Studying the heterogeneity of European higher education institutions
Renato Bruni,
Giuseppe Catalano,
Cinzia Daraio,
Martina Gregori () and
Henk F. Moed
Additional contact information
Renato Bruni: Sapienza University of Rome
Giuseppe Catalano: Sapienza University of Rome
Cinzia Daraio: Sapienza University of Rome
Martina Gregori: Sapienza University of Rome
Henk F. Moed: Sapienza University of Rome
Scientometrics, 2020, vol. 125, issue 2, No 18, 1117-1144
Abstract:
Abstract The heterogeneity of the Higher Education (HE) Institutions is one of the main critical issues in the assessment of their performance. This paper adopts a multi-level and multi-dimensional perspective, combining national (macro) and institution (micro) level data, and measuring both research and teaching activity, using performance indicators derived from the European Tertiary Education Register, CWTS Leiden Ranking, and PATSTAT patent database. Clustering and efficiency analysis are combined to characterize the heterogeneity of national HE systems in European countries, and reveal the potential of using micro level data to characterize national level performance. Large differences are observed between the European countries, partially due to the fact that they are in different phases of their scientific (and economic) development and of the re-structuring of their HE systems. Evidence is found that universities specializing either in teaching or in research tend to have a higher efficiency than those institutions balancing research and teaching. Tradeoffs are observed between undergraduate and post-graduate activities, and a “Matthew cumulative effect” seems in place on the European institutions analysed: high quality research is able to attract external funds that stimulate innovative and patenting activities that in turn are self-reinforcing to the scientific activities. The results reveal once more the limits and dangers of one-dimensional approaches to the performance of HEIs.
Keywords: University; Europe; Heterogeneity; Clustering; Efficiency analysis (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
http://link.springer.com/10.1007/s11192-020-03717-w Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:125:y:2020:i:2:d:10.1007_s11192-020-03717-w
Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192
DOI: 10.1007/s11192-020-03717-w
Access Statistics for this article
Scientometrics is currently edited by Wolfgang Glänzel
More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().