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This paper describes current trends in scientific research on Smart Specialisation 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 influence 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 Specialisation.
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Exploring Current Trends in Scientific
Research on Smart Specialisation
Luca Mora, Mark Deakin, Alasdair Reid
Scienze Regionali, vol. 18, 3/2019, pp. 397-422
ISSN 1720-3929
© 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
Specialisation.
Keywords: smart specialisation, research trends, core literature, knowledge producers.
JEL classification: O31, O33, R11, R58.
1. Introduction
In March 2000, the European Council set a new strategic goal: to make
Europe
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)
because its
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
European-based
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
this community?
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
community?
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.
2. Methodology
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
website: https://www.elsevier.com/solutions/scival.
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
documents.
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)
3. Results
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
Specialisation.
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
further reflections».
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
development of
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
level, and
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
link: http://s3platform.jrc.ec.europa.eu.
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.
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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
Appendix A
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.
... Considering the SS and RIS literature, in general, after the publication of the first policy briefs, these concepts started to move out from the grey literature (i.e. published without academic peer-review process) and enter the scientific publishing system, opening up a new research field (Mora et al., 2019). The dynamically growing number of publications in this field tend to be very centred on either the process of designing RIS and SS or on their implementation (Lopes et al., 2019), including identification of weaknesses and emerging bottlenecks in these processes and possible solutions to overcome such problems (Capello and Kroll, 2016). ...
... There is a paucity of research presenting the results of bibliometric analysis in the field of the SS and RIS literature. In addition, the existing studies are focused on selected issues, e.g. productivity of publications, authors, organisations and citations (Mora et. al, 2019), co-citation analysis (Fellnhofer, 2018) or they are based on very limited number of publications included in the analysis (Lopes et al., 2019). Moreover, the timespan of the latest of these studies was limited up to 2016. This undoubtedly needs expansion and updating due to the significant increase in the number of the SS and RIS publi ...
... When the title and abstract were not sufficiently clear, an attempt was made to access the whole text of the publication to read. In addition, taking into account that the data extracted from scientific databases contained errors (Mora, 2019), the collected data was checked for accuracy and, if necessary, changed in relation to information obtained from the full texts of source documents or information on the publisher's website. Finally, 612 records were selected for the detailed bibliometric analysis. ...
Article
Full-text available
Purpose: The purpose of the article was to determine and map the field of smart specialisation (SS) and regional innovation strategy (RIS) literature. Design/Methodology/Approach: The longitudinal bibliometric analysis of the SS and RIS literature based on extensive examination of publications indexed in the Scopus database was conducted. The timespan of the analysis covered the years 1991-2020. The quantity, quality and structural bibliometric indicators were applied. Using the VOSviewer software tool the network analyses were performed and major clusters of the SS and RIS research were determined. Findings: The conducted analysis made it possible to indicate the most productive authors, sources, organisations and countries in the analysed scientific field. The most popular research topics and subject areas, the most influential research channels and impact from authors, sources, countries in the SS and RIS literature were indicated. Moreover, it was recognised how the SS and RIS publications are clustered. Practical Implications: Determination of sources with the highest productivity and citations can be used by potential authors of publications to adopt an appropriate publication strategy. The information about the most active countries and organisations and the most influential authors may constitute the valuable basis for establishing future collaboration. The analysis results can also be useful for decision-makers in regions by indicating the most influential publications in terms of the SS and RIS development and implementation. Originality/Value: There is a paucity of research presenting the bibliometric analysis of the SS and RIS literature. This article comprises an up-to-date comprehensive analysis of this domain and enriches the understanding of its existing patterns and trends.
... The present review focuses on results whose relevance may be general and, therefore, on a selection of recent academic papers and of reports produced for the European Commission. It has to be considered that, as shown by Mora et al. (2019), the number of academic papers related to Smart Specialisation is exponentially increasing, even if the literature continues to cluster around a few seminal and defining contributions (Capello & Kroll, 2016;Foray, 2015;Iacobucci, 2014;McCann & Ortega-Argilés, 2015). ...
Technical Report
Full-text available
The objective of this report is to provide an account of how and to what extent the Smart Specialisation approach to regional innovation policy has been implemented in practice. The analysis explores how policy measures implemented under the Thematic Objective 1 “Strengthening research, technological development and innovation” of national and regional Operational Programmes, co-financed by the European Regional Development Fund, have incorporated key Smart Specialisation principles during the 2014-2020 programming period. We identify three main design principles of Smart Specialisation and translate them into three research hypotheses characterized in ways that can be tested empirically. We find that the Smart Specialisation strategies under scrutiny mostly apply a limited portfolio of traditional, supply-side instruments. All things considered, there is limited evidence of the implementation of a truly selective intervention logic aimed to support in a dedicated way different investment priorities. We observe quite pervasive support to the establishment of a critical mass of individual and collaborative entrepreneurial initiatives in all the Smart Specialisation areas, while support to the formation and strengthening of stakeholder communities is only present in a very few territories. We find positive although not widespread evidence of the introduction of novel elements in the design of some instruments; this points to a tentative break with tradition and path dependency which is in line with the spirit of Smart Specialisation. Policy implications for the future development and evolution of European regional innovation policy are derived.
... Up to now, the literature about S3 has devoted its attention to discussing the rationales behind this strategy and how the process was implemented by EU regions (Fellnhofer, 2018;Hassink & Gong, 2019;Mora et al., 2019;Radosevic, 2017). However, we have little evidence about how much the actual allocation of funds complied with the criteria required (or better, suggested in the guidelines) in the design and the implementation of S3 (Foray et al., 2012). ...
Article
Full-text available
The aim of this paper is to evaluate to what extent the implementation of Smart Specialisation Strategy (S3) has changed the allocation of structural funds of Italian regions in the programming period 2014-2020. Given the novelties introduced by this policy, we expect an increase in sectoral and technological concentration of funds, a higher share assigned to research and technological development and a stronger involvement of universities and research centres in the projects funded by regional authorities. In the empirical analysis, we exploit OpenCoesione, an original database that tracks all the projects funded with EU Cohesion Funds in Italy. We compare the characteristics of the projects managed by regional authorities in two consecutive programming periods, namely the one following and the one preceding S3 policy and implementation. Results show that changes between the two programming periods are modest and heterogeneous between regions. Overall, there is no strong evidence of any substantial change in how regions have allocated structural funds.
... The monitoring of RIS3 performance was not tackled in detail by previous literature. Mora et. al. (2019) identified current scientific trends in research on smart specialisation, but did not indicate any increasing numbers of scientific work on monitoring activities, despite the fact that monitoring became more relevant at the end of current funding period. Gianelle & Kleibring (2015) arrange monitoring activities in the overall implementa ...
Article
Full-text available
Smart Specialisation is dedicated to be a key driving force for entrepreneurial discovery and innovation in the European innovation policy paradigm in line with the European Strategy 2020 and the funding period 2014-2020. At the current stage, all EU NUTS-2 regions are monitoring their individually developed Regional Innovation Strategies on Smart Specialisation (RIS3) including monitoring systems that are needed to adjust upcoming future RIS3 strategies in the new funding periods. Despite the thematic topicality, the procedure of RIS3 evaluation and monitoring lacks a sound supra-regional approach when it comes to RIS3 implementation performance governance and institutional arrangements across all European regions. In fact, the blurring of RIS3 monitoring can be traced back to the policy nature that monitoring systems are set up, implemented and evaluated on individual regional and or national basis including a set of regionally tailored regional and national indicators. With regard to the policy challenges and research gaps of developing, and, later, using a joint macro-regional systemic institutional approach towards RIS3 implementation and monitoring, this paper provides a conceptual model for RIS3 performance, evaluation and monitoring governance based on case study analysis, best practices from RIS3 research and policy stakeholders' interviews. It is intended to serve as a comprehensive and comparative governance model on regional, national and European level, which fosters the institutional thickness and institutional multi-level horizontal cooperation among institutions involved in RIS3 performance and monitoring implementation. Within the empirical narrative, 10 NUTS-2 regions within the INTERREG Central Europe Programme area and in the frame of the "SMART_watch" project were subject to the analysis pertaining to their strategy design, priority axes and monitoring indicators. As a result, the so-called Transnational RIS3 Observatory Model was designed, which yields conceptual linkages to theoretical concepts using cluster theories as well as builds upon practical policy-driven approaches mushrooming in the innovation policy paradigm of the European Union. Furthermore, recommendations to foster the RIS3 policy implementation in the upcoming funding period are introduced in line with the setup of the observatory structure and its institutional embeddedness.
... Mora et. al. [6] identified current scientific trends in research on smart specialisation, but did not indicate any increasing numbers of scientific work on monitoring activities, despite the fact that monitoring became more relevant at the end of current funding period. However, existing research papers in the field of smart specialization monitoring mainly focus on fostering the systems for a certain region. ...
Conference Paper
Smart Specialisation approach is regarded as one of the key pillars in the funding period 2014–2020 of the European Union in order to enhance innovation capacity in Europe. The NUTS-2 level regions evaluate their implementation and rethink their individual strategies for the upcoming funding period 2021–2027 by using their individually developed monitoring systems. For a sufficient comparison of regional performance with regard to the Smart Specialisation approach, the existing monitoring systems seem to lack any comparability. The European regions act like islands when setting up, implement and monitor their Smart Specialisation strategies. Another circumstance detaining a comparable monitoring across Europe is the existence of partly regional and partly national Smart Specialisation strategies.
... These services are today affected by important changes, especially in metropolitan areas, due to the evolution of ICT solutions and the application of Internet of Things (IoT) and Big Data paradigms, which concern aspects such as: methods of data detection, analysis and management; methods of communication/interaction with users; monitoring of performance; methods of response of systems, network interactions, etc. The digitalization of urban management processes is not simply bringing services towards ICTbased solutions, but it is redefining in a disruptive way the meanings of the concept of the city itself (digital, eco, green, intelligent, sustainable, etc.) [2,3], multiplying the interpretive keys of its cognitive methods [4], dynamically expanding its boundaries (from the smart city to the smart region) in relation to the growth of networks based on smart specialization strategies [5,6]. It is a scenario characterized by a heterogeneity of interpretations and experiments [7][8][9][10] in which the evolution of the new ICT technological offer plays an important role in placing the importance of services as enablers of transformations of the behaviors of the different categories of stakeholders [11] as well as in the management of tangible and intangible assets and related parameters for urban performance assessment [8]. ...
Chapter
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A Smart City can be defined as a complex socio-technical system in which services are optimized by the use of digital telecommunication technologies for the benefit of its inhabitants and business activities. The Smart City topic is today at the centre of many debates at European and international levels, also for the potential impact of the innovation of urban services within the overall performance of cities. Literature and virtuous cases of Smart Cities at the European level envisage optimization and innovation scenarios for traditional Urban Facility Management (UFM) services, based on the application of Information and Communication Technologies (ICTs), in particular Internet of Things (IoT) and Big Data management. Although the interest in the transition of the cities towards Smart Cities by administrations is growing, this transformation process appears to be still experimental and not much supported by shared knowledge references and tools. In light of this premise, the contribution - that is part of the PRIN research “Metropolitan cities: economic-territorial strategies, financial constraints and circular regeneration” - introduces the main results of the study conducted on a sample of 21 cities at the European scale with the aim of deepening and analyzing: (i) current innovation scenarios of UFM services enabled by ICTs that allow information sharing (Big Data flows) and a continuous monitoring of infrastructures and physical assets at the urban scale; (ii) characteristics and main trends in the implementation by public administrations of information platforms for the provision of smart UFM services and, more in general, for the smart management of cities; (iii) the potentialities of Milan, investigating the evolution of the offered smart urban services and of the adopted cognitive tools to manage city information, highlighting main trends, strengths and possible scenarios of improvement.
... The Smart Specialisation policy community and researchers have deployed an impressive collective effort to promote knowledge creation and circulation on this specific policy experiment. The result is the flourishing production of books, academic papers, technical reports, policy briefs and online contents on Smart Specialisation (Fellnhofer, 2017;Mora et al., 2019). Recent progresses in the conceptual framework of the policy as well as in the definition and operationalisation of the strategies in many places are, among other things, the outcome of this learning process. ...
Technical Report
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The goal of this paper is to contribute to the collective learning process on the Smart Specialisation policy experience. It does so by presenting a systematic collection of evidence and lessons on this policy endeavour. More specifically, the reflections contained in this paper draw upon the views and experiences of national and regional authorities, collected during the Peer eXchange and Learning (PXL) workshops organised by the Smart Specialisation Platform of the European Commission’s Joint Research Centre (Territorial Development Unit). Overall, 25 among European Union (EU) regions and countries were peer-reviewed and around 350 participants contributed to the debates. This report explores some of the main challenges, providing lessons and recommendations, on three important components of the Smart Specialisation policy framework: governance, entrepreneurial discovery process and monitoring. The arguments and list of points illustrated in this paper do not aim at completeness; rather, they represent an effort to collect disperse evidence and knowledge, which can inform the current debate on the future of the policy in the EU and beyond.
Article
Full-text available
Purpose/Thesis: This paper examines the position of public libraries in smart city strategies. To that end, I verify two hypotheses, H1: Cities analyzed employ strategic plans to define their path to “smartness”, and H2: Public libraries are a part of these strategies. Approach/Methods: Top 30 cities from the ranking of IESE Cities in Motion Index 2019 were se­lected. The hypotheses were tested through the analysis of strategy documents and web portals. In most cases, the analysis relied on English versions of said documents/portals, occasionally compared with the national language version . Results and conclusions: The process of verifying the first hypothesis led to identifying four groups: G1, comprising cities with a general strategy, presumed to include smart initiatives (3 cities), G2: cities with a separate “smart city” strategy, published on their own portal, or a related website (15 cities); G3: cities with subsites/portals briefly summarizing their activities in the area of ‘smart’ development (10 cities), and G4: cities with many sectoral strategies, presumed to include smart initiatives (2 ci­ties). The analysis allowed the identification of a number of areas in which public libraries already contribute to smart development: smart building, smart infrastructure, smart services, digital skills and life-long learning, sustainability, creativity, digital citizenship and smart business Originality/Value: Although many library and information science scholars study smart cities, no similar study has been conducted, and therefore, this paper, with its unique approach, offers a new perspective on the discussion on smart libraries.
Book
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Untangling Smart Cities: From Utopian Dreams to Innovation Systems for a Technology-Enabled Urban Sustainability helps all key stakeholders understand the complex and often conflicting nature of smart city research, offering valuable insights for designing and implementing strategies to improve the smart city decision-making processes. The book drives the reader to a better theoretical and practical comprehension of smart city development, beginning with a thorough and systematic analysis of the research literature published to date. It addition, it provides an in-depth understanding of the entire smart city knowledge domain, revealing a deeply rooted division in its cognitive-epistemological structure as identified by bibliometric insights. Users will find a book that fills the knowledge gap between theory and practice using case study research and empirical evidence drawn from cities considered leaders in innovative smart city practices. Key features: Provides clarity on smart city concepts and strategies; Presents a systematic literature analysis on the state-of-the-art of smart cities' research using bibliometrics combined with practical applications; Offers a comprehensive and systematic analysis of smart cities research produced during its first three decades; Generates a strong connection between theory and practice by providing the scientific knowledge necessary to approach the complex nature of smart cities; Documents five main development pathways for smart cities development, serving the needs of city managers and policymakers with concrete advice and guidance.
Technical Report
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The white paper on “Intelligence and Co-creation in Smart Specialisation Strategies” outlines some key conclusions from the Online S3 project, funded under the Horizon 2020 programme of the European Commission. The Online S3 project has produced an online platform composed of software applications and roadmaps that facilitate the design and implementation of Research and Innovation Strategies for Smart Specialisation (RIS3). Using a baseline set of methodologies for strategy design, Online S3 is advancing the understanding of RIS3 as a place-based and evidence-driven innovation policy, relying on large datasets and software for user engagement, co-creation and collective intelligence in policy design. In this white paper, the core building blocks of RIS3 are presented, as they appear in EU documents and related literature, such as ex ante conditionalities, stakeholder engagement, specialisation by diversification, entrepreneurial discovery, policy co-design, monitoring and assessment. This white paper also discusses weaknesses of the current period and what can be done better in the near future; thus, puts RIS3 in retrospect and prospect for 2021-2027. At the same time, it looks into critical dimensions for the next stage of RIS3, focusing on how strategies can be improved by datasets and software, enabling the implementation of complex methods; thus, facilitating collective intelligence and co-creation of solutions, which both are able to usher a transition from the triple to quadruple helix model of collaboration. Finally, the annex presents a short description of the 28 software applications and the 4 roadmaps hosted on the Online S3 Platform, which enable the use of datasets and sophisticated methodologies by policy-makers.
Technical Report
Full-text available
The Online S3 Platform (http://s3platform.eu/) aims to expand administrative capabilities of regional institutions, and thus, become an essential tool for improving the effectiveness of decision-making processes. The report describes the overall Online S3 platform mechanism, in terms of information flows and application interoperability. Its main rationale is to present the logical connections and the information links between the 28 developed applications, as well as to illustrate different ways in which they could be combined to provide services to the users. These services could be used to support the RIS3 design and implementation phases, as well as generic processes related to the general concept of strategic planning. Moreover, the identification and development of 4 comprehensive roadmaps aims on more explicitly guide regional authorities towards an effective implementation of the RIS3 process. The Mini-S3 roadmap provides a core set of methodologies and applications that are essential for the development of RIS3 strategies, whereas the EDP roadmap targets on providing guidance on effectively supporting the three phases of EDP implementation – knowledge production, stakeholder engagement and knowledge sharing, as well as collaborative decision-making. The significance and role of specialisation analysis in the context of developing and implementing a RIS strategy is addressed by the Specialisation roadmap, whilst methodological guidance to policymakers and regional officers on specific (thematic) investment priority areas within their RIS3 strategy is provided by the Industry vertical platforms and Global Value Chains roadmap.
Conference Paper
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This paper reports on the findings of the Online-S3 project, funded under the Horizon 2020 Programme (ISSI-4-2015), which tries to address the challenge of strengthening regional smart growth policies by developing an online platform for policy advice. The Online-S3 Platform offers a web-based environment for supporting the design, implementation and assessment of Research and Innovation Strategies for Smart Specialisation (RIS3) aiming to enrich the methodological framework that is being used towards enhancing smart growth policy design processes in EU regions. The paper first provides an overview of the Online-S3 platform, and then, focuses on the applications that could be used to help regional and national authorities during the priority setting phase of a RIS3 strategic planning process. Given that this phase relates to the identification and selection of specific sectors that can be used as flagships to support regional growth, the Online-S3 Platform offers a great tool towards enhancing the effectiveness of the smart growth paradigm.
Book
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This book comprises a selection of the top contributions presented at the second international conference “Smart and Sustainable Planning for Cities and Regions 2017”, held in March 2017 in Bolzano, Italy. Featuring forty-six papers by policy-makers, academics and consultants, it discusses current groundbreaking research in smart and sustainable planning, including the progress made in overcoming cities’ challenges towards improving the quality of life. Climate change adaptation and mitigation of global warming, generally identified as drivers of global policies, are just the “tip of the iceberg” when it comes to smart energy transition. Indeed, equally relevant towards this current transformation – and key topics in this volume – are ICTs, public spaces and society; next economy for the city; strategies and actions for good governance; urban-rural innovation; rethinking mobility. The book’s depth in understanding and insightfulness in re-thinking demonstrate the breaking of new ground in smart and sustainable planning. A new ground that policy-makers, academics and consultants may build upon as a bedrock for smart and sustainable planning.
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More than 20 years have now passed since the concept of smart city first appeared in a scholarly publication, marking the beginning of a new era in urban innovation. Since then, the literature discussing this new concept and the ICT-oriented urban-innovation approach it stands for has been growing steadily, along with the number of initiatives that cities all over the world have launched to pursue their ambition of becoming smart. However, current research still falls short of providing a clear understanding of smart cities and the scientific knowledge policy makers and practitioners both need to deal with their progressive development. In response to this shortfall, this paper offers a bibliometric study of the first two decades of smart-city research, whereby citation link-based clustering and text-based analysis are combined to: (1) build and visualize the network of scholarly publications shaping the intellectual structure of the smart city research field; (2) identify the clusters of thematically related publications; and (3) reveal the emerging development paths of smart cities that these clusters support and the strategic principles they embody. This study uncovers five main development paths: the Experimental Path; the Ubiquitous Path; the Corporate Path; the European Path; and the Holistic Path. Overall, this analysis offers a comprehensive and systematic view of how a smart city can be understood theoretically and as a scientific object of knowledge able to inform policy-making processes.
Conference Paper
Full-text available
This article suggests the Entrepreneurial Discovery Process (EPD) that underlies Research and Innovation Strategies for Smart Specialisation (RIS3) is not so much caught in the transition from the Triple to the Quadruple Helix, as rooted in a division within civil society. In particular, rooted in a division within civil society, over public trust in the EDP and around the democratic deficit of RIS3. Over public trust in the EDP and around the democratic deficit of RIS3 as a transgression, which centers attention on the participatory governance of science and technology, which is regressive in nature and whose knowledge economy seeks to overcome such limitations as part of the search for sustainable regional growth that serves civil society.
Conference Paper
Full-text available
Smart specialisation can be considered an entrepreneurial discovery process which makes it possible to identify where regions can benefit from specialising in specific areas of science and technology. The European Commission suggests the development of research and innovation strategies for smart specialisation (RIS3) should concentrate resources on the most promising areas of comparative advantage, e.g. on clusters, existing sectors and cross-sectoral activities, eco-innovation, high value-added markets or specific research areas. This calls for regions to assess their assets, single out competitive advantages and highlight the cohesive qualities of territories. The RIS3 Key and Self-Assessment Guides both advise regions on how to prepare for smart specialisation, by identifying existing strengths and the potential for future development efforts, spotting remaining gaps and bottlenecks in the innovation system and mobilizing the relevant institutions involved in the entrepreneurial discovery process. The paper sets out the results of the Online S3 project's open consultation on these guides and the 29 RIS3 methods developed to guide this process of entrepreneurial discovery under the post-linear era of research and innovation.
Article
Bibliometrics is a powerful tool for analyzing knowledge domains and revealing their cognitive-epistemological structure. Different mathematical models and statistical techniques have been proposed and tested to carry out bibliometric analyses and demonstrate their effectiveness in uncovering how fields of research are intellectually structured. These include two hybrid techniques that allow clusters of related documents obtained from a co-citation analysis to be labeled using textual data. This paper reports on the findings of a bibliometric study in which these hybrid techniques are combined to: (1) build and visualize the network of publications shaping the intellectual structure of the smart city research field by considering the first two decades of literature dealing with this subject; (2) map the clusters of thematically-related publications; and (3) reveal the emerging development paths of smart cities that each thematic cluster represents and the strategic principles they embody. The five development paths which the analysis uncovers and the strategic principles each stands on are then compared by reviewing the most recent literature on smart cities. Overall, this bibliometric study offers a systematic review of the research on smart cities produced since 1992 and helps bridge the division affecting this research area, demonstrating that it is caused by the dichotomous nature of the development paths of smart cities that each thematic cluster relates to and the strategic principles they in turn support