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Is smart specialisation monopolising the research on the EU cohesion policy? Evidence from a bibliometric analysis

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Abstract

The aim of the paper is to perform a bibliometric analysis of the scientific literature of the European cohesion policy based on articles published in more than three decades, from 1986 to 2019. The period considered covers the main events that have characterised European policy for regions and cities, starting from the signature of the Single European Act in 1986 to the implementation of Smart Specialisation Strategy (S3) since 2014, which has been guiding investment policies in scientific research and innovation funded by cohesion policy. One of the key results concerns the exponential interest of researchers on the topic of Smart Specialisation which has the potential to monopolise the debate in the coming years, especially if it will be associated with the emerging topic of sustainability under the EU regional policies. The map** and evaluation of the literature relating to cohesion policy can represent an important point of reference to inspire future research.

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Notes

  1. Research and Innovation for Smart Specialisation Strategy.

  2. For an overview on NUTS classification is useful to consult: https://ec.europa.eu/eurostat/web/nuts/background

  3. Regulation (EU) 2021/1060 of the European Parliament and of the Council of 24 June 2021, Official Journal of the European Union L 231, 30.6.2021, p. 159–706 http://data.europa.eu/eli/reg/2021/1060/oj

  4. In the case of excluded papers, this information on funding was present, for some reason, in the abstract.

  5. SCIMAGO Journal & Country Rank reports alternative measurements to the IF. See https://www.scimagojr.com/.

  6. This index is calculated as Inclusion index = #(A ∩ B)(#A;#B) and assumes value 1 when all keywords of theme B are contained in theme A.

  7. https://www.aeaweb.org/jel/guide/jel.php.

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Correspondence to Francesco Foglia.

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Foglia, F. Is smart specialisation monopolising the research on the EU cohesion policy? Evidence from a bibliometric analysis. Scientometrics 128, 1001–1021 (2023). https://doi.org/10.1007/s11192-022-04585-2

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