Clustering networked funded European research activities through rank-size laws

Roy Cerqueti (), Antonio Iovanella () and Raffaele Mattera ()
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Roy Cerqueti: Sapienza University of Rome
Antonio Iovanella: University of International Studies of Rome - UNINT
Raffaele Mattera: Sapienza University of Rome

Annals of Operations Research, 2024, vol. 342, issue 3, No 17, 1707-1735

Abstract: Abstract This paper treats a well-established public evaluation problem, which is the analysis of the funded research projects. We specifically deal with the collection of the research actions funded by the European Union over the 7th Framework Programme for Research and Technological Development and Horizon 2020. The reference period is 2007–2020. The study is developed through three methodological steps. First, we consider the networked scientific institutions by stating a link between two organizations when they are partners in the same funded project. In doing so, we build yearly complex networks. We compute four nodal centrality measures with relevant, informative content for each of them. Second, we implement a rank-size procedure on each network and each centrality measure by testing four meaningful classes of parametric curves to fit the ranked data. At the end of such a step, we derive the best fit curve and the calibrated parameters. Third, we perform a clustering procedure based on the best-fit curves of the ranked data for identifying regularities and deviations among years of research and scientific institutions. The joint employment of the three methodological approaches allows a clear view of the research activity in Europe in recent years.

Keywords: Rank-size analysis; Complex networks; Cluster analysis; European research projects (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10479-023-05321-6

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