Multidimensional Clustering of EU Regions: A Contribution to Orient Public Policies in Reducing Regional Disparities

Abstract

This paper applies multidimensional clustering of EU-28 regions with regard to their specialisation strategies and socioeconomic characteristics. It builds on an original dataset.Several academic studies discuss the relevant issues to be addressed by innovation and regional development policies, but so far no systematic analysis has linked the different aspects of EU regions research and innovation strategies (RIS3) and their socio-economic characteristics. This paper intends to fill this gap, with the aim to provide clues for more effective regional and innovation policies.In the data set analysed in this paper, the socioeconomic and demographic classification associates each region to one categorical variable (with 19 categories), while the classification of the RIS3 priorities clustering was performed separately on "descriptions" (21 Boolean categories) and "codes" (11 Boolean Categories) of regions' RIS3. The cluster analysis, implemented on the results of the correspondence analysis on the three sets of categories, returns 9 groups of regions that are similar in terms of priorities and socioeconomic characteristics. Each group has different characteristics that revolve mainly around the concepts of selectivity (group's ability to represent a category) and homogeneity (similarity in the group with respect to one category) with respect to the different classifications on which the analysis is based.Policy implications showed in this paper are discussed as a contribution to the current debate on post-2020 European Cohesion Policy, which aims at orienting public policies toward the reduction of regional disparities and to the enhance complementarities and synergies within macro-regions.

Reinforcing comparative monitoring of Smart Specialisation performance across European regions: transnational RIS3 observatory model as a tool for Smart Specialisation governance

“…The European Commission highly supports cluster strategies within the European growth strategy 2020 (European Commission, 2016a; Ketels & Protsiv, 2016;El Idrissi et al, 2020). Pavone et. al.…”

“…This structure is necessary for regular information exchange as well as on-going monitoring on European level, including an evaluation of funding programmes and their results in terms of the RIS3 approach. To make sure a well-balanced number of regions within the observatories and avoid large-scale observatories, a geographical limitation could be implemented, also socio-economic characteristics could be reasonable allocation of the observatories (Pavone et. al., 2020).…”

Mapping regional strengths in a key enabling technology: The distribution of Internet of Things competences across European regions

“…In this interregional perspective about policy implications, our findings provide regional policy‐makers with a very operational support, thanks to the identification of which regions should be fostered as full IoT value‐chain providers and which need to specialize further or, alternatively, diversify into new, related, complementary domains and networks across regions and countries. In terms of regional policies, this calls for new perspectives towards different units of policy interventions, as is the case of macro‐regional strategies (Pavone et al, 2020; Radosevic et al, 2017; Russo et al, 2019).…”

Integration of Baltic Small and Medium-Sized Ports in Regional Innovation Strategies on Smart Specialisation (RIS3)

“…In line with RIS3 analysis for NUTS-2 regions, cluster conceptualisations for elaboration of innovation systems are a sufficient theoretical concept [51] using the definition of Porter [52] for clusters being an interconnection of companies and institutions in a particular field with a certain geographic concentration. NUTS-2 regions can be classified as clusters under the implementation of RIS3 [53,54] as well. Thus, maritime clusters are the conceptual connection between RIS3 and SMSPs, bearing in mind that cluster can be seen as tools for regional development as a reduced scales innovation system [55].…”