribution

2.37 %

4.06 %

1.70 %

2.05 %

6.63 %

4.25 %

2.79 %

2.55 %

100 %

EU Con-

tribution

per citizen

(EUR)*

72.7

74.3

60.7

64.9

67.7

67.1

61.9

51.4

FP6

Nordic Countries

Country

Denmark

Sweden

Norway

Finland

Other countries

The

Netherlands

Belgium

Switzerland

Austria

Total for all countries

participating in FP6

TABLE 2.16

DANISH PARTICIPATION IN FP7 COMPARED TO OTHER COUNTRIES

Participa-

tions

2,754

4,506

2,185

2,650

8,151

5,458

4,457

3,516

Coordina-

tors

503

722

350

355

1,634

919

1,036

675

EU Contri-

bution

(EUR m)

1,061

1,709

754

876

3,330

1,815

2,034

1,184

Share of EU

Contribution

2.36 %

3.80 %

1.68 %

1.95 %

7.41 %

4.04 %

4.53 %

2.64 %

EU Con-

tribution

per citizen

(EUR)**

188.8

177.1

147.6

160.7

197.9

162.0

249.9

139.2

FP7

Nordic Countries

Country

Denmark

Sweden

Norway

Finland

Other countries

The

Netherlands

Belgium

Switzerland

Austria

Total for all

countries

participating in FP7

133,615

25,237

44,917

100 %

2.9.

Denmark’s international collaborators

The most favoured collaborators of Danish institutions and companies have not

changed significantly in relative terms from FP6 to FP7. Germany is the most fre-

quent partner for Danish participants, with the United Kingdom and France as

numbers two and three in both FP6 and FP7. The overall number of Danish project

collaborators has, along with the number of total participations, increased from FP6

to FP7. The tables primarily show Danish international collaborators from Europe,

but it is worth noticing that Denmark collaborates more with the United States in

15 *Eurostat: Population on 1 January 2007: http://ec.europa.eu/eurostat/tgm/table.do?tab=tab-

le&init=1&language=en&pcode=tps00001&plugin=1”

16 **Eurostat: Population on 1 January 2014: http://ec.europa.eu/eurostat/tgm/table.do?tab=ta-

ble&init=1&language=en&pcode=tps00001&plugin=1

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

FP7 than in FP6, moving from number 33 to 24 on the list of countries that Danish

partners collaborate most frequently with.

The other Nordic countries, namely Sweden, Norway and Finland, seem to retain

a strong collaborative position with Danish institutions throughout FP6 and FP7.

The collaborations with Spain (FP6: 6th, FP7: 4th), Austria (FP6: 14th, FP7:

10th), Portugal (FP6: 17th, FP7: 15th) and Ireland (FP6: 18th, FP7: 16th) increased

from FP6 to FP7.

Interestingly, Danish participants’ collaboration with EU-10 countries (countries

that acceded to the Union as a result of the EU enlargements in 2004 and 2007) de-

creased in relative terms from FP6 to FP7, with Romania as the only country mov-

ing up the ranks in FP7.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

FIGURE 2.7

DENMARK’S COLLABORATORS IN FP6

Other countries

Israel

112

Iceland

European Union (JRC)

Russia

China

Estonia

Latvia

Lithuania

Ireland

170

United

Kingdom

779

United States

Canada

South Africa

India

Ukraine

Brazil

Romania

Sweden

462

Norway

298

Finland

298

Poland

Netherlands

329

579

Germany

786

Belgium

419

Czech Republic

225

Slovakia

Austria

Hungary

287

Switzerland

205

France

Slovenia

Croatia

335

649

128

Italy

583

Bulgaria

Turkey

Greece

316

Cyprus

Malta

Portugal

203

Spain

538

17 The number of collaborative links is the number of times a minimum of one participant has par-

ticipated in a project with a minimum of one participant from country x.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

FIGURE 2.8

DENMARK’S COLLABORATORS IN FP7

Other countries

Israel

172

Iceland

United States

107

Finland

394

European Union (JRC)

Russia

Estonia

113

Latvia

Lithuania

Ireland

263

United

Kingdom

1214

China

Canada

Australia

South Africa

Brazil

Sweden

611

Norway

398

Poland

Netherlands

310

868

Germany

1259

Belgium

607

Czech Republic

Luxembourg

213

Slovakia

Austria

Hungary

417

Switzerland

218

France

Slovenia

Croatia

485

927

149

Serbia

Italy

864

Romania

153

Bulgaria

Turkey

129

Portugal

289

Spain

872

Greece

353

Cyprus

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

3. Importance of FP6/FP7

– perceived effects

This chapter presents an analysis of what effects Danish universities, GTS insti-

tutes

and Danish companies perceive to be the most important to them from their

participation in projects funded by FP6 and FP7. The purpose is to describe effects

that may not be identifiable in a statistical impact assessment.

3.1.

Main findings

The overall picture is that

building new European network

is perceived to be the

most crucial effect of participating in FP6/FP7 for universities and GTS institutes,

closely followed by

funding of activities that otherwise would not have been im-

plemented

and

cooperation with excellent foreign research and innovation envi-

ronments.

The differences in the perception of the most important effects between

universities and GTS institutes seem rather limited, which could indicate that uni-

versities and GTS institutes experience similar effects, despite the difference in the

main objective of their normal activities.

Danish companies perceive

funding of activities that would not otherwise have

been implemented

as the most important effect, closely followed by

cooperation

with (excellent) foreign universities and research organisations

and

access to new

knowledge.

Interestingly, small companies experience greater effects than mid-size

and large companies. Furthermore approximately half of the participating compa-

nies indicate having launched new products or services as a result of their participa-

tion in FP6 and FP7 projects.

3.2.

Methodology

The results of this chapter are based on a questionnaire which was developed on the

basis of 6 pilot interviews. The questionnaire was sent to 183 representatives from

the universities (Provosts for Research, Deans and Heads of Institutes). 74 respond-

ents from universities answered the questionnaire, giving a response rate of 40 per

cent. The questionnaire was sent to one representative (general manager) from the

9 GTS institutes and all 9 answered, giving a response rate of 100 per cent. A slightly

changed version of the questionnaire was sent to 652 Danish companies that had

participated in a FP6 or FP7 project. 116 companies answered, giving a response

rate of 18 per cent.

18 The objective of the GTS institutes is to spread the most recent knowledge and state-of-the-art

technology to the business community and thus further the competiveness of companies. Com-

panies can buy services from the GTS institutes or participate in collaboration projects that are

co-funded.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

The questionnaire to the universities and the GTS institutes listed in total 25 ef-

fects, and the questionnaire to the companies listed 16 effects. The representatives

were asked to estimate the importance of their FP6/FP7 participation on these ef-

fects on a scale of 1-5 (5 being very important). We have then ranked the effects in

order of importance.

3.3.

Effects for universities and GTS institutes

Both universities and GTS institutes perceive

building new European network

the most important effect from participating in FP6/FP7, cf. table 3.1. Universities

also rank

highly funding of activities that otherwise not would have been imple-

mented.

TABLE 3.1

FIVE MOST IMPORTANT EFFECTS OF PARTICIPATING IN FP6/FP7 FOR UNIVERSITIES AND

GTS INSTITUTES

Universities

Building new European network

Funding of activities that otherwise would not

have been implemented

Cooperation with excellent foreign research- and

foreign environments

Expansion of existing European network

International prestige

GTS Institutes

Building new European network

Cooperation with excellent foreign research- and inno-

vation environments

Access to new knowledge/knowledge retrieval

Construction of new scientific or technological

strengths

Cooperation with foreign companies

Both universities and GTS institutes find

cooperation with excellent foreign re-

search and innovation environments

as an important effect of participating. One

difference is especially worth noticing:

cooperation with foreign companies

is per-

ceived as an important effect for the GTS institutes, whereas

international prestige

is an important effect experienced by the universities. Given the results described in

chapter 6, it could be expected that the respondents from the universities would see

an important influence of FP6/FP7 on

publishing in international scientific jour-

nals,

but it is ranked as number 13 out of a total of 25 effects. Universities may not

have been aware of the outstanding performance levels of publications linked to FP6

or FP7.

It is also noticeable that the GTS institutes do not rank access to the marketing of

services / products in new markets higher than number 15. According to their latest

performance report

, the GTS institutes’ international commercial activities have

grown considerably the last 10-15 years, and around 58 per cent of the GTS insti-

tutes’ total turnover now stems from international activities.

Looking at the overall scores, the most important effect for universities and GTS

institutes is

building new European network,

rated on average 3.9 out of a maxi-

mum of 5 points. Also effects like

funding and cooperation with foreign research

and innovation environments

are perceived to be important effects when partici-

pating in FP6/FP7.

19 Teknologi for danske virksomheder, performanceregnskab for GTS-net 2015: http://2ah7jj3h-

lyru2jz2ai1v8mad.wpengine.netdna-cdn.com/wp-content/uploads/2015/06/GTS_PFR2015_

web.pdf

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

FIGURE 3.1

THE AVERAGE EFFECTS FROM FP6/FP7 PERCEIVED BY UNIVERSITIES AND GTS INSTITUTES

Building new European network

Funding of activities that otherwise would not have been implemented

Cooperation with excellent foreign research- and innovation environments

Expansion of existing European network

International prestige

Expansion of existing scientiﬁc or technological strengths

National prestige

Maintaining existing European network

Acces to new knowledge/knowledge retrieval

Building new scientiﬁc or technological strengths

Maintaining existing scientiﬁc or technological strengths

Attracting PhD-students

Publishing in international scientiﬁc journals

Access to larger empirical databases through partners in the project

Cooperation with foreign ﬁrms

Attracting international elite scientists

Internationalisation of teaching

Improving the teaching of the master students

Cooperation with danish ﬁrms

Cooperation with danish public authorities

Acces to the marketing of services/products in new markets

Cooperation with foreign public authorities

Cooperation with foreign NGO's

Improving the teaching of the bachelor students

Cooperation with Danish NGO's

2.3

2.2

2.0

1.9

1.8

3.9

3.8

3.7

3.6

3.5

3.4

3.2

3.0

2.9

2.8

2.7

2.6

3.4.

Effects for universities

In the following section we will examine the answers from the universities in more

detail, looking at the responses from different universities and different scientific

fields. It is worth mentioning that, with a limited number of respondents, some of

the conclusions should not be overstated. For instance, there are only two respond-

ents from Roskilde University (RUC) and Copenhagen Business School (CBS).

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

TABLE 3.2

FIVE MOST IMPORTANT EFFECTS FOR EACH OF THE EIGHT UNIVERSITIES

SDU

International

prestige

Building new

European net-

work

Cooperation

with excellent

foreign research

and innovation

environments

Funding of

activities that

otherwise would

not have been

implemented

Maintaining ex-

isting European

network

National prestige

Expansion of ex-

isting European

network

Building new

European net-

work

Cooperation

with excellent

foreign research-

and innovation

environments

Expansion of ex-

isting European

network

Expansion of ex-

isting European

network

Publishing in

international sci-

entific journals

Funding of

activities that

otherwise would

not have been

implemented

Funding of

activities that

otherwise would

not have been

implemented

Building new Eu-

ropean network

Cooperation

with excellent

foreign research-

and innovation

environments

Cooperation

with excellent

foreign research-

and innovation

environments

CBS

Access to larger

empirical data-

bases through

partners in the

project (eg.

Patients, cases,

registration data

etc.)

Funding of

activities that

otherwise would

not have been

implemented

Cooperation

with excellent

foreign research-

and innovation

environments

Expansion of ex-

isting European

network

Building new Eu-

ropean network

Expansion of ex-

isting European

network

DTU

Building new

European net-

work

Maintaining ex-

isting European

network

Expansion of ex-

isting European

network

Cooperation

with excellent

foreign research-

and innovation

environments

Access to new

knowledge/

knowledge

retrieval

Cooperation

with excellent

foreign research-

and innovation

environments

International

prestige

ITU

Building new

European net-

work

International

prestige

Publishing in

international

scientific jour-

nals

Maintaining ex-

isting European

network

AAU

Funding of

activities that

otherwise would

not have been

implemented

Funding of

activities that

otherwise would

not have been

implemented

Building new Eu-

ropean network

RUC

Building new

European net-

work

Maintaining ex-

isting European

network

Expansion of ex-

isting European

network

When looking at the effects perceived the eight universities are not that different

from each other. The most important effect perceived is either

funding of activities

that otherwise would not have been implemented

building new European net-

work,

cf. table 3.2.

Although the universities are quite similar, some of the effects differ in smaller

detail. The respondents from CBS rank

access to larger empirical databases

the second most important of the effects, and CBS is the only university that has

this specific effect in the top 5. The respondents from the University of Southern

Denmark (SDU) are the only ones that rank

national prestige

as a top 5 effect. The

respondents from Aarhus University (AU) have experienced the highest effects,

together with the respondents from the Technical University of Denmark (DTU).

This is not surprising, due to the fact that DTU is a fairly specialized university that

matches the themes in both FP6 and FP7.

20 SDU: University of Southern Denmark; KU: University of Copenhagen; AU: Aarhus University;

CBS: Copenhagen Business School; DTU: Technical University of Denmark; ITU: IT-University;

AAU: Aalborg University; RUC: Roskilde University

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

FIGURE 3.2

AVERAGE EFFECT OF THE EIGHT UNIVERSITIES

3.5

3.0

2.5

2.0

1.5

1.0

0.5

0.0

SDU

CBS

DTU

ITU

AAU

RUC

Note: Each university ranks the individual effects from 1-5, 5 indicating significant effect. The line

illustrates the average effect of the universities.

The respondents from RUC, which is mainly a university for the humanities and so-

cial sciences, evaluate that the effects in general are smaller.

The overall picture is more or less the same when the rated effects are divided

into the fields of science. In general the fields of science that experience the highest

effect are agricultural sciences as well as engineering and technology, cf. figure 3.3.

This is in line with the observations for the universities, where, for example, DTU

experienced high effects.

FIGURE 3.3

AVERAGE EFFECT OF PARTICIPATION ACROSS FIELD OF SCIENCE

Agricultural

Sciences

Engineering and

technology

Natural

Sciences

Medical

Sciences

Humanities

Social

Sciences

3.4

3.2

2.9

2.8

2.7

Correspondingly, social sciences experience the lowest effects of participating in

FP6/FP7. When looking at the top-rated effects of participating,

building new Eu-

ropean network

is the highest-ranked effect for humanities, agricultural, medical

and technical science, cf. table 3.3. Agricultural science in particular experiences

higher effects than average.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

TABLE 3.3

FIVE MOST IMPORTANT EFFECTS DIVIDED BY FIELDS OF SCIENCE FOR THE UNIVERSITIES

Humanities

Building new

European net-

work

Building new

European net-

work

Expansion of

existing Euro-

pean network

Expansion of

existing Euro-

pean network

Access to new

knowledge/

knowledge

retrieval

Cooperation

with excel-

lent foreign

research- and

innovation en-

vironments

Maintaining ex-

isting European

network

Expansion

of existing

scientific or

technological

strengths

Attracting PhD

students

Agricultural

Sciences

Access to

larger empiri-

cal databases

through part-

ners in the

project (eg.

Patients, cases,

registration

data etc.)

National pres-

tige

Natural

Sciences

Funding of

activities that

otherwise

would not have

been imple-

mented

Funding of

activities that

otherwise

would not have

been imple-

mented

Building new

European net-

work

Expansion of

existing Euro-

pean network

Cooperation

with excel-

lent foreign

research- and

innovation en-

vironments

International

prestige

Building new

European net-

work

Social

Sciences

Cooperation

with excel-

lent foreign

research- and

innovation en-

vironments

Funding of

activities that

otherwise

would not have

been imple-

mented

Funding of

activities that

otherwise

would not have

been imple-

mented

National pres-

tige

Building new

European net-

work

Medical

Sciences

Expansion of

existing Euro-

pean network

Cooperation

with excel-

lent foreign

research- and

innovation en-

vironments

Expansion of

existing Euro-

pean network

Maintaining ex-

isting European

network

Enginee-

ring and tech-

nology

Building new

European net-

work

Maintaining ex-

isting European

network

Expansion

of existing

scientific or

technological

strengths

For both natural sciences and social sciences, the highest-rated effect is

funding

of activities that otherwise would not have been implemented.

Social science and

medical science are the only fields of science with

international prestige

rated in top

5 effects.

The answers collected from the universities are now divided into three different po-

sitions: Head of Institution, Dean and Provost for Research. Overall the Provosts for

Research estimate FP6/FP7 to have a stronger influence on a number of effects than

their colleagues.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

TABLE 3.4

FIVE MOST IMPORTANT EFFECTS DIVIDED INTO JOB POSITIONS AT THE UNIVERSITIES

Head of Institute

Funding of activities that

otherwise would not have

been implemented

Building new European

network

Expansion of existing Eu-

ropean network

Cooperation with excel-

lent foreign research and

innovation environments

Maintaining existing Euro-

pean network

Dean

Building new European network

Provost for Research

Building new European network

Expansion of existing European net-

work

Cooperation with excellent foreign re-

search and innovation environments

Funding of activities that otherwise

would not have been implemented

International prestige

Cooperation with excellent foreign re-

search and innovation environments

Publishing in international scientific

journals

Access to new knowledge/knowledge

retrieval

International prestige

For the Provosts, an important effect they experienced is

publishing in interna-

tional scientific journals.

This may not be surprising when measuring the effects on

universities, but was nevertheless not ranked in the top 5 for all respondents from

the universities.

The numbers of participations vary for the individual institutions. In general,

when participating between 0-20 times in either FP6 or FP7, the institutions seem

to experience FP6/FP7 as having a less important influence on a number of effects

than when participating more often. But the main effects are still the same, re-

gardless of the number of participations.

Prestige,

both national and international,

seems to become more important, though, when participating more often cf. table

3.5.

TABLE 3.5

FIVE MOST IMPORTANT EFFECTS DIVIDED INTO NUMBER OF PARTICIPATIONS,

UNIVERSITIES AND GTS INSTITUTES

0-20

FP6 participations

Building new European

network

Above 21

FP6 participations

Cooperation with

excellent foreign re-

search- and innovation

environments

Building new European

network

0-20

FP7 participations

Building new European

network

Above 21

FP7 participations

Building new European

network

Funding of activities that

otherwise would not have

been implemented

Cooperation with excel-

lent foreign research and

innovation environments

Expansion of existing Eu-

ropean network

Building new scientific or

technological strengths

Cooperation with

excellent foreign re-

search- and innovation

environments

Funding of activities

that otherwise would

not have been imple-

mented

Building new scien-

tific or technological

strengths

Expansion of existing

European network

Cooperation with

excellent foreign re-

search- and innovation

environments

Expansion of existing

European network

Funding of activities

that otherwise would

not have been imple-

mented

International prestige

National prestige

Maintaining existing

European network

Looking closely at the share of external funding that comes from FP6/FP7, there do

not seem to be great differences with regard to the effects perceived, cf. table 3.6.

Overall the effects are the same, independent of the share of the total external fund-

ing.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

TABLE 3.6

FIVE MOST IMPORTANT EFFECTS FOR THE SHARE OF EXTERNAL FUNDING OF THE

INSTITUTIONS THAT COMES FROM FP6/FP7 (THE TOTAL POPULATION)

FP6 share 0-20

per cent

Building new Eu-

ropean network

Cooperation with

excellent foreign

research and

innovation envi-

ronments

Funding of activ-

ities that other-

wise would not

have been imple-

mented

Expansion of ex-

isting European

network

International

prestige

FP6 share 21-50

per cent

Funding of activities that

otherwise would not have

been implemented

Maintaining scientific or

technological strengths

FP7 share FP7 0-20

per cent

Building new European

network

Funding of activities that

otherwise would not have

been implemented

FP7 share 21-50

per cent

Cooperation with excellent

foreign research and inno-

vation environments

Cooperation with foreign

companies

Expanding new scientific

or technological strengths

International prestige

Building new European

network

Building new European

network

Cooperation with excellent

foreign research and inno-

vation environments

Expansion of existing Euro-

pean network

Cooperation with excellent

foreign research and inno-

vation environments

Access to new knowledge/

knowledge retrieval

Funding of activities that

otherwise would not have

been implemented

When looking at the degree of importance, the results indicate that the larger the

FP6/FP7 share of participations, the more the institutions experience higher effects

of the funding, cf. figure 3.4.

FIGURE 3.4

AVERAGE EFFECT SCORE FOR THE SHARE OF EXTERNAL FUNDING OF THE INSTITUTIONS,

THE TOTAL POPULATION

3.5

3.0

2.5

2.0

1.5

1.0

0.5

0.0

Funding 0-20%

FP6

Funding 21-50%

FP6

Funding 0-20%

FP7

Funding 21-50%

FP7

3.5.

Effects for private companies

Private companies rank

funding of activities that otherwise would not have been

implemented

highest and

cooperation with (excellent) foreign universities and re-

search organisations

second highest. Just like the GTS institutes, companies do not

rank

access to the marketing of services/products in new markets

highly. In fact it

is the effect with the lowest average score of 2.56 (the highest average is 3.97).

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

TABLE 3.7

FIVE MOST IMPORTANT EFFECTS OF PARTICIPATING IN FP6/FP7 FOR COMPANIES

Private companies

Funding of activities that otherwise would not have been implemented

Cooperation with (excellent) foreign universities and research organisations

Access to new knowledge

Building and expansion of existing European network

Building new technological strengths

When looking at the importance of FP6/FP7 for the different size of companies,

small and medium-sized companies experience higher effects than medium-sized

companies and large companies. On average, small companies (0-50 employees)

evaluate the effects of FP6/FP7 on all named parameters with a score of 3.77 (on a

scale of 1 – 5), whereas the figures are 3.09 for medium-sized companies (50-250)

and 3.21 for large companies. An explanation would be that the participation in a

FP6 or FP7 project is more important for a small company, where EU project fund-

ing can amount to a considerable percentage of the company’s overall expenditure

on research and innovation, whereas the isolated effect for a large company will be

more difficult to identify.

FIGURE 3.4

AVERAGE EFFECT BY FP6/ FP7 ON ALL PARAMETERS FOR SMALL COMPANIES, MEDI-

UM-SIZED COMPANIES AND LARGE COMPANIES

Importance of FP6/FP7

4.0

3.5

3.0

2.5

2.0

Small companies

Medium-sized companies

Large companies

When asked if their participation in FP6 or FP7 projects has led to the launching of

new products or services, 49 per cent answer in the affirmative. Considering that

research and innovation projects often have uncertain outcomes, this figure is quite

high. Launching of new products or services should hopefully have a positive effect

for the company on both turnover and the number of employees. 18 per cent answer

that their participation has led to the admission of new patents. It is not surprising

that new products or services are not necessarily linked to the issuance of patents,

and therefore this figure is equally considered to be quite high.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

TABLE 3.8

HAS YOUR PARTICIPATION IN FP6/FP7 PROJECTS LED TO THE LAUNCHING OF NEW

PRODUCTS OR SERVICES?

Yes

Don’t know

49 %

43 %

TABLE 3.9

HAS YOUR PARTICIPATION IN FP6/FP7 PROJECTS LED TO THE ADMISSION OF NEW

PATENTS?

Yes

Don’t know

18 %

79 %

Although we were unable to detect any statistically significant increase in the share

of PhDs and masters employed (chapter 4), almost half of the companies answering

the questionnaire reply that their participation in FP6/FP7 projects has led to the

employment of new knowledge workers. See table 3.10 below.

TABLE 3.10

HAS YOUR PARTICIPATION IN FP6/FP7 PROJECTS LED TO THE EMPLOYMENT OF NEW

KNOWLEDGE WORKERS?

Yes

Don’t know

46 %

51 %

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

4. Economic impact on

FP6/FP7-participating

companies

This chapter presents the impact assessment of company participation in FP6 and

FP7 projects. The purpose is to gain a better understanding of what economic im-

pact the participating companies gain from taking part in projects under FP6 and

FP7.

Using detailed employer-employee-linked data spanning from 2000 to 2012, we

first describe participating companies relative to other companies. We then perform

a five-year forward-looking impact assessment of company participation in projects

initiated between 2002 and 2008, which are evaluated from the end of 2007 to the

end of 2012.

The premise for the existence of public support for public-private research part-

nerships such as the Sixth Framework Programme (FP6) or the Seventh Framework

Programme (FP7) is that the financial support will strengthen research activity

within industries — and thus companies. This impact assessment is a micro study of

the average isolated effects of participation of the individual companies. It does not

focus on macro outcomes such as increasing the size and strength of the research

infrastructure of industries, which is an overall objective of the framework pro-

grammes.

Because FP6/FP7 projects offer access to top scholars in the academic world,

strengthen international relations and thus potentially widen the scope for business,

we are particularly interested in finding out whether participation leads to higher

long-term investments in Danish research and development (R&D) activity, added

economic growth and value creation.

To perform such an analysis we must establish the alternative scenario: What

would have happened had these companies not participated in FP6/FP7 projects?

For this purpose, we construct a control group of companies to perform a counter-

factual analysis. A very useful and well-recognised tool for this purpose is a match-

ing analysis. For each participant, we find a similar, non-participating company we

might expect to participate. We try to mitigate the selection bias of participants who

are not randomly picked for projects.

We assess impact through six performance variables that cover knowledge in-

tensity, value creation and growth. More specifically, we measure the share of em-

ployees that hold at least a master’s degree, export intensity, labour productivity,

full-time equivalent employees and revenue. Unfortunately, not enough of the par-

ticipating companies are covered by the Danish R&D expenditure statistics. Thus we

have to rely on indirect indicators of R&D intensification.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

4.1.

Main findings

The overall picture that we obtain from the analysis is that FP6/FP7 companies are

quite different from the average Danish company on a range of economic perfor-

mance indicators. They gain, on average, about 40 per cent of their revenue through

exports, grow revenue at a fast pace, and employ intensively highly-skilled workers.

Larger companies also make up a larger percentage of the participating companies

compared to their general share of companies in Denmark. The largest share of par-

ticipants is found in the following industries: manufacturing, professional, scientific

and technical activities.

Our results from the assessment of impact on a range of different performance

variables suggest that participating companies do outperform comparable non-par-

ticipating companies. The difference is, however, not statistically significant, mean-

ing that it is not possible to identify whether the difference is random or due to FP6/

FP7 participation. What characterises participating companies is the intensive use

of highly-skilled employees, and a high degree of exports. In other words, these

companies have, in general, already succeeded in breaking through into interna-

tional markets, and they are, regardless of their participation in FP6/FP7 projects,

well-run companies that do not seem to be critically dependent on particular fund-

ing of public-private research partnership projects.

We emphasize that our matching sample for the impact assessment – though on

average resembling the total population of participating companies and by size large

enough to mechanically test mean differences — should preferably have been larger,

with more observed participating companies and more control companies. Having

a larger sample would have made us able to assert more rigorously whether, for

example, a few individual outlier matches of participating companies and control

companies that may appear to be good matches at the matching point are not too

influential on the group means. Furthermore, the sample size limits the scope for

digging deeper and searching for subgroup trends.

The impact assessment task is demanding: we require that the impact can be

measured already five years after project start, and 1) not be influenced significantly

by other decisions or circumstances within the company, and 2) that projects with

an average dedicated budget of less than a third of the cost of a full-time equiva-

lent (FTE) employee can stimulate change at the overall performance level of the

company — a company that has already dedicated resources for employing high-

ly-skilled employees.

Despite missing statistically significant and positive results from the analysis of

six company performance variables, project participation may still play an impor-

tant role for the companies that we cannot measure. The motivation for partici-

pating may also be related to indirect objectives for future growth and earnings

potential, e.g. by serving as signalling to other potential partners or investors, or

networking, including lower recruitment search costs. Such reasoning and associ-

ated outcomes are difficult to identify in an economic impact assessment.

The chapter proceeds as follows: Section 4.2 presents a descriptive view of FP6/

FP7 participants, while section 4.3 presents the results of the impact assessment.

Section 4.4 sums up.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

4.2.

Characteristics of participating companies

This section briefly describes the characteristics of the companies participating in

FP6/FP7. In our descriptive statistics we observe 400 unique companies partici-

pating in FP6/FP7. We have aggregated the industries into three relevant, broad

sectors and a residual sector (“Other”). Thus, the described figures presented in this

section are aggregated accordingly. (This has no influence on the impact assessment

later on.) Figure 4.1 compares the average allocation of Danish companies partici-

pating in FP6/FP7 projects between 2002 and 2012 to the allocation of the number

of active companies (legal entities) in the Danish economy during the same period.

Clearly, these two distributions of companies are different. While Danish manufac-

turing companies constitute 15 per cent of all active Danish companies, 38 per cent

of all participating companies belong to the manufacturing sector. Together with

companies in the sector Professional, scientific and technical activities (Scientific

etc. in the figure), these companies make up 78 per cent of all participating compa-

nies.

FIGURE 4.1

RELATIVE ALLOCATION OF COMPANIES BY INDUSTRY

Pct.

69 %

38 %

15 %

40 %

12 %

Scientiﬁc etc.

10 %

Other

Inform. & Comm

Industry share, all

Manufacturing

Industry share, participants

Source: DASTI’s own calculation using registry data from Statistics Denmark and eCORDA data-

base.

Within the four sectors, the participating companies are also different from other

companies. The average share of their employees that hold at least a master’s degree

is higher. The same is the case for the share of PhDs employed, cf. figure 4.2.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

FIGURE 4.2

AVERAGE SHARE OF

MAs/M.Sc.s

AND

PhDs

BY INDUSTRY

Pct.

All Participants

Inform. & Comm

MA/M.sC. share

Manufacturing

PhD share

Scientiﬁc etc.

Other

Total

Note: The stacked bars are indicative, as they are simple averages of PhD shares and MA/M.Sc.

shares across companies.

Source: DASTI’s own calculation using registry data from Statistics Denmark and the eCORDA da-

tabase.

Participating companies are in general considerably dependent on export sales. In

the manufacturing sector the relative share of exports to total revenue is on average

58 per cent compared to 17 per cent in general. The difference is also notable in

other sectors of the economy, cf. figure 4.3.

FIGURE 4.3

RELATIVE SHARE OF REVENUE FROM EXPORTS

Pct.

58 %

39 %

27 %

17 %

Inform. & Comm

Export intensity

Manufacturing

Scientiﬁc etc.

Other

Total

25 %

40 %

Export intensity, participants

Source: DASTI’s own calculation using registry data from Statistics Denmark and the eCORDA da-

tabase.

In addition to belonging to certain sectors and relying heavily on the highest skill

types of labour, large companies are also more frequently represented in FP6/FP7

than comparable companies in general, cf. figure 4.4.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

FIGURE 4.4

COMPANY SIZE AND (WITHIN) INDUSTRY ALLOCATION

Pct.

100

Total (Participants)

Inform. & Comm

(All)

Scientiﬁc etc.

(All)

Other

(Participants)

Inform. & Comm

(Participants)

Scientiﬁc etc.

(Participants)

Manufacturing

(All)

Manufacturing

(Participants)

Other (All)

Total (All)

Employees <49

Employees 50-249

Employess 250+

50-249

Employees

Employees <49

Notes: Companies participating more than once are counted individually. Employees are measured

as full-time equivalent employees.

Group

Source: DASTI’s own calculation using registry data from Statistics Denmark and the eCORDA-da-

tabase.

About 90 per cent of all Danish manufacturing companies have less than 50 em-

ployees, whereas only 40 per cent of the participating manufacturing companies

have less than 50 employees. The picture is that small companies constitute a con-

siderable share of the participating companies, but large companies are relatively

more represented among participants than their share of the Danish distribution

of companies by size. A few large companies tend to increase the overall average

number of employees, and the median participating company has about 40-70 em-

ployees.

Clearly, when performing an impact assessment by matching participating com-

panies with other similar companies that are likely to be participants, we must ad-

dress the characteristics — and others — presented above. The participating compa-

nies are high-performance companies compared to the average Danish company.

4.3.

Impact assessment

We base our impact assessment on a difference-in-differences matching analysis.

Our sample time span covers a five-year window, which is aligned individually for

each company according to observed participation initiation (i.e. some participate

in 2003, some in 2007 etc.).

We start by briefly describing how we measure impact

before presenting the results.

4.3.1. The matching sample

The data sample for the impact assessment has been carefully constructed by com-

bining propensity score matching with pre-selection of possible control group com-

panies to accommodate selection bias, 1-1 matching within each year on industry,

Our outcome variables in the analysis are differences between base year and up to five years for-

ward.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

and exporter status, and to a large extent on employment (intervals).

Finally the

sample has been examined and cleared for outliers and unlikely matches, despite

the rigorous matching process and balancing testing.

The matching process ensures that we are comparing participating companies

with non-participating companies that are likely to have participated in the same

industries.

Figure 4.5 briefly shows the main process of the sample construction leading to

the impact assessment. We draw control group companies from the Innovation

Denmark database. This database covers Danish national innovation and research

support programme participation by companies and their potential project partners

(universities, research institutions, etc.). Potential control group companies include

companies that at some point in time between 2000 and 2012 have participated

in national public-private collaboration projects.

We do this to mitigate selection

issues in such a highly selective programme as FP6/FP7. Participation in other

collaboration programmes indicates that these could also be successful in FP6/FP7

projects.

FIGURE 4.5

AN OVERVIEW OF THE STEPS OF THE MATCHING SAMPLE CONSTRUCTION

Step #1

Full sample match of

companies and their

employees

Step #2

Indentifying level 2 NACE

industries with FP6/FP7

participants (discarding

other industries)

Step #3

Pre-selecting companies

for the control group that

have participated in na-

tional public-private col-

laboration programmes.

Step #6

Matching remaining par-

ticipants and non-partici-

pants (nearest neighbour

on matching and one-

to-one on year, industry,

employment intervals,

and export status)

Step #5

Estimating propensity

scores on the restricted

sample of participants

and non-participants

Step #4

Discarding participants

and non-participants that

participate in FP6/FP7 up

to three years before ob-

served project initiation

Step #7

Difference-in-differences match-

ing estimation of isolated partic-

ipation effect of participating in

FP6/FP7 projects

IMPACT ASSESSMENT

The resulting sample consists of participating companies that are matched with

highly similar companies not participating that we can observe for five years. The

22 In the intervals “250-499” and “+500”, there are a few odd matches, but company size is still

relatively well-matched.

23 The control group companies have either participated in Research Voucher, The Danish Na-

tional Advanced Technology Foundation or Innovation Consortia.

24 We also tested matching with all companies (irrespective of prior participation in national sup-

port programme) as potential control group companies. This does not result in different conclu-

sions.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

sampled participants are drawn from a population of 344 unique participating

companies between 2002 and 2008 (to observe companies five years forward from

latest 2007 to 2012). Because participating companies sometimes return to partic-

ipate, we must be aware of not using participating companies as controls at a later

point, or evaluating them as participants again when the impact of an earlier project

may start to kick in. Therefore, the analysis has a clear 3-year window to obtain the

effects of participating in FP6/FP7. Table 4.1 presents the results of the matching

procedure. The table below presents averages, but it is worth mentioning that the

median company has between 40 and 60 employees, which is similar to the full

population of participating companies.

TABLE 4.1

THE MATCHING SAMPLE

Participants

Number of companies

Revenue (million DKK)

Total fixed assets (million DKK)

EBIT (million DKK)

Labour productivity (thousand DKK)

FTE employment

FTE size categories

- FTE<50

- FTE 50-249

- FTE 250-499

- FTE 500+

Export intensity

MA/M.Sc. share

PhD share

Company age

0.49

0.27

0.12

0.45

0.22

0.06

18.29

0.49

0.28

0.16

0.07

0.45

0.20

0.05

17.31

-3.9

-11.5

19.6

-0.7

14.5

0.6

5.9

0.00

-0.30

-0.76

1.35

-0.05

1.05

0.04

0.46

1.00

0.77

0.45

0.18

0.96

0.29

0.97

0.65

110

210.92

109.14

12.84

467.54

166.72

Control group

107

180.27

126.68

10.37

475.58

142.35

t-test for match quality

%-bias

9.5

-6.2

4.6

-1.9

12.1

t-value

0.74

-0.37

0.33

-0.15

0.86

p-value

0.46

0.71

0.74

0.88

0.39

Note: All companies are matched using propensity score matching and one-to-one match on

semi-aggregated NACE 2 industries (see separate technical note), export status, FTE interval dum-

mies, and participation year minus one.

Source: DASTI’s own calculation using registry data from Statistics Denmark and the Innovation

Denmark-database.

The sampled companies participating in FP6/FP7 resemble the full population of

participating companies well, also with regard to the overall budget for the FP6/FP7

project they participated in, as well as their own share of the project’s budget. The

sample includes relatively few companies that participated in projects receiving an

EU contribution of +70 per cent of the project’s budget rather than in the full popu-

lation of participating companies, cf. figure 4.6.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

FIGURE 4.6

EU CONTRIBUTION AS SHARE OF PROJECT BUDGET (EU CO-FINANCING)

Pct.

74 %

53 %

45 %

24 %

0-30 %

31-70 %

All participants

71-100 %

Sampled participants

Source: DASTI’s own calculation using registry data from Statistics Denmark, the InnovationDen-

mark-database and eCORDA database.

The sampled companies participating in FP6/FP7 also have to resemble the full

population of participating companies with regard to the importance of the EU

contribution in relation to the company’s research capacity. Therefore, the project

budget was distributed on employees within R&D. An average project in the sample

has a budget of roughly DKK 400,000 per employee holding an MA, M.Sc., or PhD,

cf. figure 4.7.

FIGURE 4.7

BUDGET IN DKK PER

MA/M.Sc./Ph.D

DKK

700,000

600,000

500,000

400,000

300,000

200,000

100,000

606,529

414,979

285,447

450,409

424,060

420,630

478,926

383,092

0-30 %

Sampled Participants

31-70 %

71-100 %

Total

All Participants

Note: The mean for “All, 31-70 per cent” excludes a few companies (99th percentile) with very high

budgets per employee that disturb the overall picture of the distribution of budget per employee.

Source: DASTI’s own calculation using registry data from Statistics Denmark, the InnovationDen-

mark database and eCORDA database.

4.3.2. Results

In this section we illustrate the development of six key performance variables:

The share of PhDs employed, share of masters employed, export intensity, labour

productivity (value added per full-time equivalent employee), full-time equivalent

labour force (FTE), and revenue. These variables sum up indicators for organic

The measure is not perfect because non-scientific personnel also hold master’s degrees. Only

using PhDs, on the other hand, would exclude companies that do not employ PhDs. Therefore

value itself is not as interesting as creating a common unit for comparison across companies of

varying size and skill levels.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

growth (revenue, exports and employment), longer-term investments in research

activities (skill intensity), and increased value creation (labour productivity). The

illustrations sum up the average development of the participants and their compa-

rable control companies (i.e. companies are followed up to five years ahead but from

different points in time). This illustration approach can blur the results, because of

business cycle trends. However, we correct for business cycle trends in our formal

tests of impact (i.e. the underlying difference-in-differences estimation).

We start out by inspecting the structural indicators of intensifiying R&D, follow-

ing the startup of an FP6/FP7 project. Developments in the intensity level of skilled

labour may indicate that by entering FP6/FP7 projects, companies focus more in-

tensively on research than before. The development in the share of PhDs indicates

that participating companies, on average, intensify their use of PhDs, cf. figure 4.8.

The share of PhDs for control group companies has a declining trend. The difference

in the development of the two groups is, however, not statistically significant. The

same case applies to the share of masters employed in the sampled companies.

FIGURE 4.8

SHARE OF

PhDs

Pct.

-2

-1

-2

-1

FIGURE 4.9

SHARE OF

MA/M.Sc.s

AND

PhDs

Pct.

Control group

Participants

Control group

Participants

Source: Matching analysis performed on data from Statistics Denmark and eCORDA database.

Because FP6/FP7 facilitates Danish companies to team up with global partners, it

seems relevant to investigate whether export intensity levels change differentially

from control group companies. Export intensity levels do increase over time, but

they are not significantly different for the two groups of companies, cf. figure 4.10.

On average, participating companies, though not developing significantly differently

from control group companies, increase labour productivity by about 6 per cent per

annum over a five-year period, cf. figure 4.11.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

FIGURE 4.10

EXPORT INTENSITY

Pct.

-2

-1

FIGURE 4.11

LABOUR PRODUCTIVITY

Index: -1=100

140

130

120

110

100

-2

-1

Control group

Participants

Control group

Participants

Source: Matching analysis performed on data from Statistics Denmark and eCORDA database.

There seems to be stagnation in employment, cf. figure 4.12, both for the partici-

pating companies and the control group. This stagnation could be the result of the

abrupt change of development in the employment level past mid-2008. However,

the average accumulated growth in revenue post participation shows that the aver-

age growth rate over a five-year period is 42 per cent, cf. figure 4.13. Behind this av-

erage growth of 42 per cent over five years we find varying growth rates for each of

the matching years ranging from 25 to 58 per cent. Common for full-time equivalent

employment and revenue is that the developments are not significantly different

from the control group companies.

FIGURE 4.12

EMPLOYMENT

Index: -1=100

130

120

110

100

-2

-1

FIGURE 4.13

REVENUE

Index: -1=100

150

140

130

120

110

100

-2

-1

Control group

Participants

Control group

Participants

Note: Accumulated average growth in employment and revenue relative to the base level in year -1

(index 100).

Source: Matching analysis performed on data from Statistics Denmark and eCORDA database.

One interpretation for not observing a differential increase for participating com-

panies is that participation does not stimulate isolated increases in business perfor-

mance in the short run.

The overall picture that we obtain from this analysis is that FP6/FP7 companies

and the very similar control group of companies are highly unusual companies com-

pared to the average Danish company. They export, on average, about half of their

revenue, grow revenue at a fast pace, and employ intensively highly-skilled workers.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

4.4.

Why the missing statistical difference in impact?

Working with micro analysis of companies and comparing growth rates is always

difficult, because standard errors of growth terms are often relatively large. Micro

level growth is often abrupt and unpredictable.

When comparing the development of revenue, export intensity, and labour pro-

ductivity, participating companies grow faster but not statistically significantly.

We have tried to find control group companies that could have participated, but

ultimately it is very difficult to tell whether decisions to initiate a project crucially

depend on FP6/FP7 funding or not.

More observations could allow an even more rigorous selection of control com-

panies. Searching for other indicators should also be part of future reassessments

of the impact, as should further discussion about which other public R&I funding

systems participating and control group companies participate in.

Reassessment some years from now should be done, when the number of ob-

servations could be increased. Longer time spans might also help some years from

now; however, the further away from the base year we evaluate impact, the more

likely other factors are to play a role. These issues should be discussed before new

assessments can be made.

Finally, note that both participating and non-participating companies are strong

economic performers that create and increase value by exporting.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

5. Private companies’ use

of FP6, FP7 and the Danish

national research and

innovation system

This chapter presents a mapping of the FP6 or FP7-participating Danish companies’

use of the Danish research and innovation (R&I) system. The purpose is to gain a

better understanding of what the links are between the funding opportunities in

FP6 and FP7 and the Danish R&I system for Danish companies.

As far as the methodology is concerned, data from the European Commission’s

eCORDA database are linked together with data from the InnovationDenmark data-

base (see box 5.1), which include data from 14 different Danish R&I schemes.

5.1.

Main findings

The participating Danish companies in FP6 or FP7 are multiple users of the Danish

R&I system. Approximately two-thirds of the companies participating in FP6 or FP7

have participated in one or more Danish R&I scheme.

There is a positive correlation between the number of different schemes the com-

panies participate in and the size of the companies.

The companies participating in FP6 or FP7 make up a relatively large share of the

companies that take part in large-scale programmes

– programmes which are sim-

ilar to FP6 or FP7.

There is an increasing participation in other schemes up to the time when the

companies take part in FP6 or FP7.

5.2.

The companies’ use of the Danish research and innovation

system

The mapping shows that the Danish companies participating in FP6 or FP7 make

use of the different schemes in the Danish R&I system. Approximately two-thirds of

the Danish companies participating in FP6 or FP7 have also participated in one or

more schemes in the Danish R&I system (see figure 5.1).

37 percent of the companies participating in FP6 or FP7 have not received any

funding from the Danish R&I system. One in four Danish companies from FP6 or

26 The Danish National Advanced Technology Foundation, The Danish Council for Strategic

Research and Strategic Platforms for Innovation and Research.

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

FP7 has participated in one scheme in the Danish R&I system. Approximately 40

per cent of the participating companies have participated in more than one national

scheme. The participating Danish companies in FP6 or FP7 are in other words mul-

tiple users of the Danish research and innovation system.

When looking at the size of the participating companies in FP6 or FP7 that do or

do not participate in the Danish research and innovation system, there is a positive

correlation between the number of different schemes the companies participate in

and the size of the company. Figure 5.2 shows that approximately 90 per cent of

the companies that only participate in one scheme are SMEs, while SMEs account

for only approximately 40 per cent of the companies that participate in 5 to 8 other

schemes. 97 per cent of the companies that do not participate in any Danish R&I

scheme, but that are in FP6 or FP7, are SMEs.

FIGURE 5.1

SHARE OF PARTICIPATION OF UNIQUE

COMPANIES FROM FP6 OR FP7 IN THE

DANISH RESEARCH AND INNOVATION

SYSTEM FOR THE PERIOD 2002-2013

FIGURE 5.2

SIZE OF THE COMPANIES FROM FP6 OR

FP7 RELATED TO THEIR PARTICIPATION IN

THE DANISH RESEARCH AND INNOVATION

SYSTEM FOR THE PERIOD 2002-2013

Pct.

100

0 schemes

1 scheme

2 schemes

3 schemes

4 schemes

5-8 schemes

10%

15%

25%

37%

0 schemes

3 schemes

1 scheme

4 schemes

2 schemes

5-8 schemes

1-49 employees

50-249 employees

Over 250 employees

Note: The figures are based on unique participation both in FP6, FP7 and other schemes, so the

companies can have participated more than once in the different schemes, but this only accounts for

one.

Source: The Danish Agency for Science, Technology and Innovation, the InnovationDenmark Data-

base 2015.

5.3.

The most popular Danish research and innovation schemes

When looking at the different Danish schemes that the participating Danish com-

panies in FP6 and FP7 took part in, the most popular one is Innovation Network

Denmark. This is not surprising, as an analysis of the Danish companies’ use of the

Danish national and regional innovation and research funding landscape (DASTI

2013)

showed that Innovation Network Denmark is the entrance to the national

research and innovation system. Only 5 per cent of the companies in Innovation

Network Denmark, however, have participated in FP6 or FP7. This indicates that

there is a potential for an increased participation in EU framework programmes.

27 DASTI (2013), Sammenhæng for vækst og innovation. En databaseret kortlægning af sammen-

hænge i udbud og efterspørgsel i det danske innovations- og erhvervsfremmesystem.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

The participating companies in FP6 or FP7 make up a relatively large share of the

companies that take part in large-scale programmes

– programmes which resem-

ble thematic areas under FP6 or FP7. They account for approximately 35 to 45 per

cent of the total participation of unique companies.

TABLE 5.1

SHARE OF DANISH COMPANIES PARTICIPATING IN FP6 OR FP7 THAT ALSO TOOK PART

IN ONE OR MORE SCHEMES IN THE DANISH R&I SYSTEM OUT OF THE TOTAL NUMBER OF

COMPANIES THAT PARTICIPATE IN THE SAME SCHEME FOR THE PERIOD 2002-2013

Number of

companies

Innovation Networks Denmark

The Danish National Advanced Technology Foundation

Industrial PhD

Innovation Consortia

Innovation Vouchers

Innovation Agents

The Innovation Incubator Scheme

The Danish Council for Strategic Research

EUopSTART

Strategic Platforms for Innovation and Research (SPIR)

Open Funds

Knowledge Pilots

Gazelle Growth

Research Vouchers

Spin-outs from Danish Universities

Total

265

113

112

103

960

Share of FP6/FP7

companies in the

same scheme

35 %

24 %

22 %

45 %

35 %

16 %

22 %

Note: The table is based on unique participation both in FP6, FP7 and other schemes, so the compa-

nies can have participated more than once in the different schemes, but it only accounts for one.

Source: The Danish Agency for Science, Technology and Innovation (2015), the InnovationDenmark

Database.

5.4.

The entrance to the Danish research and innovation system

Figure 5.3 shows when the participating companies in FP6 or FP7 take part in other

schemes over a period of five years before and five years after their participation in

FP6 or FP7. 46 per cent of the companies participated in another scheme under the

Danish R&I system before their participation in FP6 and FP7, while 54 per cent did

after.

Year 0 shows the number of companies that obtained a grant from FP6/FP7 par-

ticipated a Danish scheme within the same year. Year 1 shows the number of com-

panies that participated in a national scheme the year after the start of their FP6/

FP7 participation.

There is a trend towards an increasing participation in national schemes prior to

FP6/ FP7 participation.

28 The Danish National Advanced Technology Foundation, The Danish Council for Strategic Re-

search and Strategic Platforms for Innovation and Research

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

FIGURE 5.3

PARTICIPATION OF UNIQUE COMPANIES IN FP6 OR FP7 AND OTHER LARGE-SCALE

PROJECTS OVER A FIVE-YEAR PERIOD FOR THE PERIOD 2002-2013

Number of companies

-5

-4

-3

-2

-1

Employess 250+

The Danish Council for Strategic Research

Innovation Consortia

The Danish National Advanced Technology Foundation

Strategic Platforms for Innovation and Research (SPIR)

Note: The figure is based on unique participation in FP6, FP7 and other schemes, so the companies

can have participated more than once in the different schemes, but this only accounts for one – the

first participation.

Source: The Danish Agency for Science, Technology and Innovation (2015), the InnovationDenmark

Database.

5.5.

Conclusion

The results from this analysis show that the participating Danish companies in FP6

or FP7 are multiple users of the Danish national research and innovation system.

They also show that the participating companies in FP6 or FP7 make up a relatively

large share of the companies that take part in large-scale Danish programmes.

All these findings demonstrate that FP6 and FP7 is an integral part of the funding

landscape for Danish companies. Only 5 per cent of the companies in Innovation

Network Denmark, have participated in FP6 or FP7. This indicates that there is a

potential for an increased participation in EU framework programmes.

BOX 5.1 THE INNOVATIONDENMARK DATABASE

Danish Agency for Science, Technology and Innovation (DASTI) has an increasing focus on collecting

data from the different national research and innovation schemes. The data are harmonized in a joint

database called the InnovationDenmark database.

The InnovationDenmark database includes data from 16 national and international research and inno-

vation programmes, and includes approximately 12,800 projects and 11,700 Danish and international

participants. There are approximately 11,300 unique Danish companies in the database. The database

covers the period from 2002 to 2013.

As standard, the following harmonised data are collected for all research and innovation schemes in

DASTI:

•

Variables for each project: Name of programme, project title, grant status (rejection or approval),

application year, start date for the project, end date for the project, total budget and total grant

Variables for the participating partners in each project: Company registration number (CVR num-

ber), type of organisation, region, sector (NACE) and number of employees.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

6. Bibliometric perfor-

mance analysis of publi-

cations from Danish re-

searchers linked to FP6

and FP7

This chapter presents an analysis

of the impact of Danish scientific publications

that were the result of FP6 or FP7 funding. The purpose is to gain an insight into the

scientific impact researchers can achieve when participating in FP6 and FP7.

In order to look at impact we have identified citations belonging to scientific

publications with at least one Danish author. This is done using data from the in-

ternational citation database Web of Science (WoS). These results are compared to

the results of the bibliometric analyses from the previous evaluations of the Danish

National Research Foundation (DNRF) and the Danish Council for Independent Re-

search (DFF). Finally the analyses also explore the impact at the level of programme

themes under FP6 and FP7.

6.1.

Main findings

The present bibliometric analyses examine the performance of journal articles af-

filiated to scholars at Danish research institutions and linked to projects funded by

the European Framework Programmes FP6 and FP7. The data sets analysed include

2,020 unique publications linked to 171 FP6 projects in the period 2002 to 2013 and

3,583 unique publications linked to 461 FP7 projects in the period 2007 to 2013.

We examine the citation impact of these publications and we compare the impact

to other funding benchmark units. Benchmark units include validated publica-

tion sets linked to two main Danish funding institutions, i.e. the Danish National

Research Foundation (DNRF) and the Danish Council for Independent Research

(DFF). To align the FP6 and FP7 publication sets for comparison with the bench-

mark units, the time period for these comparisons is restricted to 2005-2011 (FP6)

and 2007-2011 (FP7). We analyse the publication sets at the aggregate level of FP

programmes and the disaggregate level of FP-specific “programme themes”. The

main findings and some caveats are presented below in this summary.

29 The study was produced by Jesper W. Schneider and Thomas Kjeldager Ryan, Danish Centre

for Studies in Research and Research Policy, Department of Political Science and Government,

Aarhus University, Denmark. Data was collected and provided by DASTI.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

Overall the aggregate publication sets linked to FP6 and FP7 examined in this

study perform respectively above and far above the international performance lev-

els, when it comes to citation impact. The impact levels are generally high, and the

impact levels for the FP7 set can be considered outstanding. The average article

citation score for the FP6 set is approximately 50 per cent above the international

level, whereas the score for the FP7 set is close to 75 per cent above the international

level. Likewise, the FP6 set has 1.75 times as many publications as expected among

the 10 per cent most cited in the database, whereas the FP7 set has twice as many as

expected.

Noticeable for both sets is the degree of internationalisation. Although we ex-

pected that a considerable number of the publications would be international col-

laborations, the observed proportion of approximately 70 per cent was higher than

expected. The general proportion of Danish publications with international collabo-

ration is around 55-60 per cent in the period examined.

Also characteristic for both sets are the publication profiles, when it comes to

output in the “multidisciplinary sciences” journal subject category. For both groups,

this is the single largest journal subject category when it comes to output, and it is

also the category with the highest citation impact. This is the category where broad

journals such as Science, Nature and PNAS (Proceedings of the National Academy

of Sciences) are categorised. The FP6 and FP7 sets vary to some degree when their

subject profiles are characterised according to the OECD’s main research fields (cf.

technical report). Not surprisingly, the natural science field is the largest in both

sets, but in the case of FP6 the field of engineering and technology performs at the

same level as the natural science field, whereas in the case of FP7 the natural science

field markedly outperforms all other fields.

A main finding of the present analyses is the outstanding performance level of

the FP7-linked publications. As a set it has a higher citation impact compared to all

the benchmark units. As in previous analyses of funding units

, we also see that, in

the present case, removing either the FP6 or the FP7 set causes a decrease in overall

Danish impact. The results are robust, yet the decrease is most marked for the FP7

set. Like the benchmarks sets, this analysis confirms that the FP6 and FP7 publica-

tion sets contain a relatively larger proportion of the most highly-cited articles in the

database compared to the overall distribution of Danish articles. As the distribution

of citations is highly skewed among articles, removing the funding sets stepwise

compared to random sets causes important drops in the overall national impact.

Interestingly, the two sets differ when it comes to the actual impact of the articles

with international collaboration. As expected, impact is generally high and consid-

erably higher than the impact of publications with no or merely national collabo-

ration. Nevertheless, the impact level for the FP6 set is below the levels for the two

funding units used as benchmarks, whereas the FP7 set outperforms them all.

Statistical modelling suggests that substantial parts of the impact received by

FP6 and FP7-linked publications are associated with the high level of international

collaboration. But again there are differences between the two sets. The expected

marginal impact for FP6-linked publications is on the same level as the DFF set, but

below the DNRF set when controlling for international collaboration. Without the

statistical control, the expected impact level for FP6-linked publications is on a level

http://ufm.dk/en/publications/2013/files-2013/appendiks-5_bibliometrisk_report_03122013.

pdf

http://ufm.dk/publikationer/2014/filer-2014/analyses-of-the-scholarly-and-scientific-output-

from-grants-funded-by-the-danish-council-for-independent-research-from-2005-to-2008.pdf

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

with or slightly below the benchmark sets. Consequently, international collabora-

tion, with its derived impact effects, to a large extent seems to statistically explain

the performance level of the FP6 set.

International collaboration is, however, not the only explanation for the outstand-

ing performance levels for the FP7 set. Controlling for international collaboration

reduces the expected marginal impact, nevertheless even after the statistical con-

trol the expected impact of FP7-linked publications is markedly higher than the

two benchmark sets. Consequently, the high impact of FP7 publications cannot be

explained as primarily an effect of international collaboration. Other factors are at

play.

Publications linked to ERC and Marie Curie grants are included in the FP7 set.

They constitute 27 per cent of the total FP7 set and 33 per cent of the restricted

set used for the benchmark analyses. Removing the ERC and Marie Curie-linked

publications causes a considerable drop in impact for the remaining FP7-linked

publications. Depending on whether we focus on indicators based on full or frac-

tional counts, the performance level for the remaining FP7 publications is on a level

with the DNRF with full counts, or below the DNRF but on par with the DFF set

using fractional counts. It is noticeable here that the more robust indicator for the

proportion of highly-cited articles suggests that the drop is most marked in the av-

erage-based indicators, as they are less robust in relation to the influence of outliers

on indicator values. Subsequent modelling confirms these findings, in as much as

controlling for ERC and Marie Curie grants seems to explain most of the gap to the

DNRF set, although the expected marginal impact is still slightly higher for the FP7

set, even after controlling for these specific grants.

Finally, the disaggregate analyses at the level of thematic areas reveal that no

single type of thematic area seems to dominate performance, as high impact levels

are spread among various different funding themes and types. It is interesting to ob-

serve that other “thematic areas” than ERC and Marie Curie grants both have large

volume and high impact in the FP7 set.

When interpreting the results presented in this report it should be kept in mind

that measuring the properties of science is a difficult exercise. Bibliometric data can

contribute important insights to this exercise, but cannot stand alone. Indicators

measuring citation impact capture the short-term reception of journal articles in

the scholarly communication system. But it is important to realize that there is no

one-to-one relationship between impact and research “quality”. Under reasonable

circumstances, impact on aggregate levels of analysis may be seen as a partial or

indirect measure of “quality”. As a consequence of the partial and one-dimensional

nature of the indicators, a single indicator is often not reliable.

However, when various complementary indicators suggest similar insights, more

convincing evidence about the property observed is offered. Furthermore, the indi-

cators have to be appropriate to the units under investigation. The limitations with

regard to this are well-known within the humanities and major parts of the social

sciences, but also apply to certain areas of the hard sciences. While the units ana-

lysed in this study have good coverage and can be seen as valid, they only include

journal articles indexed in the Web of Science. Finally, bibliometric indicators are

unreliable below certain levels of aggregation and need careful mathematical nor-

malization to be used across diverse research areas. However, these normalization

procedures are by no means perfect. The interpretation of the data in this report

should in other words be done with care; however, despite these limitations, biblio-

metric data do have a lot to offer when examining academic performance.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

One specific issue needs to be emphasised in relation to the presented analyses:

the potential risk of systematic selection bias in the examined data sets. The two-

step data collection process neither provides apparent populations nor generates

random samples. Although we seem to have included approximately half of the

originally targeted FP6 and FP7 projects, we definitely cannot rule out some selec-

tion bias. We cannot expect the missing projects and their affiliated publications

to be an exact mirror of those included, although it is also highly unlikely that a

large majority of the missing publications should be specifically located in the tails

of the distributions, potentially causing major changes to the calculated indicator

values.

In the technical report we try to examine to what extent the included data may

be biased. Would the citation distributions significantly change if the FP6 and FP7

publication sets were substantially enlarged? The general impression is that the con-

stitutions of the two sets are fairly robust given their actual size, and combined with

the experience we have with larger data sets such DFF and DNRF, we are inclined to

say that an enlargement will probably not change the distributions and thus impact

levels in any substantial way – yet we cannot rule it out. Consequently, the results

presented in this report should be interpreted carefully, as systematic bias cannot be

excluded. However, we have good indications that the results are indeed robust and

to a large extent reliable.

The subsequent section presents the main results in tables and figures, and the fi-

nal section gives an overview of the methods and indicators used. The methods and

results presented here are documented and scrutinised more comprehensively in

the supplementary technical report.

6.2.

Results

6.2.1. Publication performance FP6 and FP7

Table 6.1 presents the overall performance statistics for the publication sets linked

to the FP6 and FP7 programmes. Even though the time period is longer for the FP6

programme, the analysed FP6 publication sets are considerably smaller compared

to the FP7 set. The FP6 and FP7 publication sets have coverages in the database of

slightly above 80 per cent, which conventionally is interpreted as “excellent” for the

purpose of citation analyses.

When looking at impact we use two main indicators: an average article citation

score (MNCS - mean normalised citation score) and a score for the share of highly-

cited publications (PPtop10 per cent). The average article citation score (MNCS) is

based on the actual number of citations publications have received. A value above

1 indicates that the mean impact for the unit of analysis is above world average,

whereas a value below 1 indicates the opposite. The indicator for the share of high-

ly-cited publications (PPtop10 per cent) shows the proportion of publications be-

longing to the top 10 per cent most frequently cited publications in a field. A share

of 20 per cent means that 20 per cent of the unit of analysis is among the 10 per

cent most frequently cited. The level for Danish scientific publications is normally

around 12 per cent.

When it comes to citation impact, the FP6 and FP7 publication sets differ con-

siderably. With full count average article citation score values of 2.03 and share of

highly-cited publication values of 22.2 per cent, the FP7 set has an outstanding per-

formance level. The performance level of the FP6 publication sets is also noticeably

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above the international standard, but also distinctly below the impact level of FP7

set. Looking at the indicators based on fractional counts and comparing them, the

average article citation score for the FP6 set is approximately 50 per cent above the

international level, whereas the score for the FP7 set is close to 75 per cent above

the international level. Likewise, the FP6 set has 1.75 times as many publications as

expected among the 10 per cent most cited in the database, whereas the FP7 set has

twice as many as expected.

All analyses have been done with both full and fractional counting – as shown in

table 6.1: No. of fractional publications, Average article citation score and Share of

highly-cited publications. With full counting, a unit of analysis is given full credit

for a publication regardless of the number of authors, institutions or countries

mentioned in the address field of the publication. With fractional counting a unit is

credited a fraction of each publication - in the present case in proportion to its share

of all countries mentioned in the address field in a publication. Consequently, we

fractionalise at the country level because a principal interest in the analyses is the

units’ degree of internationalisation.

The indicator for average journal citation score (MNJS) reflects the journal pub-

lication profile of the unit under investigation. It measures the average citation im-

pact of the journals in which a set of publications has appeared, where the citation

impact has been normalized for the fields to which the journals belong. Above one

means that on average the journals have been cited more frequently than would

be expected based on their fields. The stable indicators of 1.47 for FP6 and 1.55 for

FP7 can be considered high. In other words, the FP6 and FP7 publications are on

average published in journals with a high impact in their respective fields. On an ag-

gregate level, one can expect that publications in higher impact journals will result

in higher overall citation impact scores (although this reasoning does not hold for

individual articles).

TABLE 6.1

OVERALL PERFORMANCE STATISTICS FOR PUBLICATION SETS LINKED TO FP6 AND FP7

PROGRAMMES

FP6

(2002-2013)

No. of publications

No. of fractional publications

Database coverage

Share of international collaboration

Average article citation score (MNCS )

Average article citation score - fractional (MNCS

frac

)

Share of highly-cited publications (PPtop10 per cent)

Share of highly-cited publications - fractional (PPtop10 per cent

frac

)

Average journal citation score (MNJS)

2,020.0

1,083.5

82 %

71 %

1.79

1.52

19.6 %

17.2 %

1.47

FP7

(2007-2013)

3,583.0

1,958.9

85 %

69 %

2.03

1.74

22.2 %

19.8 %

1.55

Interestingly, the journal publication profiles are similar for the two sets when it

comes to output in the “multidisciplinary sciences” journal subject category in Web

of Science. For both sets, this is the single largest journal subject category when it

comes to output, and it is also the category with highest mean normalized citation

impact. This is the category where broad journals such as Science, Nature and PNAS

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

are categorised (journal and OECD subject profiles for the FP6 and FP7 sets can be

found in the technical report).

Besides the outstanding performance level for FP7 publications, the most inter-

esting finding from this overall performance analysis is the very high proportion of

articles with international collaboration both in the FP6 and FP7 sets. Obviously,

we would expect that a majority of the articles would be a result of international

collaboration, given the nature of the EU funding programmes and combined with

the general trend of larger shares of annual publication volumes with international

collaboration (e.g., for Denmark this share has been between 55 and 60 per cent in

the last decade). Nevertheless, 71 per cent for FP6 and 69 per cent for FP7 is more

than expected, and knowing that international co-authored articles on average have

higher citation rates compared to articles with no or merely national collaboration,

this fact no doubt influences the overall impact of the two publication sets.

Table 6.2 shows performance statistics for articles from the two publication sets

with no collaboration, national or international collaboration. If we compare the

performance of the articles with no extra-institutional collaboration with the per-

formance of articles with national institutional performance, we see that for both

the FP6 and FP7 sets the performance for both the journal publication indicator

(MNJS) and the article impact (MNCS) is considerably higher for articles with no

collaboration.

TABLE 6.2

PERFORMANCE STATISTICS FOR ARTICLES WITH NO (NO COLLAB.), NATIONAL

(NAT. COLLAB.) OR INTERNATIONAL COLLABORATION (INT. COLLAB.) IN THE PUBLICA-

TION SETS LINKED TO FP6 AND FP7

FP6

(2002-2013)

Publication sets

No. publications

No. of fractional publications

Average article citation score (MNCS )

Average article citation score -

fractional (MNCS

frac

)

collab.

348

1.49

Nat.

collab.

213

1.32

Inter.

collab.

1441

503.5

1.93

collab.

689

1.64

FP7

(2007-2013)

Nat.

collab.

420

1.47

Inter.

collab.

2474

850.5

2.22

1.49

17.6 %

1.32

14.3 %

1.63

20.9 %

1.64

19.1 %

1.47

18.4 %

1.95

23.7 %

Share of highly-cited publications

(PPtop10 per cent)

Share of highly-cited publications -

fractional (PPtop10 per cent

frac

)

17.6 %

1.37

14.3 %

1.28

18.2 %

1.53

19.1 %

1.34

18.4 %

1.31

21.3 %

1.66

Average journal citation score (MNJS)

If we then compare the performance of the two previous collaboration types with

international collaboration, we clearly see that the previous two sets were relatively

smaller in size, and that the performance of internationally co-authored articles on

average is markedly higher compared to articles with no or national collaboration.

Nevertheless, the patterns between the three collaboration types deviate from the

overall characteristics for Danish publications in as much as articles with no col-

laboration have a higher impact compared to articles with national collaboration.

What is noticeable is that articles with international collaboration are generally

published in journals with higher international impact (MNJS) and have themselves

on average a much higher impact compared to the other two categories. But it is

also remarkable that the performance for the FP7 set is higher in all three categories

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compared to the FP6 set and considerably higher when it comes to articles with in-

ternational collaboration.

6.2.2. Benchmark analyses

We present the main performance statistics for the benchmark comparisons in

tables 6.3 (FP6) and 6.4 (FP7) below; for more detailed analyses we refer to the

technical report. Two overall benchmark approaches have been used. One where we

examine what happens to the overall national impact for Denmark, when the FP6

and FP7 publication sets are removed from the total Danish set of publications (sim-

ilar consequences when removing the DFF and DNRF sets in combination with the

FP6 and FP7 sets are documented in the technical report). The second benchmark

approach simply compares the performance between the two benchmark funding

sets and the FP6 and FP7 sets for the publication periods 2005-2011 and 2007-2011

respectively.

Overall, removing the FP6 or FP7 sets causes a drop in national Danish impact.

The effect of removing the FP6 set is smaller than removing the FP7 set. This is a

consequence of the smaller volume of the FP6 publication set but also the lower

impact levels compared to the FP7 set. Notice that successively removing the FP

sets together with DFF and then DNRF results in a continuous decrease of overall

Danish impact, from 1.46 to 1.40 (Average article citation score) in the FP6 case

and from 1.48 to 1.40 (Average article citation score) for the FP7 case (cf. technical

report).

The general drop is more marked when removing the FP7 set. In previous anal-

yses of DNRF and DFF we discussed how to interpret the seemingly small changes

in impact. Significance tests are irrelevant here

, yet resampling techniques, where

random sets of articles of similar size to the funding units are removed from the

overall Danish sets, reveal that the changes caused by the funding sets are indeed

substantial. Nothing happens to the Danish impact when we resample, but remov-

ing publications linked to the specific funding units decreases overall Danish im-

pact. This is so because the funding sets have a substantially higher proportion of

highly-cited articles.

Comparing the overall performance for the FP6 publication set to the benchmark

units (table 6.3), we see that the impact levels are comparable to the DFF set, but

below the DNRF set. Notice that when we compare the units according to fractional

counted average article citation score, the impact score for FP6 drops below the

DFF. This is most probably an effect of the larger proportion of publications with

international collaboration in the FP6 set in combination with the lower level of

intrinsic robustness of the average article citation score indicator (we will examine

this below). In all instances, the FP6 set is considerably smaller compared to the

benchmarks. Notice that approximately 10 per cent of the FP6-linked publications

are also linked to either a DFF grant or a CoE funded by the DNRF.

31 Cf. previously mentioned DNRF and DFF reports, and Schneider, J.W. (2013). Caveats for using

statistical significance tests in research assessments. Journal of Informetrics, 7(1), 50- 62.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

TABLE 6.3

COMPARISON OF PERFORMANCE BETWEEN FP6 PUBLICATION SET (2005-2011) AND

BENCHMARK UNITS, THE DNRF AND DFF FUNDING SETS, AND THE OVERALL DANISH

SET OF PUBLICATIONS

Average

article

citation

score

(MNCS )

1.46

1.45

1.82

1.81

1.88

Share of

highly-

cited

publi-

cations

(PPtop10

per cent)

15.5 %

20.0 %

19.3 %

21.7 %

Average

journal

citation

score

(MNJS)

1.24

1.46

1.49

1.57

No. of

fraction-

alized

publica-

tions

51,538.9

50,860.5

695.0

4,182.6

4,458.0

Average

article

citation

score -

fractional

(MNCS

frac

)

1.28

1.57

1.62

1.72

Share of

highly-

cited pub-

lications -

fractional

(PPtop10

per cent

frac

)

13.5 %

13.4 %

18.1 %

17.9 %

19.6 %

No. of

publica-

tions

Denmark (DK)

DK excl FP6

Total FP6 set of

pubs

Total DFF set of

pubs

Total DNRF set

of pubs

78,173

76,930

1,267

6,272

7,164

The differences in impact levels between FP7 and the benchmarking units are no-

ticeable. The difference between the DFF and DNRF is well-known and was docu-

mented in previous reports. While the time period is slightly different in the pres-

ent analysis, the impact scores are similar to the ones in the previous reports. Notice

that previously the DFF and DNRF publication sets have been considered to have

high performance levels; the DNRF in particular has been characterized as having a

very high performance when it comes to the proportion of highly-cited articles. Re-

markably, the performance of the FP7 set in the present analysis is above that of the

DNRF, and the level can therefore be considered to be outstanding.

TABLE 6.4

COMPARISON OF PERFORMANCE BETWEEN FP7 PUBLICATION SET (2007-2011) AND

BENCHMARK UNITS, THE DNRF AND DFF FUNDING SETS, AND THE OVERALL DANISH

SET OF PUBLICATIONS

Average

article

citation

score

(MNCS )

1.48

1.46

2.11

1.82

1.89

Share of

highly-

cited

publi-

cations

(PPtop10

per cent)

15.8 %

15.6 %

23.0 %

19.3 %

22.2 %

Average

journal

citation

score

(MNJS)

1.26

1.25

1.57

1.5

1.58

No. of

fraction-

alized

publica-

tions

38,490.8

37,515.7

1,068.1

3,895.0

3,421.0

Average

article

citation

score -

fractional

(MNCS

frac

)

1.29

1.28

1.81

1.63

1.72

Share of

highly-

cited pub-

lications

- fractional

(PPtop10

per cent

frac

)

13.6 %

13.4 %

21.7 %

18.0 %

19.9 %

No. of

publica-

tions

Denmark (DK)

DK excl FP7

Total FP7 set of

pubs

Total DFF set of

pubs

Total DNRF set

of pubs

59,130

57,355

1,908

5,841

5,638

The share of highly-cited publications is also markedly higher. The marked differ-

ences are also visible with fractional counts, but here the degree of internationaliza-

tion must also be taken into consideration. This influences the scores – not only the

fractioning of scores but also in relation to the fact that international co-authored

articles on average have higher citation density rates. The similar journal publica-

tion profiles for the FP7 and DNRF sets are also noteworthy. The average journal

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

citation score (MNJS) confirms that average publication behaviour is directed

towards journals with the highest impact in their respective fields; largest among

them is the “multidisciplinary sciences”. The volume of the FP7 set is larger than

FP6, but at the same time also considerably lower compared to the benchmarks.

Note that approximately 11 per cent of the FP7-linked publications are also linked to

either a DFF grant or a CoE funded by the DNRF.

As already documented, around 70 per cent of publications in the FP6 and FP7

sets are a result of international collaboration. In table 6.5 we compare the degree of

internationalisation between the FP6 and FP7 publication sets and the benchmark

units.

We also outline the performance for the internationally co-authored articles in

these sets. The FP6 set has a markedly higher share of internationally co-authored

articles, and the DNRF set has the second highest share, albeit more than nine per-

centage points less than the FP6 set. Interestingly, even though the DFF and DNRF

sets have considerably lower shares of articles with international collaboration, their

impact levels for this group of articles are markedly higher than the FP6 set. On

the other hand, the FP7 set has a slightly lower proportion of internationally co-au-

thored articles compared to the FP6 set, but still a larger proportion compared to

the benchmark units; yet the impact for this set is remarkable.

TABLE 6.5

COMPARISON OF PERFORMANCE OF INTERNATIONAL CO-AUTHORED ARTICLES

BETWEEN THE FP6 AND FP7 PUBLICATION SETS AND THE TWO FUNDING BENCHMARK

UNITS (DNRF AND DFF)

(2005-2011)

FP6

Share of international collaboration

Average article citation score (MNCS)

Share of highly-cited publications

(PPtop10 per cent)

Average journal citation score

(MNJS)

Average article citation score -

fractional (MNCS

frac

)

Share of highly-cited publications -

fractional (PPtop10 per cent

frac

)

70.9 %

1.98

21.0 %

1.49

1.71

18.7 %

DFF

56.5 %

2.07

20.9 %

1.62

1.88

19.5 %

DNRF

61.4 %

2.05

24.2 %

1.69

1.92

22.5 %

FP7

67.7 %

2.32

23.8 %

1.67

2.01

21.9 %

(2007-2011)

DFF

56.5 %

2.08

20.9 %

1.63

1.89

19.5 %

DNRF

63.2 %

2.07

24.5 %

1.69

1.93

22.8 %

In order to explore the relationship between citation impact and the degree of in-

ternationalisation further, we examined this in relation to the different funding

sets in a number of models controlling for well-known factors influencing citation

impact (details on model specification and results can be found in the technical re-

port). Predictably, the regressions generally showed that the expected impact for the

FP sets is higher than or comparable to the benchmarks, but when we control for

international collaboration the expected impact between the FP sets and the bench-

mark units diminishes. There are, however, differences between FP6 and FP7. The

expected citation impact for the FP6 set after controlling for international collabora-

tion is lower than the DNRF set and equal to the DFF set. However, after controlling

for international collaboration, and thus the citation benefits this may give, the

expected citation impact for the FP7 set is still higher than the two benchmark sets.

Consequently, international collaboration with its derived impact effects seems to a

large extent to statistically explain the performance level of the FP6 set compared to

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the benchmarks, although this is not the only factor that may explain the outstand-

ing performance levels for the FP7 set.

The FP7 set includes ERC and Marie Curie grants. These grants are different

from the more strategic or topic-specific FP7 thematic areas (see next section). To-

gether, the publications linked to ERC or Marie Curie grants constitute 27 per cent

of all FP7-linked publications, and 33 per cent of the restricted FP7 set used for the

benchmark analyses. Table 6.6 shows what happens to the impact scores when we

remove these grants from the restricted FP7 set.

TABLE 6.6

CONSEQUENCES OF REMOVING ERC AND MARIE CURIE GRANTS FROM THE RESTRICTED

FP7 SET OF PUBLICATIONS USED FOR THE BENCHMARK ANALYSES (2007 - 2011)

FP7

Share of international collaboration

Average article citation score (MNCS )

Share of highly-cited publications

(PPtop10 per cent)

Average journal citation score (MNJS)

Average article citation score - fractional

(MNCS

frac

)

Share of highly-cited publications - fractional

(PPtop10 per cent

frac

)

67.7 %

2.11

23.0 %

1.57

1.81

21.7 %

FP7 without

ERC & Ma-

rie Curie

68.0 %

1.91

21.1 %

1.49

1.61

19.7 %

DFF

56.5 %

1.82

19.3 %

1.5

1.63

18.0 %

DNRF

63.2 %

1.89

22.2 %

1.58

1.72

19.9 %

It is clear that the degree of internationalisation is not affected, but both full and

fractional count average article citation score and the share of highly-cited publica-

tions scores drop markedly, and so does the average journal citation score. The lat-

ter suggests that the publication profile for these specific grants is perhaps the most

important factor influencing citation impact on the aggregate level of publication

sets in journals with very high international visibility.

Depending on whether we focus on indicators based on full or fractional counts,

the performance level for the remaining FP7 publications is on a level with the

DNRF with full counts for the average article citation score, but slightly below in the

share of highly-cited publications. With fractional counts the average article citation

score is considerably below the DNRF level but similar to DFF. Here it is noticeable

that the more robust indicator for the proportion of highly-cited articles (Pptop10

per centfrac) suggests that the drop is most marked in the average-based indicators

(average article citation score), as they are less robust in relation to the influence

of outliers on indicator values. Consequently, the average-based indicators in the

FP7 set are more “vulnerable”, because the subset of ERC and Marie Curie-linked

publications include some very highly-cited outliers. Note that there is no overrep-

resentation of ERC or Marie Curie-linked publications that also have links to either

the DFF or DNRF sets. For ERC there is a 9 per cent overlap with DFF and 11 per

cent with DNRF; for Marie Curie, there is again a 9 per cent overlap with DFF but

only 8 per cent with DNRF.

A further regression seems to confirm this general finding: that ERC and Marie

Curie-linked publications to a large extent can explain the remaining gap between

FP7 and the DNRF when we control for international collaboration. However, for

full counts, the expected marginal impact is still slightly higher for the FP7 set, even

after controlling for ERC and Marie Curie grants. In other words, even after con-

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trolling for international collaboration and specific funding schemes, the FP7 set

still performs on a level with the DNRF set.

6.2.3. Bibliometric analysis of publication sets linked to programme

themes under FP6 and FP7 programmes

As a final performance analysis we disaggregate the FP6 and FP7 publication sets

to the level of thematic areas. Below in figures 6.1 and 6.2 we present the results for

full count average article citation score scores plotted as a function of output for the

individual thematic areas.

FIGURE 6.1

AVERAGE ARTICLE CITATION SCORES (MNCS) AS A FUNCTION OF PUBLICATION OUTPUT

(FULL COUNTS) FOR FP6 THEMATIC AREAS

3.5

2.5

4. aero & space

1. life sci

9. hum res & mobil

6. sustain develop

12. sci & society

2. inf soc technol

11. res infrastructure

MNCS

1.5

8. horizon res activity

14. support coord

activity

7. citizen & govern

3. nano

13. support int coop

5. food

10. policy support

0.5

Publications (log-scale)

100

1000

FP6 thematic areas: 1. Life sciences, genomics and biotechnology for health; 2. Information society

technologies; 3. Nanotechnologies and nanosciences, knowledge-based multifunctional materials

and new production processes and devices; 4. Aeronautics and space; 5. Food quality and safety;

6. Sustainable development, global change and ecosystems; 7. Citizens and governance in a know-

ledge-based society; 8. Horizontal research activities involving SMEs; 9. Human resources and

mobility; 10. Policy support and anticipating scientific and technological needs; 11. Research infra-

structures; 12. Science and society; 13. Specific measures in support of international cooperation;

14. Support for the coordination of activities.

By plotting impact to output it becomes easier to interpret the importance and

robustness of the individual indicators. We have plotted a grid line corresponding

to 50 full count publications on a log-scaled x-axis (output); this rather arbitrary

threshold can be used as a guideline when interpreting the results. Results on or

just below the threshold should be treated carefully and results far below should be

discarded.

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FIGURE 6.2

AVERAGE ARTICLE CITATION SCORES (MNCS) AS A FUNCTION OF PUBLICATION OUTPUT

FOR FP7 THEMATIC AREAS

4.5

3.5

8. GALILEO

17. OCEAN

4. ERC-AG

5. ERC-COG

MNCS

2.5

23. SSH

9. HEALTH

15. Marie-Curie

12. INFRA

3. ENV

14. KBBE

7. ERC-SG 16. NMP

1.5

6. ERC-OA

19. SIS

20. SME

11. INCO 26. TPT-TPT

1. AAT

2. ENERGY

13. JTI

22- SPA

10. ICT

24. SST

25.SST-OCEAN

18. SEC

0.5

21.SPS

Publications (log-scale)

100

1000

FP7 thematic areas: 1. Aeronautics and air transport; 2. Energy; 3. Environment (including Cli-

mate Change); 4. ERC-Advanced Grants; 5. ERC-Consolidated grants; 6. ERC-Other activities; 7.

ERC-Starting Grants; 8. ERC-Support to the European global satellite navigation system (Galileo)

and EGNOS; 9. Health; 10. Information and Communication Technologies; 11. Activities of In-

ternational Cooperation; 12. Research Infrastructures; 13. Joint Technology Initiative; 14. Food,

Agriculture and Fisheries, and Biotechnology; 15. Marie-Curie Actions; 16. Nanosciences, Nanotech-

nologies, Materials and new Production Technologies - NMP; 17. OCEAN.2010/2011; 18. Security;

19. Science in Society; 20. Research for the benefit of SMEs; 21. EURATOM; 22. Space; 23. So-

cio-economic sciences and Humanities; 24. Sustainable surface transport (including the ‘European

Green Cars Initiative’); 25. The Ocean of Tomorrow (OCEAN) 2010/2011; 26. Horizontal activities

for implementation of the transport programme.

From figure 6.1 (FP6) we can see that eight thematic areas have publication outputs

above 50, and all eight also have impact scores on or above 1.20. One theme, “Life

sciences, genomics and biotechnology for health (1.)”, has an impressive impact

score of 2.30 and at the same time this thematic area is the largest among the 14 ex-

amined in this analysis when it comes to publication output.

In figure 6.2 (FP7), 14 thematic areas have outputs from approximately 50 up to

760 full count publications. Thirteen of these areas have indicator values of above

1.20 and 6 with average article citation scores of above 2. The two highest perform-

ing themes among those with robust publication outputs are The Ocean of Tomor-

row (17.) and ERC-Advanced Grants (4.) with impressive average article citation

score scores of 3.02. It is noticeable that there seemingly is a broad variation among

the 14 thematic areas, when it comes to project types among the 14 most robust

thematic areas. There is a mixture of ERC grants, Marie Curie grants, infrastructure

and thematic areas, all with high performance - no single type seemingly stands out.

This supports the previous findings, where we removed ERC and Marie Curie grants

– the overall performance of the FP7 set is robust and varied among the different

thematic areas.

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In the technical report supplementary figures are presented for the share of high-

ly-cited publications indicator as a function of output. Two overall tables present the

main performance statistics for the FP6 and FP7 thematic areas, as well as demon-

strations of the validity when it comes to coverage and publication volume using this

disaggregate unit of analysis compared to usage of individual projects.

6.3.

Methods

The bibliographic data used in the analyses are validated journal articles (research

articles and review articles) indexed in the international citation database Web of

Science (WoS). We use the in-house value-added version of WoS at CWTS, Leiden

University, Netherlands. A thorough validation process has been set up and man-

aged by the Danish Agency for Science, Technology and Innovation (DASTI) at the

Ministry of Higher Education and Science, where individual scholars at Danish

research institutions with funded projects under the FP6 or FP7 programmes were

contacted and asked to validate pre-selected publication lists, as to whether the

specific articles could be linked to the EU funding grant. Since mid-2008 potential

funding acknowledgements mentioned in journal articles have been made available

for analyses in the WoS. In order to try to enlarge the validated data set of publica-

tions, we utilized the WoS funding acknowledgement data and manually analysed

the pre-selected publication lists for all non-validated projects, in order to check

whether potential FP6 and FP7 grants were acknowledged. If so, these publications

and projects were also included in the analyses, thereby extending the data set.

Eventually 175 FP6 and 503 FP7 projects and their linked publications were in-

cluded in the analyses; we refer to the technical report for more details on inclusion

and exclusion of projects and publications.

The analyses are based on several different units of analysis. Bibliometric data

are characterised by skewed distributions, and robust statistics require considerable

sample sizes. A common, although arbitrary, threshold is often a minimum of 50

full count publications, but larger samples are preferable. A further consideration

with bibliometric data, especially from citation databases, is the well-known cover-

age problems. The enhanced citation database we use in the analysis only indexes

journal articles, and mainly English language journals. Hence, research areas where

international journals are not the primary medium for reporting research results

will have lower coverage in the database, and citation analyses in such areas become

problematic.

To obtain a proxy for coverage we have examined the reference behaviour in the

aggregate units of analysis, in the sense that we calculate the proportion of refer-

ences given to other journal articles indexed in WoS. This number indicates to what

extent the unit is dependent on international journals in the scientific communica-

tion process, and eventually the validity of doing citation analysis on such a set of

articles. In the technical report we analyse the coverage for the aggregate and disag-

gregate units of analysis and find that coverage is satisfactory for the aggregate FP6

and FP7 publication sets and the disaggregate sets of thematic areas.

In scientometric analyses it is desirable to compare like with like, such as a re-

search institution with other research institutions, or countries with countries. It

is also preferable to compare units of roughly similar size, as it is generally so that

with larger units indicator values will tend to move closer towards the reference

value as mentioned in the introduction. The units of analysis in this report are Eu-

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ropean funding programmes, and we credit publications which are supposedly the

direct or indirect result of a project funded by one of these programmes. Obviously,

publications as discrete units primarily “belong” to authors and institutions, where

funders, and there are often several of them, are given an acknowledgement, but

otherwise not credited. Nevertheless, we use the funding institution as the unit of

analysis and link publications to it. An ideal benchmark unit would obviously be a

very similar funding institution. From previous bibliometric analyses of two main

Danish funding institutions, Centres of Excellence (CoE) funded by the Danish Na-

tional Research Foundation (DNRF), and various smaller grant types (compared

to DNRF) funded by the Danish Council for Independent Research (DFF), we have

validated publication sets linked to these instruments for roughly the same period

as the present analysis of FP6 and FP7. We utilize these publication sets as bench-

marks in this analysis because they to some extent can be considered “similar” units

of analysis (i.e. publications linked to funding programmes). Such a comparison is

however not without problems. The different funding units clearly have different

aims and purposes, and are different when it comes to the size of grants. Further,

publications may well be linked to several funding institutions and grants, making it

very difficult to claim any direct link between funding and performance.

The FP6 programme ran from 2002 to 2006, and the FP7 programme from 2007

to 2013. We have chosen the following time period for the two programmes: FP6,

all validated articles published from 2002 to 2013, and FP7, all validated articles

published from 2007 to 2013. We use a citation window of three years including the

publication year. This means that articles published after 2011 have shorter win-

dows. In the technical report we analyse the robustness of the overall results when

removing publications with shorter citation windows, and the findings are generally

robust (e.g., excluding the 2013 publications does not change the overall results).

Note that the same citation windows are applied to the different benchmark units,

yet as the DNRF and DFF sets of publications only have a common coverage be-

tween 2005 and 2011, the benchmark analyses are carried out with the following

time period: FP6 from 2005 to 2011, and FP7 from 2007 to 2011.

Table 6.7 below presents the standard indicators we use in the analyses. The indi-

cators are defined and constructed by CWTS and tailored to their in-house version

of the WoS database. These are the same indicators used in their Leiden Ranking.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

TABLE 6.7

OVERVIEW OF STANDARD CWTS BIBLIOMETRIC INDICATORS USED IN THE PRESENT

ANALYSES

Dimension

No. of publications

No. of fractional

publications

Coverage

Output

(participation)

Output

(contribution)

Validity

Definition

Total number of publications of a unit.

Fractionalised publications of a unit; in the present analy-

sis we fractionalise according to country

Internal coverage. Proxy of oeuvre being covered by WoS.

Measured by the proportion of cited references in the

oeuvre linking to other WoS publications.

Mean normalised number of citations of the publications

of a unit (self-citations not included).

Mean normalised number of citations of the publications

of a unit (self-citations not included) based on fractional

publication counting at the country level.

Mean normalized citation score of the set of journals in

which a unit has published.

Proportion of articles that belong to the top 10 per cent

highest-cited publications in the database.

Proportion of articles that belong to the top 10 per cent

highest-cited publications in the database based on frac-

tional publication counting on the country level.

Average article citation

score (MNCS )

Average article citation

score - fractional

(MNCS

frac

)

Average journal citation

score (MNJS)

Share of highly-cited

publications

(PPtop10 per cent)

Share of highly-cited

publications - fractional

(PPtop10 per cent

frac

)

Impact

Journal impact

Impact

There is an ongoing debate in the scientometric research community of whether to

use full counting or fractional counting, or both counting methods. There are valid

arguments for both positions. The fractional counting method is usually promoted

because it has good mathematical properties. Field-normalized comparisons across

units sum up to unity in the database and provide an interpretable scale where

1 corresponds to the average citation impact in the database. Full counting may

“favour” minor units with more international publication activity. Due to multiple

counts, full counting does not have the same mathematical property as fractional

counting, and consequently not quite the same interpretability in relation to a com-

mon reference value in the database. Such a rate is higher, and indicator values in

general are also higher with full counting (i.e., the “database average” is somewhat

higher than 1, probably 0.2-0.3 points). Despite violating mathematical properties,

full counting can certainly be relevant for specific analyses. Indeed, full and frac-

tional counts can be seen as measuring different constructs, i.e. participation (full)

and contribution (fractional). We provide results using both counting methods be-

cause we see these indicators as complementary rather than competing.

It is also important to emphasize that the meaning of an indicator’s numerical

value is strongly related to the aggregation level of the unit under study. At higher

aggregation levels, where publication volumes are generally larger, it becomes more

difficult to have relative impact scores substantially above the database average or

the expected proportion of articles among the 10 per cent most cited in the data-

base. This “regression-towards-the-mean

” phenomenon is mainly an effect of the

underlying skewed citation distributions. At the meso-level (e.g., units with 500-

1000 full count publications per year), an average article citation score value of be-

tween 0.8 and 1.2 is generally interpreted as a performance level comparable to the

average in the database (i.e., “world average” citation score), whereas values above

Regression-towards-the-mean: A statistical phenomenon. If a variable is extreme on its first

measurement, it will tend to be closer to the average on its second measurement.

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1.2 mean that the unit’s impact as a whole is above the international level, and val-

ues of 2 and more are far above the international level of the fields where a unit has

published in the examined period. The same yardstick can be roughly used for share

of highly-cited publications (full counts), where values above 12 per cent would be

considered above the expected, and values above 20 per cent far above the expected

for full counts.

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7. The individuals partici-

pating in FP6 and FP7

This chapter presents the characteristics of individuals from Danish institutions and

companies participating in projects funded by FP6 or FP7. The purpose of the chap-

ter is to provide a more detailed insight into who the individuals are, compared to

the general research community.

Detailed employer-employee-linked data spanning from 2000 to 2012 are used

to describe individuals participating in FP6 and FP7. The participants are compared

with the general level of individuals working with research and development (R&D)

in 2012. Comparable individuals are selected from the public registers after the

same criteria as the participants, such as education and occupation. Participants are

categorised as researchers, PhD students or masters.

7.1.

Main findings

Participation in FP6 or FP7 has given Danish institutions the possibility of employ-

ing part of the pool of international talent. A larger share of the individuals partici-

pating in FP6 or FP7 at Danish institutions and companies are foreigners, compared

to the general level. The PhD students are the participant group with the largest

share of foreigners, also compared to PhD students in general. 11 and 42 per cent

respectively of the participating researchers and PhD students in highly-skilled po-

sitions are foreigners.

Individuals participating in FP6 or FP7 are most often men. Participating re-

searchers, masters and PhD students all have a higher proportion of men than

in general. For example, 62 per cent of the participating PhD students are men,

compared to 50 per cent of PhD students in general. The higher proportion of male

participation in FP6 and FP7 is probably related to the fact that natural science and

technical science are overrepresented in FP6 and FP7.

The chapter proceeds as follows: section 7.2 presents the characteristics of the

participating researchers, masters and PhD students in FP6 and FP7. Section 7.3 de-

scribes the method. Annex 2 describes the participants not categorised as research-

ers, masters and PhD students.

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7.2.

Characteristics of the individuals participating in FP6 and FP7

This section describes the characteristics of the individuals participating in FP6 and

FP7 (called participants in the following text) in the year of project start in the pe-

riod 2003 to 2012.

The participants are divided into four groups:

• Researchers: Participants with a PhD degree at the beginning of the project

• PhD students: Participants that are PhD students at the beginning or during the

project

• Masters: Participants that have a master’s degree but are not PhD students

• Others: Participants without a master’s or a PhD degree

There are approximately 2,000 participants for whom relevant data is available in

the selected registers (see table 7.1). One fifth of the participants are PhD students

during the project. The biggest group of participants are researchers, corresponding

to 29 per cent, while 26 per cent of the participants are defined as masters and oth-

ers.

TABLE 7.1

PARTICPATING INDIVIDUALS COVERED BY THIS ANALYSIS, 2003-2012

Number

Researchers

Masters

Others

PhD students

Total

575

525

520

389

2,009

29 %

26 %

19 %

100 %

Note: FP6 covers the period 2002-2006 and FP7 covers the period 2007-2014.

Source: DASTI’s own calculation.

The participating researchers, PhD students and masters are each compared with

the general level for comparable individuals working with R&D in 2012. Compara-

ble individuals are aggregated into three groups: 1) Researchers, 2) Masters and 3)

PhD students – using the same criteria as the participants, such as education and

occupation (see section 7.3 for further information). The participant group “others”

is described separately in Annex 2.

7.2.1. Gender balance

Participating researchers, masters and PhD students all have a higher proportion of

men than the general population working with R&D (see figure 7.1). The difference

is most striking between masters and masters in general. Approximately 77 per cent

of the participating masters are men, compared to 53 per cent for masters in gen-

eral. The participating PhD students have the most equal gender distribution, where

62 per cent of participating PhD students are men compared to 50 per cent for PhD

33 Year 2012 is the last year for which all relevant public register data are available, meaning that

there is no information on participants with project start in 2013 and 2014.

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students in general.

The higher proportion of men in FP6 and FP7 is related to the

fact that natural science and technical science are overrepresented in FP6 and FP7

(see section 7.2.3).

FIGURE 7.1

GENDER DISTRIBUTION COMPARED TO THE GENERAL POPULATION OF INDIVIDUALS

WORKING WITH R&D

Pct.

100

Researchers

in general

PhD students

in general

Masters

in general

Male

Female

Source: DASTI’s own calculation using registry data from Statistics Denmark.

7.2.2. Age

The age distribution for the participating researchers and researchers in general is

almost identical, whereas the participating masters tend to be older than the mas-

ters in general, since 40 per cent of the participating masters are more than 50 years

old, while this is the case for 27 per cent of the participating masters in general.

The participating masters differ from participating researchers in their age distri-

bution, as only 22 per cent of participating researchers are more than 50 years old

(see table 7.2).

The PhD students participating in FP6 and FP7 are younger than the PhD stu-

dents in general when starting their PhD. 64 per cent of the participating PhD stu-

dents are under 30 years old when starting their PhD education, compared to 54 per

cent for PhD students in general. This is most likely due to a higher proportion of

foreign PhD students in FP6 and FP7 projects (see section 7.2.4) than for the PhD

students in general. Danish students are generally older than foreign students.

34 In the European Commission’s FP6 gender equality report similar results were reached:

”The percentage of female coordinators in FP projects (16 – 17 per cent) is distinctly lower

than the overall percentage of female researchers recorded in Europe in 2003 (29 per cent).

http://ec.europa.eu/research/evaluations/pdf/archive/fp6-evidence-base/evaluation_stud-

ies_and_reports/evaluation_studies_and_reports_2008/fp6_gender_equality_report.

pdf#view=fit&pagemode=none

(p. 15) Similarly for FP7: http://ec.europa.eu/research/evalua-

tions/pdf/archive/fp7_monitoring_reports/7th_fp7_monitoring_report.pdf

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TABLE 7.2

THE PARTICIPANTS’ AGE COMPARED TO THE GENERAL POPULATION OF INDIVIDUALS

WORKING WITH R&D

Researchers

Under 25 years

25-29 years

30-34 years

35-39 years

40-44 years

45-49 years

Over 50 years

15 %

23 %

21 %

17 %

22 %

Researchers

in general

14 %

23 %

19 %

17 %

26 %

PhD

students

60 %

26 %

PhD students

in general

50 %

29 %

11 %

Masters

10 %

14 %

13 %

11 %

12 %

40 %

Masters in

general

19 %

20 %

14 %

10 %

27 %

Source: DASTI’s own calculation using registry data from Statistics Denmark.

7.2.3. Field of science

Participants are more likely to be educated within either natural science or technical

science compared to the general level. Furthermore, participants are less likely to be

educated within either humanities or social science compared to the general level.

The share of participating PhD students within health science is substantially lower

than for the PhD students in general. For the PhD students participating in a FP6 or

FP7 project, only 11 per cent have health as a field of science, while this is the fact for

20 per cent for PhD students in general (see table 7.3).

TABLE 7.3

THE PARTICIPANTS’ FIELD OF SCIENCE COMPARED TO THE GENERAL POPULATION OF IN-

DIVIDUALS WORKING WITH R&D

Humanities

Researchers

in general

PhD students

in general

Masters

Masters in

general

19 %

10 %

26 %

Agricul-

tural sci-

ence

13 %

Natural

science

34 %

23 %

39 %

24 %

34 %

20 %

Social

science

16 %

10 %

14 %

20 %

Health

science

12 %

13 %

11 %

20 %

13 %

10 %

Technical

science

31 %

21 %

26 %

15 %

22 %

15 %

Unspecified

18 %

Source: DASTI’s own calculation using registry data from Statistics Denmark.

7.2.4. Citizenship

Figure 7.2 shows that a larger share of the participants in FP6 or FP7 are foreigners

compared to the general level. The participating PhD students have the largest share

of foreigners. 34 per cent of the participating PhD students are foreigners compared

to 27 per cent for PhD students in general.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

FIGURE 7.2

THE PARTICIPANTS’ CITIZENSHIP COMPARED WITH THE GENERAL LEVEL

Pct.

100

Researchers

in general

PhD students

in general

Masters

in general

Danish

Foreign

Note: Participants are defined as foreigners if they do not have Danish citizenship and Denmark as

country of origin.

Source: DASTI’s own calculation using registry data from Statistics Denmark.

7.2.5. Career

Table 7.4 compares the participants’ career. The participants’ career is described us-

ing the International Standard Classification of Occupations (ISCO) (see box 7.1 for

further information).

The PhD students participating in FP6 or FP7 are underrepresented in high-

ly-skilled specialist positions compared to PhD students in general. A little more

than half of them are highly-skilled specialists, where this is the case for approxi-

mately three quarters of PhD students in general. On the other hand, 12 per cent

of the participating PhD students have an unknown classification of occupations,

compared to only 2 per cent of the PhD students in general. This is due to a higher

proportion of foreigners among the participating PhD students, since the registers

are not as complete for foreigners as for Danes.

Over 50 per cent of the participating researchers are employed in highly-skilled

specialist positions, while over 50 per cent of the participating masters are em-

ployed as specialists in general positions. Very few of the participants are working as

leaders, equal to 3 and 4 per cent for researchers and masters respectively.

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

TABLE 7.4

THE PARTICIPANTS’ CAREER POSITION COMPARED TO THE GENERAL POPULATION OF IN-

DIVIDUALS WORKING WITH R&D

Leaders

Researchers

Researchers in general

PhD students

PhD students in general

Masters

Masters in general

Specialists in

general

40 %

35 %

23 %

54 %

Highly-skilled

specialists

54 %

52 %

73 %

33 %

Others

Unspecified

12 %

Note: Leaders are DISCO code 1000-1999, Specialists in general are DISCO code 2000-2999 except

2310, Highly-skilled specialists are DISCO code 2310 and Others are 3000 – 9998.

1) Researchers and masters in general are selected so that individuals with a master’s degree and

PhD degree are only selected if employed in DISCO 2310 (research at universities) or in NACE

codes 72.11.00, 72.19.00 and 72.20.00 (public or private R&D companies). Comparison between

participating researchers and masters and their general level is not possible because the selection

method for the comparable individuals causes bias.

Source: DASTI’s own calculation using registry data from Statistics Denmark.

11 and 42 per cent respectively of the participating researchers and PhD students in

highly-skilled positions are foreigners (see table 7.5).

Participation in FP6 or FP7 therefore gives Denmark the possibility of benefitting

from the pool of international talent. This hopefully creates a knowledge spill-over

to the Danish research teams.

TABLE 7.5

PARTICIPATING HIGHLY-SKILLED SPECIALISTS EMPLOYED AT A UNIVERSITY DIVIDED ON

CITIZENSHIP AND COUNTRY OF ORIGIN

Highly-skilled specialists

Researchers

PhD students

Masters

Danish

Foreign

Danish

Foreign

Danish

Foreign

89 %

11 %

58 %

42 %

70 %

30 %

Note: Participants are defined as foreigners if they do not have Danish citizenship and Denmark as

country of origin.

Source: DASTI’s own calculation using registry data from Statistics Denmark.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

BOX 7.1 THE INTERNATIONAL STANDARD CLASSIFICATION OF OCCUPATIONS (ISCO)

DISCO is the official Danish version of the International Standard Classification of Occupations. DISCO

is a six-digit classification with a hierarchical structure with five levels. DISCO divides the Danish labour

market into 563 occupational groups, each containing a number of closely-related occupations.

The analysis divides the DISCO codes into five groups:

Leaders: Leadership in a private or public company [1000-1999]

Highly-skilled specialists: Research at universities

[

2310]

Specialists in general: Work that requires high-level knowledge [2000-2999], excluding Highly-skilled

specialists

Others: Work that requires medium-level knowledge or lower [3000-9998]

Unknown: Unknown DISCO [0 and 9999]

7.2.6. Sector

Table 7.6 compares the participants’ employment in sectors using the European In-

dustry Standard Classification System (NACE) (see box 7.2 for further information).

The participating PhD students are overrepresented in the university sector and in

public and private R&D companies, compared to PhD students in general. 82 per

cent of the participating PhD students are employed at a university, compared to 75

per cent for PhD students in general.

Comparing the three participant groups shows that masters are more often em-

ployed in the private sector compared to researchers and PhD students.

TABLE 7.6

THE PARTICIPANTS’ CAREER IN SECTOR COMPARED TO THE GENERAL POPULATION OF

INDIVIDUALS WORKING WITH R&D

Public or private

R&D company

Researchers

Researchers in general

PhD students

PhD students in general

Masters

Masters in general

12 %

11 %

Public sector

16 %

20 %

Private sector

14 %

29 %

Universities

66 %

82 %

75 %

41 %

Note: Public or private R&D departments are NACE codes 72.11.00, 72.19.00 and 72.20.00.

1)The masters and researchers in general are selected so that individuals with a master’s degree and

PhD degree are only selected if employed in DISCO 231000 (research at universities) or in NACE

codes 72.11.00, 72.19.00 and 72.20.00 (public or private R&D companies). Comparison between

participating researchers and masters and their general level is not possible because the selection

method for the comparable individuals causes bias.

Source: DASTI’s own calculation using registry data from Statistics Denmark.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

BOX 7.2 THE EUROPEAN INDUSTRY STANDARD CLASSIFICATION SYSTEM (NACE)

The NACE (European Industry Standard Classification System) code represents the sector of a compa-

ny’s main activity.

NACE is a six-digit classification where the first four digits correspond to the European classification and

the last two are a Danish classification. NACE divides the Danish companies into 730 groups according

to their main activities, each containing a number of closely-related activities.

The analysis divides the NACE codes into four sectors:

Universities: 85.42.00

Public sector: [84.10.00 – 89.00.00] excluding Universities but including public administration, hospitals

and other health sector

Public or private R&D companies: 72.11.00, 72.19.00 and 72.20.00

Private sector: All the other NACE codes

7.3.

Methods

The data for the analysis are from three sources:

• The European Commission’s eCORDA database. The information includes the

names of the coordinators from the participating Danish institutions and com-

panies.

• Names of the other participants in the projects (i.e. non-coordinators). These

data were gathered by contacting the coordinators listed in the eCORDA data-

base.

• Public register data

from Statistics Denmark. These are employer-employ-

ee-linked data including information on individuals (demographic information,

information on education and occupation).

7.3.1. Collection of data on individual level

DASTI has collected data on all individuals that have participated in a FP6 or FP7

project through a Danish research institution or company. These data were gathered

by contacting the coordinators from the different participating Danish institutions

and companies. DASTI has collected data such as full name, gender of the partici-

pants and place of employment at the time of the project. The criteria for participa-

tion include also:

• Participants from private companies and not only research and educational in-

stitutions

• Foreigners and Danes who are employed by a Danish institution or company.

• Participants who are not paid directly with funds from the project but who have

contributed significant academic and professional knowledge.

DASTI has had a response from 40 per cent of the projects. The response rate is

higher for FP7 than FP6. Data on 5,324 participants were collected, which is equal

to 4,506 unique individuals.

35 Integrated Database of Labour Market Research (IDA), Education, Population and Wage Statis-

tics Database

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

TABLE 7.7

COLLECTION OF DATA ON INDIVIDUAL LEVEL

FP6

Number of projects

Response rate

Number of individuals

302

26.8 %

1,291

FP7

945

47.9 %

4,033

Total

1,247

40.2 %

5,324

The collected data on the participants were merged with data from the European

Commission’s eCORDA database and with public register data from Statistics

Denmark. Some participants have quite common names, meaning that the public

ipant. The right participant out of several possible participants was found by using

the person’s highest completed education, current education and employment (The

International Standard Classification of Occupations) as delimitation. Through the

use of public register data it has been possible to identify 2,429 individuals that

have participated in a FP6 or FP7 project. Some of these participants have been

removed from the analysis due to lack of public register data on the participant in

the year of project start, or one to two years after, or due to project start after 2012.

Thus, the final group of participants consists of 2,000 individuals for the period

2003-2012.

7.3.2. Method for comparison – selection of comparable individuals

For the comparison the participants are aggregated into three groups:

• Researchers: The participants that have a PhD degree at the start of the project

• PhD students: The participants that are PhD students during the project

• Masters: The participants that have a master’s degree but are not PhD students

The participants from the three groups are measured in the year of the project start.

If there is no data for the participant in the year of project start, one year or two

years after project start is used.

To get an impression of the general level of individuals working with R&D in

Denmark, the participants are compared to the general level of the research staff in

2012. 2012 is the last year for which public register data is available for this analysis.

Researchers in general: The participating researchers are compared to research-

ers in general consisting of all individuals with a PhD degree in 2012. To ensure that

the participating researchers are compared with researchers still doing research,

only individuals with a PhD degree employed in the International Standard Classi-

fication of Occupations group “Teaching at universities with research obligation” or

in The European Industry Standard Classification Systems group “R&D in a public

or private company” are used.

Masters in general: Participating masters are compared to masters in general,

consisting of all individuals with a master’s degree in 2012 and working within re-

search. Thus, masters in general only contain those who are employed in the Inter-

national Standard Classification of Occupations group “Teaching at universities with

research obligation” or in The European Industry Standard Classification Systems

group “R&D in a public or private company”.

PhD students in general: The participating PhD students are compared to PhD

students in general, consisting of all PhD students starting in 2012.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

Collecting data on all the participants ex post has been a challenge.

Some of the challenges have been

• to get a satisfying response rate. A low response rate challenges the quality of an

evaluation.

• for the coordinators to remember who participated in which projects several

years back in time.

• that some participants have such common names that the public register data

contained several possible personal identification numbers per participant. It

can therefore be difficult to find the right participant.

For the evaluation of Horizon 2020 it could be interesting to do an impact assess-

ment using the propensity score matching method. Then participants would be

matched with statistically identical individuals, and a difference-in-differences

method would estimate the differences in the development for the participants and

the statistically identical individuals. This is difficult to do when we do not know all

of the participating individuals.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

8. Annexes

8.1.

Annex 1 – Participation of Denmark and private companies in

FP6 and FP7

Tables 8.1 and 8.2 present a detailed view of the participation of Denmark in FP6

and FP7.

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

TABLE 8.1

THE PARTICIPATION OF DENMARK IN FP6 (2003-2006) – DETAILED VERSION

ALL COUNTRIES

Specific

Programme

Priority Area

Life sciences,

genomics and

biotechnology for

health

Information so-

ciety

technologies

Nanotechnologies

and

nanosciences,

knowledge-based

multifunctional

materials and new

production pro-

cesses and devices

INTEGRATING AND STRENGTHENING THE ERA

Aeronautics and

space

Food quality and

safety

Sustainable de-

velopment, global

change and eco-

systems

Citizens and

governance in a

knowledge-based

society

Policy support

and anticipating

scientific and tech-

nological needs

Horizontal re-

search activities

involving SMEs

Specific measures

in support of in-

ternational coop-

eration

Support for the

coherent develop-

ment of research

& innovation

policies

Support for the

coordination of

activities

Integrating and

strenghtening the

ERA total

STRUCTURING THE ERA

Research and in-

novation

Human resources

and mobility

Research

infrastructures

Science and

society

Structuring the

ERA total

Euratom

Projects

Participants

(incl.

Coordinators)

EC Contri-

bution

(EUR m )

Projects

Participants

(incl.

Coordinators)

DENMARK

Coordinators

EC Contri-

bution

(EUR m)

Share of

EC Contri-

bution

600

1,093

6,828

14,340

2,339.6

3,799.5

150

134

203

199

80.3

48.6

3.43 %

1.28 %

446

241

185

5,883

3,496

3,209

1,539.0

1,068.6

751.6

107

138

25.7

4.4

52.9

1.67 %

0.42 %

7.04 %

671

10,560

2,306.5

177

317

83.7

3.63 %

146

1,949

244.2

4.9

2.01 %

522

492

4,606

5,458

601.7

485.2

115

157

123

20.2

10.9

3.35 %

2.24 %

343

2,514

351.6

5.3

1.50 %

102

4,860

237

4,617

154

161

5,169

10,107

169

1,204

60,216

1,841

8,475

1,841

1,025

13,182

1,185

74,583

13.8

288.0

13,789.4

225.4

1,693.2

725.2

77.8

2,721.6

185.7

16,696.6

900

158

219

1,125

1,380

172

257

1,646

115

210

0.1

5,0

342.0

5.3

40.3

4.9

2.5

53.0

1.1

396.1

0.51 %

1,74 %

2.48 %

2.33 %

2.38 %

0.67 %

3.25 %

1.95 %

0.59 %

2.37 %

EURATOM

Total

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

TABLE 8.2

THE PARTICIPATION OF DENMARK IN FP7 (2007-2013) – DETAILED VERSION

Priority Area

ALL COUNTRIES

Participants

(incl. coordi-

nators)

11,297

7,903

22,502

10,235

Contribution

(EUR m)

4,791.7

1,850.7

7,877.0

3,238.6

Parti-

pants

(incl.

coordi-

nators)

265

285

297

223

DENMARK

Contribution

(EUR m)

136.6

84.4

105.7

81.6

Projects

Health

Food, Agriculture

and Fisheries, and

Biotechnology

Information and

Communication

Technologies

Nanosciences,

Nanotechnologies,

Materials and

new Production

Technologies - NMP

Energy

Environment

(including Climate

Change)

Transport (including

Aeronautics)

Socio-economic

Sciences and

Humanities

Space

Security

General Activities

Joint Technology

Initiatives (JTI)

COOPERATION

total

European Research

Council

IDEAS total

Marie-Curie Actions

PEOPLE total

Research Infra-

structures

Research for the

benefit of SMEs

Regions of Know-

ledge

Research Potential

Science in Society

Support for the

coherent develop-

ment of research

policies

International Co-

operation

CAPACITIES total

Fusion Energy

Nuclear Fission

and Radiation

Protection

Euratom total

EURATOM

Total

CAPACITIES

IDEAS

PEO-

PLE

COOPERATION

1,008

516

2,328

805

Projects

202

176

218

152

Coordinators

Share of EU

Contribution

2.85 %

4.56 %

1.34 %

2.52 %

368

494

719

253

267

314

736

7,834

4,525

10,716

341

1,028

206

183

4,272

7,148

9,029

2,770

2,636

3,836

183

5,812

87,623

5,405

19,515

5,267

9,124

1,005

307

1,820

131

1,707.4

1,719.3

2,284.2

579.6

713.3

1,295.5

312.7

1,966,4

28,336.3

7,673.5

4,777.4

1,528.4

1,249.1

126.7

377.7

288.4

28.3

130

1,256

384

130

164

175

157

1,819

433

217

141

232

92.5

50.8

26.7

15.4

12.5

14.3

1.1

51.1

672.7

146.3

152.2

34.5

37.8

3.2

0.0

12.1

0.2

5.42 %

2.96 %

1.17 %

2.66 %

1.75 %

1.10 %

0.36 %

2.60 %

2.37 %

1.91 %

3.19 %

2.25 %

3.02 %

2.55 %

0.00 %

4.21 %

0.53 %

157

2,025

134

138

25,238

1,393

19,047

1,958

2,025

133,615

173.4

3,772.0

5.2

352.8

358.1

44,917.2

272

2,011

392

2,754

503

0.7

88.4

0.1

0.9

1.0

1,060.6

0.42 %

2.34 %

1.79 %

0.25 %

0.27 %

2.36 %

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

Tables 8.3 and 8.4 present a view of the participation of Danish private companies in FP6 and FP7, divided into large en-

terprises and small and medium-sized enterprises (SMEs).

TABLE 8.3

THE PARTICIPATION OF DANISH PRIVATE COMPANIES IN FP6 DIVIDED INTO LARGE ENTERPRISES AND SMES

FP6

Large enterprises

Contribution

(EUR)

28,428,427.90

Share of EU

contribution

to DK to the

particular

programme

8.31 %

SMEs

Contribution

(EUR)

40,144,656.72

Share of EU

Contribution

to DK to the

particular

programme

10.49 %

Programme

Integrating and

strenghtening the

ERA total

Life sciences,

genomics and

biotechnology for

health

Information society

technologies

Nanotechnologies

and nanosciences,

knowledge-based

multifunctional ma-

terials and new pro-

duction processes

and devices

Aeronautics and

space

Food quality and

safety

Sustainable develop-

ment, global change

and ecosystems

Citizens and gov-

ernance in a knowl-

edge-based society

Policy support and

anticipating scien-

tific and technologi-

cal needs

Horizontal research

activities involving

SMEs

Specific measures in

support of interna-

tional cooperation

Research and inno-

vation

Human resources

and mobility

Research

Infrastructures

Science and

society

Structuring the ERA

total

Euratom total

Total

Participants

127

Coordinators

Participants Coordinators

241

6,337,552.38

2,798,656.05

7.90 %

5.75 %

6,984,444.86

5,239,362.99

8.70 %

10.77 %

2,958,798.00

303,560.00

1,318,640.00

13,549,319.47

11.49 %

6.84 %

2.49 %

16.18 %

6,218,272.49

1,169,349.00

948,621.00

12,125,892.43

26,400.00

24.16 %

26.35 %

1.79 %

14.48 %

0.54 %

136

507,381.00

654,521.00

445,046.61

174,250.00

619,296.61

29,047,724.51

2.51 %

6.01 %

1.10 %

3.58 %

0.00 %

1.17 %

0.00 %

7.33 %

257

1,616,808.00

5,652,772.95

162,733.00

1,905,007.00

289,587.32

526,940.00

2,721,534.32

81,199.00

42,947,390.04

8.01 %

51.90 %

3.09 %

36.21 %

0.72 %

0.00 %

20.85 %

5.14 %

7.38 %

10.84 %

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Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

TABLE 8.4

THE PARTICIPATION OF DANISH PRIVATE COMPANIES IN FP7 DIVIDED INTO LARGE ENTERPRISES AND SMES

FP7

Large Enterprises

Share of EU

Contribution

to DK to the

particular

programme

9.07 %

3.22 %

SMEs

Share of EU

Contribution

to DK to the

particular

programme

18.94 %

28.45 %

Programme

COOPERATION

total

Health

Food, Agri-

culture and

Fisheries, and

Biotechnology

Information and

Communication

Technologies

Nanosciences,

Nanotechnolo-

gies, Materials

and new Pro-

duction Tech-

nologies

Energy

Environment

(Including Cli-

mate Change)

Transport

Socio-economic

Sciences and

Humanities

Space

Security

Joint Technol-

ogy Initiatives

(JTI)

PEOPLE total

Research Infra-

structures

Research for

the benefit of

SMEs

Regions of

Knowledge

International

Cooperation

Science in So-

ciety

CAPACITIES

total

Fission

Euratom total

Total

Participants

190

Coordina-

tors

EU Contribu-

tion (EUR)

61,028,239

4,400,360

Participants

353

Coordinators

EU Contribu-

tion (EUR)

127,431,573

38,856,722

3,999,326

4.74 %

7,126,287

8.44 %

5,487,710

5.19 %

21,672,109

20.51 %

6,507,794

25,906,202

7.98 %

28.02 %

19,723,092

14,255,505

24.17 %

15.42 %

59,998

2,123,919

0.12 %

7.97 %

3,586,760

5,336,889

7.05 %

20.02 %

1,538,509

0.00 %

10.79 %

260,150

891,448

4,734,398

1.69 %

7.12 %

33.21 %

11,004,422

8,856,401

21.52 %

5.82 %

0.00 %

10,988,213

7,661,007

527,415

21.48 %

5.03 %

1.53 %

238

1,906,508

82,117

121,070

2,109,695

71,994,336

5.05 %

2.54 %

16.78 %

0.00 %

2.39 %

0.00 %

6.79 %

125

129

516

32,121,377

69,225

332,139

33,050,156

145,149

168,287,885

85.06 %

2.14 %

0.00 %

2.74 %

37.37 %

16.77 %

15.13 %

15.87 %

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

UFU, Alm.del - 2015-16 - Endeligt svar på spørgsmål 168: Spm. om ministeren vil fremsende relevante evalueringer af Globaliseringspuljen 2007-12, til Uddannelses- og forskningsministeren

Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

8.2.

Annex 2 – Individual participation

This annex describes the characteristics of the participants not categorised as re-

searchers, PhD students or masters.

8.2.1. Age

Other participants are generally younger than participants categorised as research-

ers, masters and PhD students. 14 per cent of the other participants are under 25

years old compared to 4 per cent for the participating PhD students and 0 per cent

for the participating researchers and masters.

TABLE 8.5

OTHER PARTICIPANTS DIVIDED BY AGE

Under 25

years

Other

14 %

25-29

years

22 %

30-34

years

19 %

35-39

years

12 %

40-44

years

10 %

45-49

years

Over

50 years

17 %

Source: DASTI’s own calculation using registry data from Statistics Denmark.

Since there are no records on when the participants enter the projects, they are

measured in the year of project start, even though participants are not necessar-

ily included in the projects from the start. This implies that some participants are

measured before they even participate in the projects, and thus they have not yet

completed their master’s degree or started their PhD. This is one possible expla-

nation for why these participants are not categorised as researchers, PhD students

or masters. The high proportion of other participants under 25 years supports this

explanation.

8.2.2. Field of science

Like researchers, PhD students and masters, a large share of the other participants

have an education within technical science. A quarter of the other participants have

an unspecified education.

TABLE 8.6

OTHER PARTICIPANTS DIVIDED BY THEIR FIELD OF SCIENCE

Humanities

Others

10 %

Agricul-

tural sci-

ence

Natural

science

Social

science

14 %

Health

science

Technical

science

36 %

Unspecified

24 %

Source: DASTI’s own calculation using registry data from Statistics Denmark.

8.2.3. Career

Table 8.7 shows other participants’ career position broken down by citizenship. 54

per cent of the participating others that are foreigners are in highly-skilled specialist

positions, and 27 per cent are employed as specialists in general. Also 44 per cent of

the Danish participants are employed as specialists in general or highly-skilled spe-

cialists. This indicates that these other participants probably are researchers, PhD

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

UFU, Alm.del - 2015-16 - Endeligt svar på spørgsmål 168: Spm. om ministeren vil fremsende relevante evalueringer af Globaliseringspuljen 2007-12, til Uddannelses- og forskningsministeren

Effects of participation in EU framework programmes for research and technological development – for researchers, institutions and private companies in Denmark

students or masters, but this is not recorded due to incomplete public registers. The

public register of education is particularly inadequate for foreigners.

42 per cent of the Danish participating others are in positions that only require

skills on an intermediate level or lower (others). As with age, this indicates that

these participants are measured at a time when they have not yet started their pro-

ject participation and thus are not employed in relevant jobs. However, some of the

participants employed in positions that only require skills on an intermediate level

can also be laboratory technicians or the like.

TABLE 8.7

OTHER PARTICIPANTS DIVIDED BY CAREER POSITION AND CITIZENSHIP

Leader

Danish

Foreign

Total

Specialists in

general

31 %

27 %

29 %

Highly-skilled

specialists

13 %

54 %

29 %

Others

42 %

28 %

Unknown

10 %

13 %

11 %

Note: Leaders are DISCO code 1000-1999, Specialists in general are DISCO code 2000-2999 except

2310, Highly-skilled specialists are DISCO code 2310 and Others are 3000 – 9999.

Source: DASTI’s own calculation using registry data from Statistics Denmark.

8.2.4. Sector

Table 8.8 shows the participants’ employment in sectors broken down by citizen-

ship. Approximately three-quarters of the participating others that are foreigners

are employed at a university. As for the participants’ career position, this indicates

that they probably have a PhD or master’s degree, but this is not recorded due to

incomplete registers.

Only a quarter of the Danish participants are employed at a university, which

again indicates that these participants are measured at a time when they have not

yet started their project participation and thus are not employed in relevant jobs.

TABLE 8.8

OTHER PARTICIPANTS DIVIDED BY SECTORS AND CITIZENSHIP

Public or private

R&D companies

Danish

Foreigner

Total

Public sector

25 %

17 %

Private sector

43 %

11 %

31 %

Universities

23 %

76 %

44 %

Source: DASTI’s own calculation using registry data from Statistics Denmark.

36 Because of incomplete registers, there is a lack of information about some of the participants’

highest completed education or ongoing education. The variable “highest completed education”

only registers the level of the latest education if this is completed in Denmark. Thus Danes or

foreigners who have taken their PhD degree abroad will not be registered as a researcher, as is

the case with individuals taking their master’s degree abroad.

Ministry of Higher Education and Science – Danish Agency for Science, Technology and Innovation

UFU, Alm.del - 2015-16 - Endeligt svar på spørgsmål 168: Spm. om ministeren vil fremsende relevante evalueringer af Globaliseringspuljen 2007-12, til Uddannelses- og forskningsministeren UFU, Alm.del - 2015-16 - Endeligt svar på spørgsmål 168: Spm. om ministeren vil fremsende relevante evalueringer af Globaliseringspuljen 2007-12, til Uddannelses- og forskningsministeren