<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In recent years, the evaluation of research conducted in European universities has become a significant problem. The growing concern for the quality and evaluation of research conducted at universities highlights the importance of university rankings, especially global rankings. The aim of the paper is to identify the network system of Polish universities of economics among their European counterparts belonging to the same networks, and indicate the positions of Polish universities within these networks. The study used a network approach to analyse the connections of European universities using university networks. The networks enable the visualization of complex, multidimensional data and provide statistical indicators for interpreting the resultant graphs. The analysis is exploratory in its nature and uses visualisation techniques of social network analysis (SNA), multidimensional scaling (MDS), principal component analysis (PCA), and Eigen-model network analysis (ENA). The analysis covered 150 universities of economics in Europe and 11 university networks. Network analyses were performed with the R program. The paper presents different methods that allowed for the identification of network systems of Polish economic universities within the networks of European universities. An analysis of the social networks based on network indicators was also included.</p>
</abstract>

In recent years, the evaluation of research conducted in European universities has become a significant problem. The growing concern for the quality and evaluation of research conducted at universities highlights the importance of university rankings, especially global rankings. The aim of the paper is to identify the network system of Polish universities of economics among their European counterparts belonging to the same networks, and indicate the positions of Polish universities within these networks. The study used a network approach to analyse the connections of European universities using university networks. The networks enable the visualization of complex, multidimensional data and provide statistical indicators for interpreting the resultant graphs. The analysis is exploratory in its nature and uses visualisation techniques of social network analysis (SNA), multidimensional scaling (MDS), principal component analysis (PCA), and Eigen-model network analysis (ENA). The analysis covered 150 universities of economics in Europe and 11 university networks. Network analyses were performed with the R program. The paper presents different methods that allowed for the identification of network systems of Polish economic universities within the networks of European universities. An analysis of the social networks based on network indicators was also included.

Polish Universities of Economics in European Networks

miroslawa.sztemberg-lewandowska@ue.wroc.pl

Wroclaw University of Economics and Business

Econometrics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Polish Universities of Economics in European Networks"}

In recent years, the evaluation of research conducted in European universities has become a significant problem. The growing concern for the quality and...

Polish Universities of Economics in European Networks

Pubblicato online: 12 mag 2021

Pagine: 91 - 111

DOI: https://doi.org/10.15611/eada.2021.1.06

Parole chiave
principal component analysis (PCA), multidimensional scaling (MDS), network analysis, European universities

© 2021 Adam Sagan et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Polish Universities of Economics in European Networks

Pubblicato online: 12 mag 2021

Pagine: 91 - 111

DOI: https://doi.org/10.15611/eada.2021.1.06

Parole chiaveprincipal component analysis (PCA), multidimensional scaling (MDS), network analysis, European universities

© 2021 Adam Sagan et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Parole chiave
principal component analysis (PCA), multidimensional scaling (MDS), network analysis, European universities