Exploring Current Trends in Scientific
Research on Smart Specialisation
Luca Mora, Mark Deakin, Alasdair Reid
Scienze Regionali, vol. 18, 3/2019, pp. 397-422
© Società editrice il Mulino
Abstract: This paper describes current trends in scientific research on Smart Spe-
cialisation by answering the following questions: 1) How many scientific publications
on Smart Specialisation have been produced since this concept emerged and what are
their characteristics in terms of type and influence?; 2) How large is the community of
researchers, organisations and countries working in this field?; 3) What is their influ-
ence and productivity?; 4) What are the main regional knowledge hubs and the key
knowledge producers?; and 5) What are the highly-cited knowledge objects published
by the research community? The answers are sourced from a bibliometric analysis of
the scientific publications produced during the first 12 years of research on Smart
Keywords: smart specialisation, research trends, core literature, knowledge producers.
JEL classification: O31, O33, R11, R58.
In March 2000, the European Council set a new strategic goal: to make
the most dynamic and competitive knowledge-based economy in the world [by 2010], capable
of sustainable economic growth with more and better jobs and greater social cohesion, and
respect for the environment (Rodriguez et al., 2010, p. 11).
This goal represents the core of the Lisbon Strategy, which affirms the
European Union’s political ambitions and the determination of its Member
States to undertake the structural improvements required to harness the
The research leading to these results is part of the research project ONLINE S3 (ONLINE Platform for
Smart Specialisation Policy Advice), which has received funding from the European Union’s Horizon
2020 Research and Innovation Programme under the grant agreement n. 710659.
Luca Mora: The Business School, Edinburgh Napier University, Edinburgh, EH14 1DJ, United
Kingdom. E-mail: L.Mora@napier.ac.uk, corresponding author
Mark Deakin: School of Engineering and the Built Environment, Edinburgh Napier University,
Edinburgh, EH10 5DT, United Kingdom. E-mail: M.Deakin@napier.ac.uk
Alasdair Reid: School of Engineering and the Built Environment, Edinburgh Napier University,
Edinburgh, EH10 5DT, United Kingdom. E-mail: Al.Reid@napier.ac.uk
398 | Luca Mora, Mark Deakin, Alasdair Reid
full benefits offered by «the transition to a knowledge-based economy and
society» (European Council, 2000, p. 3). With this strategy, the European
Union started to recognize the driving force of knowledge creation, diffusion
and exploitation in supporting the resolution of the social, economic and
environmental challenges that its regions are facing and generating sustain-
able growth and prosperity (European Commission, 2010a).
To accelerate this transition and support the achievement of the Lisbon
Strategy’s objectives, in 2005 the European Commission set up the Knowl-
edge for Growth (K4G) Expert Group1. This group of European economists
was tasked with operating as an independent advisory body and providing
high-level recommendations on how to develop research and innovation poli-
cies able to move Europe towards a competitive knowledge-based economy
(Deakin et al., 2017, 2018; European Commission – Directorate-General
for Research, 2008; Komninos et al., 2018a, 2018b; Knowledge for Growth
Expert Group, 2009; Panori et al., 2018). The high-level recommendations
proposed by the Expert Group were published between 2005 and 2009
as a series of reports and policy briefs (see Foray, 2006; David, Metcalfe,
2007; Foray, Van Ark, 2007; Knowledge for Growth Expert Group, 2007;
O’Sullivan, 2007; Marimon, Carvalho, 2008; Foray et al., 2009; Giannitsis,
Kager, 2009; Hall, Mairesse, 2009; Veugelers, Mrak, 2009).
These publications offer advice on the policy challenges that the Euro-
pean Union needs to address in order to pave the way for a competitive
knowledge economy: the deficit in R&D and innovation; the governance of
science and technology systems; the globalisation of R&D; the interrelation
between technology production and diffusion; and the relationship between
higher education institutions and industry. In addition, these advisory docu-
ments introduce the concept of Smart Specialisation, which emerges as a
leading idea of the K4G Expert Group and is presented in the policy briefs
by Foray and Van Ark (2007) and Foray et al. (2009).
According to the K4G Expert Group
Europe is losing ground as a centre for research and innovation (European Commission –
Directorate-General for Research, 2008, p. 13)
companies are increasingly looking outside Europe for their R&D, and overseas companies
are less and less inclined to base their R&D in Europe (Foray, Van Ark, 2007, p. 1).
The Expert Group suggests that the solution to this problem is to create
1 The Knowledge for Growth (K4G) Expert Group is no longer active. Its activities were com-
pleted in June 2009 and then presented during the final conference S&T Policy in Times of Crisis:
Prospects for the Knowledge-Based Economy. The conference documentation can be found on the
European Union’s website: http://ec.europa.eu/invest-in-research/monitoring/knowledge_en.htm.
Exploring Current Trends in Scientific Research on Smart Specialisation | 399
global R&D hubs which can compete with foreign hubs to attract more research capacities
and other knowledge resources (European Commission – Directorate-General for Research,
2008, p. 13).
This requires countries and regions across Europe to engage in the so-
called «Smart Specialisation process», which entails the identification and
subsequent development of the most promising research and innovation
domains by means of a prioritization logic. These research and innovation
domains are considered as areas of specialisation, and their identification is
based on a process of entrepreneurial discovery: a bottom-up and place-based
collaborative learning process, during which local entrepreneurs form mutu-
ally reinforcing connections and pool their knowledge in order to identify
and explore the specialisation areas that can best support the growth of the
regional economy (Foray et al., 2009).
As McCann and Ortega-Argilés (2015), Capello (2014) and Kroll (2015)
highlight, after the publication of the first policy briefs, the concept of Smart
Specialisation started to move out from the grey literature2 produced by the
K4G Expert Group and enter the scientific publishing system, opening up
a new research field and marking the beginning of an international debate.
This paper aims to capture the effects of this transition by reporting on the
results of an exploratory study on current trends in Smart Specialisation
research3. In doing so, the paper addresses the following questions:
1) How many scientific publications dealing with Smart Specialisation
have been produced since 2005 and what are their characteristics in terms
of type and influence?
2) How large is the community of researchers, organisations and countries
working in this research field?
3) What is the influence and productivity of the entities belonging to
4) What are the main regional knowledge hubs and the key knowledge
producers in the field of Smart Specialisation?
5) What are the highly-cited knowledge objects published by the research
To answer these questions, a bibliometric analysis was conducted in which
the count of publications, authors, organisations and citations was combined
with network analysis in order to examine: 1) the scientific literature deal-
2 Grey literature consists of those publications that are «produced on all levels of government,
academics, business and industry in print and electronic formats, but [are] not controlled by com-
mercial publishers, […] i.e., where publishing is not the primary activity of the producing body»
(Schopfel, 2010). This type of literature is therefore published without being subject to the traditional
academic peer-review process (Adams et al., 2017).
3 This analysis does not map the topics and subject areas emerging in the field of Smart Spe-
cialization. Additional research focusing on this knowledge gap would be very beneficial and would
help the community of researchers working in this field to acquire an improved understanding of
its overall organization, extending the findings of the bibliometric study that this paper reports.
400 | Luca Mora, Mark Deakin, Alasdair Reid
ing with Smart Specialisation published between 2005 and 2016, a period
corresponding to the first decade of research on this subject; and 2) the
community of researchers who produced such literature.
The paper is divided into three main sections. Section 2 describes the
methodology used to conduct the bibliometric analysis, in particular, the
data collection and processing approach and the metrics adopted during
the analytical process. Section 3 is organized into four sub-sections, each
reporting the results of the analysis, which provide researchers investigating
Smart Specialisation with a comprehensive picture of their research field and
a better understanding of how its intellectual structure is being shaped. Sec-
tion 4 concludes the paper by summarizing the results and discussing their
significance in the broader debate on Smart Specialisation.
This section of the paper describes in more detail the methodology used
to conduct the bibliometric analysis. The analysis began with a search phase
designed to build an accurate representation of the research field under in-
vestigation by collecting a large sample of scientific publications on Smart
Specialisation. This literature search was conducted in February 2017 using
Web of Science and Scopus, which are two of the main databases supporting
the development of bibliometric analyses (Bakkalbasi et al., 2006; Komninos,
Mora, 2018; Mongeon, Paul-Hus, 2016; Mora et al., 2017). The decision to
adopt a multi-database approach was based on research undertaken by De
Groote and Raszewski (2012), Jacobsen et al. (2013), Levine-Clark and Gil
(2008) and Zhao et al. (2009), who all suggest using a single search tool
brings data reliability into question.
To set up the search, a timespan of twelve years was selected, from
2005 to 2016, and a search query was run to identify all the publications
in which the keyword «Smart Specialisation» was included in their titles,
abstracts, keyword lists or full texts4. Both American and English spellings
of the keyword were considered. In addition, no restrictions for languages
and document types were imposed to filter the results. The search initially
produced 274 results, which were subsequently transferred into a single
dataset. However, after eliminating duplicate publications indexed by both
Web of Science and Scopus, 205 documents remained, which were grouped
into the following five categories: Books (4); Book chapters (8); Conference
4 Considering the specific interest of this study in research focused on the concept of Smart
Specialisation, a decision was taken to design the literature search so that only publications contain-
ing the term «Smart Specialisation» were captured. No varying or related terms were considered
during the search. This made it possible to avoid the risk of adversely affecting the bibliometric
analysis by including publications that did not explicitly relate to what Smart Specialisation means
as a knowledge object.
Exploring Current Trends in Scientific Research on Smart Specialisation | 401
papers (58); Articles published in scholarly journals (128); Other (7)5. This
last category includes book reviews, editorials and books’ forewords. The
raw data necessary to perform the analysis was extracted from this group
of publications, which can be considered as the source documents of this
bibliometric analysis (Small, Crane, 1979; Shiau, Dwivedi, 2013).
The data obtained from the source documents made it possible to compute
the following group of metrics, which provide insights into the research ques-
tions and support the identification of current trends in research on Smart
Specialisation6. A full description of each metric is provided by Colledge
and Verlinde (2014), in the SciVal Metrics Guidebook7.
Metric 1: Author and organization count
Authors’ full names were extracted in each source document, along with
the information related to their affiliations8, which were grouped into four
categories: 1) University; 2) Business; 3) Government; and 4) Other. This
process made it possible to reconstruct the community of researchers and
organisations working in the field of Smart Specialisation, analyse its overall
structure and compare the distribution of authors and organisations in dif-
ferent geographic regions.
Metric 2: Publication count
This productivity metric was used to measure and compare the scientific
output at any level of aggregation (author, organisation and country). Dur-
ing the count, publications produced by multiple entities were split and
each entity was assigned an equal part. This means that a publication was
only counted once even when it was co-authored9. The counting process is
explained in Table 1.
5 The number of publications belonging to each category is shown in brackets. To be noted is that
only peer-reviewed publications are considered in this study. Grey literature, which is not indexed
by either Scopus or Web of Science, was excluded from the search process.
6 Considering that bibliometric data extracted from scholarly databases often contain errors
(Adam, 2002; Bar-Ilan, 2008), all data was checked for accuracy and changes were made when
necessary by cross-referencing the information obtained from four different sources: Web of Sci-
ence; Scopus; the full texts of the source documents; and the publishers’ repositories in which each
source document is stored.
7 SciVal is one of the Elsevier’s Research Intelligence digital tools. It is designed to support
researchers and research managers in gathering bibliometric data and analyzing research trends.
Additional information describing the functioning and features of Scival can be found on its official
8 In the case of authors with a double affiliation, only the one that they positioned first was
considered. This choice made it possible to simplify the management of the data related to a small
percentage of the analysis sample: 3.8% of the total 395 authors.
9 When available, the online publication date was considered for the classification of the source
402 | Luca Mora, Mark Deakin, Alasdair Reid
Table 1: Methodology for publication count
Source document Entity 1: Authors Entity 2: Organisations Entity 3: Countries
SD1 A1 O1 C1
SD1 A2 O1 C1
SD1 A3 O2 C2
SD1 A4 O3 C3
Counting Process A1 = 0.25 O1 = 0.50 C1 = 0.50
A2 = 0.25 O2 = 0.25 C2 = 0.25
A3 = 0.25 O3 = 0.25 C3 = 0.25
A4 = 0.25
Metric 3: Citation count10
This impact metric was used to compare the influence of authors, or-
ganisations and countries actively involved in scientific research on Smart
Specialisation. The influence of each entity was measured by counting the
number of citations that its source documents received from other source
documents. Citation data was extracted manually by analysing the reference
section of each source document. As in the case of the publication count,
when a source document was authored by two or more entities, the total
number of citations that it had received was divided equally, and each entity
was assigned an equal share.
The citation count was also used to identify the core literature on Smart
Specialisation. In a group of publications belonging to the same research
field, core documents are those publications with the highest centrality,
which is expressed by the number of citations they have obtained from other
publications in the group (Glanzel, Thijs, 2011; Glanzel, Czerwon, 1996;
Meyer et al., 2014; Mora et al., 2018, 2019; Mora, Deakin, 2019). Since core
documents are highly-cited publications, they can be considered as the most
representative literature and
are expected to form the […] cognitive nodes of the [research ﬁeld] they represent (Meyer
et al., 2014, p. 477)
The results of the analysis are discussed in the following sub-sections,
which set out current trends in research on Smart Specialisation.
10 Despite focusing on twelve years of scientific production, it is important to note that the bib-
liometric study reported in this paper was conducted by considering a short-time citation window
because all the scientific literature dealing with Smart Specialisation was published between 2011
and 2016. A comprehensive analysis of this issue and a discussion of the error rate that this condi-
tion can generate is provided by Wang (2013).
Exploring Current Trends in Scientific Research on Smart Specialisation | 403
3.1. Knowledge production
Data related to both the annual count and cumulative growth of source
documents shows that research on Smart Specialisation began in 2011 (see
Figure 1), with three publications introducing this new science-related topic.
The first is a conference paper describing the user-driven and open innovation
model promoted by TestLab, i.e. a living lab created in 2007 by the Italian
Province of Trento, in collaboration with ENoLL (European Network of
Living Labs). In light of this experience, the paper suggests that the living
lab methodology generates
a mechanism of bottom-up Smart Specialisation, whereby regional priorities can be deter-
mined by the willingness of local actors to join forces and strive for common goals (Ferrari
et al., 2011, p. 332).
The second publication is a journal article by Di Anselmo and Lo Cascio
(2011), which discusses the challenges that the recent economic crisis has
generated in Europe, highlighting the need for smarter forms of policymak-
ing able to support innovation at the regional level by deploying public
investments. According to the article, the Smart Specialisation process is a
means to fulfil this aim because it can support the establishment of new and
sustainable regional development paths that provide for «a selective use of
resources» and concentration of investments «in a narrower range of measures
which offer better returns», moving away from a deregulated provision (Di
Anselmo, Lo Cascio, 2011, p. 468). Finally, the third publication reports on
a study aimed at supporting the Smart Specialisation process in Cape Town
by explaining how this European concept can be exported to South Africa
(Lorentzen et al., 2011).
These publications initiated a scientific debate that has grown steadily
over the years, especially between 2014 and 2016, a period in which 86% of
the available literature on Smart Specialisation was published. This literature
has been mainly produced in Europe (93.0%), where universities are the
most active organisations. Their overall publication output is 69.9%, which
corresponds to about 144 of the 205 source documents, while businesses,
governments and other institutions belonging to European countries only
account for 23.1% of the publication volume. The top universities for pub-
lication output are located in Italy, which has the highest level of produc-
tion (15.4%), followed by Poland (8.9%), Spain (8.5%), United Kingdom
(7.4%), Netherlands (6.8%), Lithuania (5.2%), Latvia (4.9%) and Romania
(4.9%). In contrast, Cyprus (0.2%), Serbia (0.4%), Ukraine (0.5%), France
(0.5%), Norway (0.5%), Slovenia (0.6%), Malta (0.7%), Bulgaria (1.0%) and
Portugal (1.0%) exhibit a different pattern. With a total publication output
lower than or equal to two source documents, they have the lowest level of
involvement amongst all the European countries conducting research in the
field of Smart Specialisation (see Appendix A and Figure 2).
404 | Luca Mora, Mark Deakin, Alasdair Reid
Figure 1: Annual count and cumulative growth of source documents.
Figure 2: Level of production of European countries.
Exploring Current Trends in Scientific Research on Smart Specialisation | 405
3.2. Available workforce
Considering the period between the beginning of 2005 and the end of
2016, the scientific community conducting research on Smart Specialisation
consisted of 395 researchers from 204 organisations located in 40 differ-
ent countries. Figure 3 shows the progressive growth of this community,
in which the number of active researchers has increased annually, together
with the number of source documents. The data in Appendix A and Figure
4 suggests that these authors work mainly for European-based organisations
(90.1%), where universities have the highest share of authors (64.8%). This
data also shows that the percentage of researchers from businesses (7.6%)
and governmental institutions (11.6%) reflects the low level of production
of both sectors11.
Besides having the highest volume of output, Italy is also the country with
the highest number of active researchers (14.7%). This positive correlation
between workforce and publication output can be observed in the major-
ity of the most productive countries, where the percentage of researchers
11 To be noted is that the smaller share of researchers from businesses and governmental institu-
tions relates to their contribution to the production of scientific knowledge on Smart Specialisation,
i.e. knowledge resulting from publications which are subject to the traditional academic peer-review
process. The inclusion of grey literature in the analysis may yield different figures.
Figure 3: Annual count and cumulative growth of authors.
406 | Luca Mora, Mark Deakin, Alasdair Reid
working in the field of Smart Specialisation ranges between 3.0% and 9.1%:
Spain (9.1%); Poland (7.1%); United Kingdom (6.8%); Romania (5.1%);
Lithuania (4.6%); Latvia (3.8%); and Netherlands (3.3%). Germany, Fin-
land, Croatia and Estonia are the only entities affected by a reverse trend.
In these countries, the production of literature is lower when compared to
the most productive countries, but the workforce level is similar (see Figure
3 and Figure 4).
3.3. Influence in the scientific debate on Smart Specialisation
The share of citations that each country obtained during the period
under investigation shows that research on Smart Specialisation is mainly
driven by European countries and their universities. Together, these 30 active
countries account for about 98.8% of the 303 total citations obtained by
the source documents, and their universities have received the highest share
(82.0%). Only 16.9% of citations relate to the research activity conducted
by governmental organisations, the business sector and civic organisations
(see Appendix A and Figure 5).
In addition, a comparison of the data on both influence and publication
output yields the following key facts, which make it possible to divide the
European countries conducting research on Smart Specialisation into four
clusters (see Figure 6).
Figure 4: Workforce level of European countries.
Exploring Current Trends in Scientific Research on Smart Specialisation | 407
18 of the 30 European countries have a very limited or no influence in
the field of Smart Specialisation, and this is due to a low level of publica-
Figure 5: Influence of European countries.
Figure 6: Comparison between production and influence of European countries.
408 | Luca Mora, Mark Deakin, Alasdair Reid
Figure 7: Regional knowledge hubs and key knowledge producers.
tion output. These countries are Bulgaria, Croatia, Cyprus, Czech Republic,
Denmark, Estonia, Finland, France, Greece, Hungary, Ireland, Malta, Norway,
Portugal, Serbia, Slovakia, Slovenia and Ukraine (Cluster 1);
Despite the high level of publication output, Latvia, Lithuania, Poland
and Romania have a moderate influence (Cluster 2);
Belgium, Germany, Sweden and Switzerland (Cluster 3) are among the
most influential countries in the field of Smart Specialisation. However, they
leverage a far lower number of publications compared to Spain, Italy, Neth-
erlands and the United Kingdom (Cluster 4), which are the top countries
for both research output and influence.
The results of the analysis suggest that Belgium, Germany, Spain, Sweden,
Switzerland, Italy, Netherlands and the United Kingdom are the main regional
knowledge hubs in the field of Smart Specialisation. The eight knowledge
hubs are mapped in Figure 7, along with the key knowledge producers,
which are listed as the top 15 organisations for number of citations. It is
not surprising that most of these knowledge producers are in the regional
knowledge hubs, where research is mainly driven by universities: Politecnico
di Milano and Università Politecnica delle Marche in Italy; University of
Groningen and Utrecht University in the Netherlands; Lund University in
Exploring Current Trends in Scientific Research on Smart Specialisation | 409
Sweden; Ecole Polytechnique Federale de Lausanne in Switzerland; University
of Antwerp in Belgium; and Cardiff University in the United Kingdom. In
addition to higher education institutions, the list of key knowledge producers
includes: the non-governmental institutions Fraunhofer Institute for Systems
and Innovation Research and Orkestra – Basque Institute of Competitive-
ness, which are respectively located in Germany and Spain; the European
Commission and one of its Joint Research Centres; the Brussels’ office of
the consultancy Technopolis Group; the Institute of National Economy in
Romania; and Visionary Analytics in Lithuania.
3.4. Core literature
In order to visualize the network of citations connecting the source docu-
ments and identify the core literature on Smart Specialisation, the citation
data was processed by deploying the open software Gephi. The result of
the data processing is the network of directed and unweighted links rep-
resented in Figure 8, which was obtained using the Fruchterman-Reingold
layout algorithm (Fruchterman, Reingold, 1991). In this network, the 205
source documents are represented as nodes and the 303 edges connecting
them are the citations. Each node is assigned a dimension which is directly
proportional to the number of citations that it has received from others. In
addition, nodes are distinguished by colour: source documents with at least 1
citation are blue or grey, whereas non-cited source documents are black. The
arrows at the end of each link define the direction of the citation, making it
easy to distinguish between citing references and cited references.
An analysis of the citation pattern was conducted to define the ratio
between cited publications (58) and non-cited publications (147). It was
found that: 72% of the source documents had not yet been cited; 22% had
acquired between 1 and 7 citations; and the remaining 6% of cited references
had received at least 10 citations each, and accounted for almost 65% of
the total citations (see Figure 9). These highly-cited publications are listed
in Table 2 and can be considered as the core literature in the field of Smart
With 43 citations, McCann and Ortega-Argilés (2015) is the most cited
publication. This journal article explains the origins of the Smart Speciali-
sation concept and examines the rationale behind the policy-prioritization
logic and the place-based approach to regional development that it promotes.
This serves to highlight
the critical role of knowledge diffusion processes between sectors, activities and occupations,
and explicitly avoids automatically prioritizing high-technology sectors by taking a broader
systems perspective (McCann, Ortega-Argilés, 2015, p. 1293).
The discussion on Smart Specialisation that McCann and Ortega-Argilés
offer in this publication is expanded by way of three additional articles that
410 | Luca Mora, Mark Deakin, Alasdair Reid
Figure 8: Document citation network.
they have co-authored. These articles explore the developments relating to
regional innovation policy by reviewing the literature produced in recent
years by international development institutions such as World Bank, OECD
and the European Commission (McCann, Ortega-Argilés, 2013a, 2013b,
2014). These developments include Smart Specialisation, which is described
as «a policy prioritisation agenda for regional innovation policy» (McCann,
Ortega-Argilés, 2013a, p. 206) that results from the adaptation of the debate
on non-spatial innovation policy to the European Cohesion Policy (McCann,
Ortega-Argilés, 2013a, 2013b).
Along with Iacobucci (2014), Kroll (2015), Foray (2015) and Capello
(2014), these publications capture what is known about the concept of Smart
Specialisation. In capturing this knowledge, they also suggest that the practi-
cal design and implementation process of strategies for Smart Specialisation
Exploring Current Trends in Scientific Research on Smart Specialisation | 411
Figure 9: Distribution of source documents by number of citations.
remains at an early stage of development, and that a number of critical issues
are still unresolved. As Capello (2014, p. 5) points out:
no deﬁnitive view on the concept has so far been reached, and the challenges, strengths
and risks associated with the best design and implementation of the Smart Specialisation
strategy are still much debated.
Camagni et al. (2014) and Camagni and Capello (2013) have contributed
to the debate with two articles supporting the general philosophy behind
the Smart Specialisation concept, but criticize its direct application in
regional development policies. Like McCann and Ortega-Argilés (2015),
Camagni and Capello (2013, p. 361) suggest the Smart Specialisation ap-
proach «looks highly valuable, appropriate and a good starting point for
However, the sectoral and non-spatial logic from which it emerges
ignores the variability of regional innovation paths, [which] strongly depend on territorial
elements rooted in the local society, its history, its culture and its typical learning processes
(Camagni et al., 2014, p. 72).
According to Camagni and Capello (2013, p. 357), this calls for a new
rationale for a regionalized conception, design and delivery of innovation policies based on
a territorial taxonomy,
which their articles outline. This taxonomy is proposed to facilitate the
common approaches for similar types of regions [and] prevent [any] misallocation of public
resources and unlikely local strategies.
Table 2: Core literature
Reference Year Type Authors and affiliations N. of citations
McCann, Ortega-Argilés (2015) 2013 Journal Article McCann P., Ortega-Argiles R. (University of Groningen, Netherland) 43
Boschma (2014) 2014 Journal Article Boschma R. (Lund University, Sweden; Utrecht University, Netherland) 24
Foray (2015) 2015 Book Foray D. (Ecole Polytechnique Federale de Lausanne, Switzerland) 18
McCann, Ortega-Argilés (2014) 2014 Journal Article McCann P., Ortega-Argiles R. (University of Groningen, Netherland) 17
Camagni, Capello (2013) 2013 Journal Article Camagni R., Capello R. (Politecnico di Milano, Italy) 15
McCann, Ortega-Argilés (2013a) 2013 Journal Article McCann P., Ortega-Argiles R. (University of Groningen, Netherland) 13
Iacobucci (2014) 2014 Journal Article Iacobucci D. (Università Politecnica delle Marche, Italy) 13
Coffano, Foray (2014) 2014 Journal Article Coffano M., Foray D. (Ecole Polytechnique Federale de Lausanne, Switzerland) 12
Kroll (2015) 2015 Journal Article Kroll H. (Fraunhofer Institute for Systems and Innovation Research, Germany) 10
McCann, Ortega-Argilés (201b) 2013 Journal Article McCann P., Ortega-Argiles R. (University of Groningen, Netherland) 10
Capello (2014) 2014 Journal Article Capello R. (Politecnico di Milano, Italy) 10
Camagni et al. (2014) 2014 Journal Article Camagni R., Capello R., Lenzi C. (Politecnico di Milano, Italy) 10
Exploring Current Trends in Scientific Research on Smart Specialisation | 413
The remaining core literature: 1) focuses on the complementary relation-
ship between Smart Specialisation and Constructing Regional Advantage,
two policy concepts which have attracted much attention at the European
provides important inputs to develop a smart and comprehensive policy design that avoids
rent-seeking behaviour of vested local stakeholders but instead focuses on true economic
renewal in regions (Boschma, 2014, p. 64)
2) combines the data obtained from two questionnaire-based online surveys
and a range of qualitative interviews with policy makers to gain deeper insights
into the implementation processes of strategies for Smart Specialisation in
European regions (Kroll, 2015); and 3) explains the centrality of the entre-
preneurial discovery process that drives the bottom-up and decentralized
logic of Smart Specialisation (Coffano, Foray, 2014).
4. Discussion and conclusion
This exploratory study has evidenced current trends in research on
Smart Specialisation by means of a bibliometric analysis in which the count
of publications, authors, organisations and citations was combined with
network analysis to examine: 1) the scientific literature dealing with Smart
Specialisation that was published during the first decade of research, cor-
responding to the period between 2005 and 2016; and 2) the community of
researchers who produced such a literature.
The results of the counting process show that research on Smart Spe-
cialisation has increased steadily since the publication of the K4G Expert
Group’s policy recommendations, leading to the progressive development
of a new and emerging research field in which the numbers of authors and
scientific publications have grown exponentially. The first scientific publica-
tions dealing with Smart Specialisation date back to 2011, but most of the
literature belonging to this research field was published between 2014 and
2016. This three-year period accounts for about 86% of the 205 publications
produced during the first decade of research. The community of researchers
working in this field has expanded following a similar growth pattern: the 9
authors publishing in 2011 became 65 in 2013 and 395 at the end of 2016.
These insights reveal that research on Smart Specialisation began im-
mediately after the European Commission identified the application of the
Smart Specialisation approach as one of the main actions to achieve the
objectives of the Europe 2020 strategy. This directive was issued in October
2010, with the publication of the Communication on Regional Policy Con-
tributing to Smart Growth in Europe 2020 (European Commission, 2010b)
and its accompanying document (European Commission, 2010c). In addi-
tion, these two documents: 1) discuss the rationale behind the European
Commission’s decision to introduce the Smart Specialisation approach and
414 | Luca Mora, Mark Deakin, Alasdair Reid
the expected impact; 2) explain how this approach should be understood by
national and regional governments as strategic statements able to maximise
the impact of Regional Policy in combination with other EU policies; and 3)
inform national and regional governments about the European Commission’s
intention to launch a Smart Specialisation Platform able to advise on the
design and implementation of research and innovation strategies for Smart
Specialisation (European Commission, 2010b, 2010c). The platform is cur-
rently active and coordinated by the European Commission’s Joint Research
Centre located in Seville12.
The production of the policy briefs that introduced the concept of
Smart Specialisation in 2005 and the distribution of the first peer-reviewed
publications in 2011 can be considered two milestones in the development
of this research field. The growth in the number of active researchers and
publications characterising the period between 2014 and 2016 represents
the third one, and it was anticipated by significant developments in the
European Union’s legislative framework. A new Regulation was formally
endorsed by the Council of the European Union in December 2013, which
laid down a set of common rules aimed at governing the European Structural
and Investment Funds during the period 2014-2020 (European Commis-
sion, 2014). This new legislative framework provides a definition of Smart
Specialisation strategies as:
the national or regional innovation strategies which set priorities in order to build competitive
advantage by developing and matching research and innovation own strengths to business
needs in order to address emerging opportunities and market developments in a coherent
manner, while avoiding duplication and fragmentation of efforts.
In addition, it introduces the «existence of a national or regional Smart
Specialisation strategy in line with the National Reform Program» as a the-
matic ex ante conditionality with which all the Member States must comply
in order for the European Commission to provide them with funds for
research and technological development (European Union, 2013).
This new legislative framework has triggered the scientific debate on
Smart Specialisation, which is now led by European countries. The results
of this study show that 93% of the literature on Smart Specialisation is pro-
duced in Europe, where universities are the most active organisations, with
an overall publication output of 70%. European countries and their higher
education institutions also account for the main share of available workforce
and citations. Around 90% of the authors work for European organisations
and their publications have obtained 99% of the total citations. With 65%
of the authors and 82% of all citations, universities have the highest share
of both these measures.
12 The European Commission’s Smart Specialisation Platform can be accessed using the following
Exploring Current Trends in Scientific Research on Smart Specialisation | 415
Europe is also where the regional knowledge hubs on Smart Specialisa-
tion are located. These hubs include: Belgium, Germany, Spain, Sweden,
Switzerland, Italy, Netherlands and the United Kingdom. Currently, 13 of
the 15 top organisations for number of citations are based in the regional
knowledge hubs, where research is mainly driven by universities: Univer-
sity of Groningen; Ecole Polytechnique Federale de Lausanne; Politecnico
di Milano; Lund University; Università Politecnica delle Marche; Cardiff
University; Utrecht University; and University of Antwerp. The other key
knowledge producers belonging to the regional knowledge hubs are: the
non-governmental institutions Orkestra – Basque Institute of Competitive-
ness and the Fraunhofer Institute for Systems and Innovation Research;
the European Commission and its Joint Research Centre in Seville; and the
consultancy Technopolis Group.
Adam D. (2002), The Counting House. Nature, 415, 6873: 726-729. DOI:
Adams R. J., Smart P., Huff A. S. (2017), Shades of Grey: Guidelines for Working
with the Grey Literature in Systematic Reviews for Management and Organi-
zational Studies. International Journal of Management Reviews, 19, 4: 432-454.
Bakkalbasi N., Bauer K., Glover J., Wang L. (2006), Three Options for Citation
Tracking: Google Scholar, Scopus and Web of Science. Biomedical Digital
Libraries, 3, 7: 1-8. DOI: 10.1186/1742-5581-3-7.
Bar-Ilan J. (2008), Which H-Index? – A Comparison of WoS, Scopus and Google
Scholar. Scientometrics, 74, 2: 257-271. DOI: 10.1007/s11192-008-0216-y.
Boschma R. (2014), Constructing Regional Advantage and Smart Specialisation:
Comparison of Two European Policy Concepts. Scienze Regionali – Italian
Journal of Regional Science, 13, 1: 51-68. DOI: 10.3280/SCRE2014-001004.
Camagni R., Capello R. (2013), Regional Innovation Patterns and the EU Regional
Policy Reform: Toward Smart Innovation Policies. Growth and Change, 44, 2:
355-389. DOI: 10.1111/grow.12012.
Camagni R., Capello R., Lenzi C. (2014), A Territorial Taxonomy of Innovative
Regions and the European Regional Policy Reform: Smart Innovation Policies.
Scienze Regionali – Italian Journal of Regional Science, 13, 1: 69-106. DOI:
Capello R. (2014), Smart Specialisation Strategy and the New EU Cohesion Policy
Reform: Introductory Remarks. Scienze Regionali – Italian Journal of Regional
Science, 1: 5-13. DOI: 10.3280/SCRE2014-001001.
Coffano M., Foray D. (2014), The Centrality of Entrepreneurial Discovery in Building
and Implementing a Smart Specialisation Strategy. Scienze Regionali – Italian
Journal of Regional Science, 13, 1: 33-50. DOI: 10.3280/SCRE2014-001003.
Colledge L., Verlinde R. (2014), SciVal Metrics Guidebook. Elsevier. Available at:
guidebook-v1_01-february2014.pdf. Accessed 15 January 2017.
416 | Luca Mora, Mark Deakin, Alasdair Reid
David P. A., Metcalfe S. (2007), Universities Must Contribute to Enhancing Euro-
pe’s Innovative Performance. Knowledge Economists’ Policy Brief, 2. Available
mists_policy_brief2_final.pdf. Accessed 28 April 2017.
Deakin M., Mora L., Reid A. (2017), Smart Specialisation Strategies in the Post-
linear Era on Research and Innovation. In: Ketikidis P
., Solomon A. (eds.),
10th International Conference for Entrepreneurship, Innovation, and Regional
Development (ICEIRD 2017): University-Industry Links: Coproducing Knowledge,
Innovation & Growth. Conference Proceedings, Thessaloniki, 31 August-01
September 2017. Sheffield: The University of Sheffield and SEERC, 529-540.
Deakin M., Mora L., Reid A. (2018), The Research and Innovation of Smart
Specialisation Strategies: The Transition From the Triple to Quadruple Helix.
In: Bozina Beros M., Recker N., Kozina M. (eds.), 27th International Scientific
Conference on Economic and Social Development: Book of Proceedings. Rome,
1-2 March 2018. Varazdin: Varazdin Development and Entrepreneurship
De Groote S. L., Raszewski R. (2012), Coverage of Google Scholar, Scopus, and
Web of Science: A Case Study of the H-index in Nursing. Nursing Outlook,
60, 6: 391-400. DOI: 10.1016/j.outlook.2012.04.007.
Di Anselmo A., Lo Cascio L. (2011), Towards a New Era for Regional Development:
Investing in Leadership. Local Economy: The Journal of the Local Economy
Policy Unit, 26, 6-7: 467-472. DOI: 10.1177/0269094211419446.
European Commission (2010a), Communication from the Commission. Europe
2020: A Strategy for Smart, Sustainable and Inclusive Growth. COM(2010)
2020. Brussels: European Commission. Available at: http://eur-lex.europa.
2 February 2014.
European Commission (2010b), Communication From the Commission to the Euro-
pean Parliament, the Council, the European Economic and Social Committee and
the Committee of the Regions: Regional Policy Contributing to Smart Growth in
Europe 2020. COM(2010) 553 final. Brussels: European Commission. Available
smart_growth/comm2010_553_en.pdf. Accessed 2 February 2014.
European Commission (2010c), Commission Staff Working Document: Document
Accompanying the Commission Communication on Regional Policy Contributing
to Smart Growth in Europe 2020. SEC(2010) 1183. Brussels: European Com-
mission. Available at: http://ec.europa.eu/regional_policy/sources/docoffic/
official/communic/smart_growth/annex_comm2010_553.pdf. Accessed 2
European Commission (2014), National/Regional Innovation Strategies for Smart
Specialisation (RIS3). Brussels: European Commission. Available at: http://
lisation_en.pdf. Accessed 2 February 2014.
European Commission-Directorate-General for Research (2008), Knowledge for
Growth: European Issues and Policy Challenges. Luxembourg: Office for Official
Publications of the European Communities.
Exploring Current Trends in Scientific Research on Smart Specialisation | 417
European Council (2000), Lisbon European Council 23 and 24 March 2000: Pre-
sidency Conclusions. European Parliament. Available at: http://www.europarl.
europa.eu/summits/lis1_en.htm#. Accessed 20 April 2017.
European Union (2013), Regulation (EU) No 1303/2013 of the European Parliament
and of the Council of 17 December 2013 Laying Down Common Provisions
on the European Regional Development Fund, the European Social Fund, the
Cohesion Fund, the European Agricultural Fund for Rural Development and the
European Maritime and Fisheries Fund and Laying Down General Provisions
on the European Regional Development Fund, the European Social Fund, the
Cohesion Fund and the European Maritime and Fisheries Fund and Repealing
Council Regulation (EC) No 1083/2006. Regulation. Brussels: European Union.
Available at: http://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CEL
EX:32013R1303&from=en. Accessed 2 February 2014.
Ferrari V., Mion L., Molinari F. (2011), Innovating ICT Innovation: Trentino
As a Lab. In: Estevez E., Janssen M. (eds.), ICEGOV 2011 5th International
Conference on Theory and Practice of Electronic Governance. Tallinn, 26-29
September 2011. New York City, NY: ACM, 329-332.
Foray D. (2006), Globalisation of R&D: Linking Better the European Economy to
«foreign» Sources of Knowledge and Making EU a More Attractive Place for
R&D Investment. Report. Available at: http://ec.europa.eu/invest-in-research/
pdf/download_en/foray_report.pdf. Accessed 28 April 2017.
Foray D. (2015), Smart Specialisation: Opportunities and Challenges for Regional
Innovation Policy. Abingdon: Routledge.
Foray D., David P. A., Hall B. (2009), Smart Specialisation – The Concept.
Knowledge Economists’ Policy Brief, 9. Available at: http://ec.europa.eu/
invest-in-research/pdf/download_en/kfg_policy_brief_no9.pdf. Accessed 3
Foray D., Van Ark B. (2007), Smart Specialisation in a Truly Integrated Research
Area Is the Key to Attracting More R&D to Europe. Knowledge Economists
Policy Brief, 1, October. Available at: http://ec.europa.eu/invest-in-research/
pdf/download_en/policy_brief1.pdf. Accessed 28 April 2017.
Fruchterman T. M. J., Reingold E. M. (1991), Graph Drawing by Force-Directed
Placement. Software-practice and Experience, 21, 11: 1129-1164.
Giannitsis T., Kager M. (2009), Technology and Specialization: Dilemmas, Op-
tions and Risks? Knowledge Economists’ Policy Brief, 8. Available at: http://
sed 28 April 2017.
., Czerwon H. J. (1996), A New Methodological Approach to Biblio-
graphic Coupling and Its Application to the National, Regional and Institutional
Level. Scientometrics, 37, 2: 195-221.
Glanzel W., Thijs B. (2011), Using «core Documents» for the Representation of
Clusters and Topics. Scientometrics, 88, 1: 297-309. DOI: 10.1007/s11192-
Hall B. H., Mairesse J. (2009), Measuring Corporate R&D Returns. Knowledge
Economists’ Policy Brief, 6. Available at: http://ec.europa.eu/invest-in-research/
pdf/download_en/kfg_report_no6.pdf. Accessed 28 April 2017.
418 | Luca Mora, Mark Deakin, Alasdair Reid
Iacobucci D. (2014), Designing and Implementing a Smart Specialisation Strategy
at Regional Level: Some Open Questions. Scienze Regionali – Italian Journal
of Regional Science, 13, 1: 107-126. DOI: 10.3280/SCRE2014-001006.
Jacobsen T., Punzalan R. L., Hedstrom M. L. (2013), Invoking Collective Memory:
Mapping the Emergence of a Concept in Archival Science. Archivial Science,
13, 2-3: 217-251. DOI: 10.1007/s10502-013-9199-4.
Komninos N., Kakderi C., Panori A., Garcia E., Fellnhofer K., Reid A., Cvijanović
V., Roman M., Deakin M., Mora L., Reid A. (2018a), Intelligence and Co-Cre-
ation in Smart Specialisation Strategies: Towards the Next Stage of RIS3. White
Paper. Available at: https://www.onlines3.eu/results. Accessed 10 August 2018.
Komninos N., Mora L. (2018), Exploring the Big Picture of Smart City Rese-
arch. Scienze Regionali – Italian Journal of Regional Science, 1: 15-38. DOI:
Komninos N., Panori A., Kakderi C., Reid A., Cvijanović V., Roman M., Dea-
kin M., Mora L., Tiemann M., Badii L. (2018b), Online S3 Mechanism for
Knowledge-based Policy Advice. Available at: https://www.onlines3.eu/results.
Accessed 10 October 2018.
Knowledge for Growth Expert Group (2007), What Policies Are Needed to Over-
come the EU’s R&D Deficit? Policy Debate, 1. Available at: http://ec.europa.eu/
invest-in-research/pdf/download_en/policy_debate.pdf. Accessed 28 April 2017.
Knowledge for Growth Expert Group (2009), Knowledge for Growth: Prospects
for Science, Technology and Innovation. Selected Papers from Research Com-
missioner Janez Potočnik’s Expert Group. Available at: http://ec.europa.eu/
invest-in-research/pdf/download_en/policy_debate.pdf. Accessed 28 April 2017.
Kroll H. (2015), Efforts to Implement Smart Specialization in Practice – Leading
Unlike Horses to the Water. European Planning Studies, 23, 10: 2079-2098.
Levine-Clark M., Gil E. L. (2008), A Comparative Citation Analysis of Web of
Science, Scopus, and Google Scholar. Journal of Business & Finance Libra-
rianship, 14, 1: 32-46. DOI: 10.1080/08963560802176348.
Lorentzen J., Muller L., Manamela A., Gastrow M. (2011), Smart Specialisation
and Global Competitiveness: Multinational Enterprises and Location-Specific
Assets in Cape Town. African Journal of Business Management, 5, 12: 4782-4791.
Marimon R., Carvalho M. (2008), An Open, Integrated, and Competitive European
Research Area Requires Policy and Institutional Reforms, and Better Gover-
nance and Coordination of S&T Policies. Knowledge Economists Policy Brief,
3, April. Available at: http://ec.europa.eu/invest-in-research/pdf/download_en/
kfgbriefno31142008080416.pdf. Accessed 28 April 2017.
McCann P., Ortega-Argilés R. (2013a), Modern Regional Innovation Policy. Cam-
bridge Journal of Regions, Economy and Society, 6, 2: 187-216. DOI: 10.1093/
., Ortega-Argilés R. (2013b), Transforming European Regional Policy: A
Results-driven Agenda and Smart Specialization. Oxford Review of Economic
Policy, 29, 2: 405-431. DOI: 10.1093/oxrep/grt021.
McCann P., Ortega-Argilés R. (2014), The Role of the Smart Specialisation Agen-
da in a Reformed EU Cohesion Policy. Scienze Regionali – Italian Journal of
Regional Science, 13, 1: 15-32. DOI: 10.3280/SCRE2014-001002.
Exploring Current Trends in Scientific Research on Smart Specialisation | 419
McCann P., Ortega-Argilés R. (2015), Smart Specialization, Regional Growth and
Applications to European Union Cohesion Policy. Regional Studies, 49, 8:
1291-1302. DOI: 10.1080/00343404.2013.799769.
Meyer M., Libaers D., Thijs B., Grant K., Glanzel W., Debackere K. (2014), Origin
and Emergence of Entrepreneurship as a Research Field. Scientometrics, 98,
1: 473-485. DOI: 10.1007/s11192-013-1021-9.
Mongeon P., Paul-Hus A. (2016), The Journal Coverage of Web of Science and
Scopus: A Comparative Analysis. Scientometrics, 106, 1: 213-228. DOI: 10.1007/
Mora L., Bolici R., Deakin M. (2017), The First Two Decades of Smart-City
Research: A Bibliometric Analysis. Journal of Urban Technology, 24, 1: 3-27.
Mora L. Deakin M. (2019), Untangling Smart Cities: From Utopian Dreams to
Innovation Systems for a Technology-Enabled Urban Sustainability. Amsterdam:
Mora L., Deakin M., Reid A. (2018), Smart City Development Paths: Insights from
the First Two Decades of Research. In: Bisello A., Vettorato D., Laconte P.,
Costa S. (eds.), Smart and Sustainable Planning for Cities and Region: Results
of SSPCR 2017. Cham: Springer, 403-427.
Mora L., Deakin M., Reid A. (2019), Combining Co-Citation Clustering and
Text-Based Analysis to Reveal the Main Development Paths of Smart Cit-
ies. Technological Forecasting and Social Change. 142: 56-69. DOI: 10.1016/j.
O’Sullivan M. (2007), The EU’s R&D Deficit & Innovation Policy. Report. Available
port0207.pdf. Accessed 28 April 2017.
Panori A., Angelidou M., Mora L., Reid A., Sefertzi E. (2018), Online Platforms
for Smart Specialisation Strategies and Smart Growth. In Regions at a Turning
Point: Post-Digital Communities, New Regionalism and Re-Nationalisation –
Sustainable Development Implications. Athens, 4-5 March 2018. Kallithea:
Harokopio University, 96-102.
Rodriguez R., Warmerdam J., Triomphe C. E., Gács J., Kwiatiewicz A., Erhel
C., Voss and Havess E., Calvo J., Pond R. (2010), The Lisbon Strategy 2000-
2010: An Analysis and Evaluation of the Methods Used and Results Achieved.
Report. European Parliament. Available at: http://www.europarl.europa.eu/
EN.pdf. Accessed 30 April 2017.
Schopfel J. (2010), Towards a Prague Definition of Grey Literature. In: Farace
D. J., Fratzen J. (eds.), Twelfth International Conference on Grey Literature:
Transparency in Grey Literature. Grey Tech Approaches to High Tech Issues.
Prague, 6-7 December 2010. Amsterdam: TextRelease, 11-26.
Shiau W., Dwivedi Y. K. (2013), Citation and Co-Citation Analysis to Identify Core
and Emerging Knowledge in Electronic Commerce Research. Scientometrics,
94, 3: 1317-1337. DOI: 10.1007/s11192-012-0807-5.
Small H. G., Crane D. (1979), Specialties and Disciplines in Science and Social
Science: An Examination of Their Structure Using Citation Indexes. Sciento-
metrics, 1, 5-6: 445-461.
420 | Luca Mora, Mark Deakin, Alasdair Reid
Veugelers R., Mrak M. (2009), The Knowledge Economy and Catching-Up Member
States of the European Union. Knowledge Economists’ Policy Brief, 5. Available
pdf. Accessed 28 April 2017.
Wang J. (2013), Citation Time Window Choice for Research Impact Evaluation.
Scientometrics, 94, 3: 851-872. DOI: 10.1007/s11192-012-0775-9.
Zhao Y., Cui L., Yang H. (2009), Evaluating Reliability of Co-Citation Clustering
Analysis in Representing the Research History of Subject. Scientometrics, 80,
1: 91-102. DOI: 10.1007/s11192-008-2056-1.
Table A: Publications, organisations, authors and citations by country and organization type. U: University; B: Business; G: Government; O: Other
Country % Authors % Organisations % Publications % Citations
U B G O Tot. U B G O Tot. U B G O Tot. U B G O Tot.
Europe 64.8 7.6 11.6 6.1 90.1 59.3 8.8 12.3 6.9 87.3 69.9 5.3 10.9 6.9 93.0 82.0 3.5 6.2 7.2 98.8
Belgium 0.5 0.8 0.8 0.0 2.0 0.5 1.0 1.0 0.0 2.5 0.5 0.7 0.9 0.0 2.1 1.3 1.7 1.5 0.0 4.5
Bulgaria 1.0 0.0 0.0 0.0 1.0 1.5 0.0 0.0 0.0 1.5 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0
Croatia 0.3 0.5 1.8 0.5 3.0 0.5 0.5 2.5 0.5 3.9 0.5 0.5 1.1 0.3 2.4 0.0 0.0 0.0 0.0 0.0
Cyprus 0.3 0.0 0.0 0.0 0.3 0.5 0.0 0.0 0.0 0.5 0.2 0.0 0.0 0.0 0.2 0.6 0.0 0.0 0.0 0.6
Czech Republic 1.8 0.0 0.0 0.0 1.8 1.5 0.0 0.0 0.0 1.5 1.4 0.0 0.0 0.0 1.4 0.0 0.0 0.0 0.0 0.0
Denmark 1.0 0.0 0.0 0.0 1.0 1.5 0.0 0.0 0.0 1.5 1.1 0.0 0.0 0.0 1.1 0.0 0.0 0.0 0.0 0.0
Estonia 2.8 0.0 0.0 0.3 3.0 1.0 0.0 0.0 0.5 1.5 2.2 0.0 0.0 0.4 2.6 0.8 0.0 0.0 0.2 1.0
Finland 4.1 0.3 0.5 0.0 4.8 3.4 0.5 1.0 0.0 4.9 2.6 0.1 0.3 0.0 3.0 0.6 0.0 0.0 0.0 0.6
France 0.5 0.0 0.0 0.0 0.5 1.0 0.0 0.0 0.0 1.0 0.5 0.0 0.0 0.0 0.5 0.0 0.0 0.0 0.0 0.0
Germany 1.5 1.3 0.0 0.5 3.3 2.0 1.5 0.0 0.5 3.9 0.9 0.6 0.0 1.2 2.7 0.0 0.3 0.0 4.0 4.3
Greece 1.3 0.3 0.3 0.3 2.0 1.5 0.5 0.5 0.5 2.9 1.2 0.2 0.2 0.5 2.2 0.6 0.0 0.0 0.0 0.6
Hungary 1.3 0.0 0.3 0.0 1.5 1.5 0.0 0.5 0.0 2.0 1.1 0.0 0.2 0.0 1.3 0.0 0.0 0.0 0.0 0.0
Ireland 1.0 0.0 0.3 0.0 1.3 0.5 0.0 0.5 0.0 1.0 1.0 0.0 0.5 0.0 1.5 0.0 0.0 0.0 0.0 0.0
Italy 11.1 1.8 1.5 0.3 14.7 9.3 1.5 1.5 0.5 12.7 12.0 1.3 2.0 0.2 15.4 18.7 0.0 0.7 0.0 19.4
Latvia 3.3 0.0 0.0 0.5 3.8 2.5 0.0 0.0 0.5 2.9 4.7 0.0 0.0 0.2 4.9 0.3 0.0 0.0 0.0 0.3
Lithuania 3.0 0.8 0.3 0.5 4.6 1.0 1.0 0.5 0.5 2.9 3.3 0.7 0.7 0.5 5.2 0.3 1.3 0.6 0.0 2.2
Malta 0.3 0.0 1.0 0.0 1.3 0.5 0.0 1.0 0.0 1.5 0.2 0.0 0.5 0.0 0.7 0.0 0.0 0.8 0.0 0.8
Netherlands 2.5 0.0 0.3 0.5 3.3 2.5 0.0 0.5 1.0 3.9 6.2 0.0 0.2 0.4 6.8 33.1 0.0 0.7 0.1 33.9
Norway 0.3 0.0 0.0 0.0 0.3 0.5 0.0 0.0 0.0 0.5 0.5 0.0 0.0 0.0 0.5 0.3 0.0 0.0 0.0 0.3
Poland 5.1 0.3 1.5 0.3 7.1 3.4 0.5 1.5 0.5 5.9 7.4 0.2 1.1 0.2 8.9 1.2 0.0 0.0 0.0 1.2
Portugal 1.0 0.0 0.0 0.3 1.3 1.0 0.0 0.0 0.5 1.5 0.8 0.0 0.0 0.2 1.0 0.0 0.0 0.0 0.0 0.0
Romania 4.6 0.0 0.5 0.0 5.1 4.4 0.0 1.0 0.0 5.4 3.9 0.0 1.0 0.0 4.9 0.0 0.0 1.0 0.0 1.0
Serbia 0.8 0.0 0.0 0.0 0.8 0.5 0.0 0.0 0.0 0.5 0.4 0.0 0.0 0.0 0.4 0.0 0.0 0.0 0.0 0.0
Slovakia 2.5 0.0 0.0 0.0 2.5 2.0 0.0 0.0 0.0 2.0 2.0 0.0 0.0 0.0 2.0 0.0 0.0 0.0 0.0 0.0
Slovenia 1.3 0.0 0.0 0.0 1.3 1.0 0.0 0.0 0.0 1.0 0.6 0.0 0.0 0.0 0.6 0.0 0.0 0.0 0.0 0.0
Spain 3.3 1.0 2.8 2.0 9.1 3.4 1.0 0.5 1.0 5.9 3.1 0.5 2.2 2.7 8.5 0.7 0.0 1.0 3.0 4.6
Sweden 1.8 0.0 0.0 0.0 1.8 1.0 0.0 0.0 0.0 1.0 1.7 0.0 0.0 0.0 1.7 8.3 0.0 0.0 0.0 8.3
Switzerland 0.5 0.0 0.0 0.0 0.5 0.5 0.0 0.0 0.0 0.5 2.0 0.0 0.0 0.0 2.0 12.2 0.0 0.0 0.0 12.2
Ukraine 0.5 0.0 0.0 0.0 0.5 0.5 0.0 0.0 0.0 0.5 0.5 0.0 0.0 0.0 0.5 0.0 0.0 0.0 0.0 0.0
United Kingdom 5.8 0.8 0.0 0.3 6.8 8.8 1.0 0.0 0.5 10.3 6.8 0.4 0.0 0.2 7.4 3.1 0.2 0.0 0.0 3.3
Other 7.1 0.0 2.3 0.5 9.9 9.8 0.0 2.0 1.0 12.7 5.3 0.0 1.5 0.2 7.0 1.2 0.0 0.0 0.0 1.2
Australia 2.5 0.0 0.3 0.0 2.8 2.5 0.0 0.5 0.0 2.9 1.1 0.0 0.2 0.0 1.3 0.0 0.0 0.0 0.0 0.0
Canada 0.5 0.0 0.3 0.5 1.3 1.0 0.0 0.5 1.0 2.5 0.2 0.0 0.2 0.2 0.7 0.0 0.0 0.0 0.0 0.0
China 0.3 0.0 0.0 0.0 0.3 0.5 0.0 0.0 0.0 0.5 0.2 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.0
Israel 0.3 0.0 0.0 0.0 0.3 0.5 0.0 0.0 0.0 0.5 0.5 0.0 0.0 0.0 0.5 0.0 0.0 0.0 0.0 0.0
Kazakhstan 0.0 0.0 0.8 0.0 0.8 0.0 0.0 0.5 0.0 0.5 0.0 0.0 0.5 0.0 0.5 0.0 0.0 0.0 0.0 0.0
Mexico 0.5 0.0 0.0 0.0 0.5 0.5 0.0 0.0 0.0 0.5 0.3 0.0 0.0 0.0 0.3 0.0 0.0 0.0 0.0 0.0
Russia 1.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 1.0 0.8 0.0 0.0 0.0 0.8 0.2 0.0 0.0 0.0 0.2
South Africa 0.0 0.0 1.0 0.0 1.0 0.0 0.0 0.5 0.0 0.5 0.0 0.0 0.5 0.0 0.5 0.0 0.0 0.0 0.0 0.0
United States 2.0 0.0 0.0 0.0 2.0 3.9 0.0 0.0 0.0 3.9 2.2 0.0 0.0 0.0 2.2 0.9 0.0 0.0 0.0 0.9
Total 71.9 7.6 13.9 6.6 100.0 69.1 8.8 14.2 7.8 100.0 75.2 5.3 12.4 7.1 100.0 83.1 3.5 6.2 7.2 100.0
Table A: Continue
Country % Authors % Organisations % Publications % Citations
U B G O Tot. U B G O Tot. U B G O Tot. U B G O Tot.