A heuristic approach based on Leiden rankings to identify outliers

Evidence from Italian universities in the European landscape

Bibliographic Data

ID21442209
AuthorsCinzia Daraio (0000-0002-4825-0071, Sapienza University of Rome, corresponding author), Simone Di Leo (0000-0001-9532-8399, Sapienza University of Rome), L Leydesdorff (0000-0002-7835-3098, University of Amsterdam)
Year2023
Volume128
Issue1
Pages483-510
Publication date2023-01-01
Open AccessYes
TypeARTICLE
VenueScientometrics (JOURNAL)
Journal identifiersISSN: 0138-9130 • E-ISSN: 1588-2861
PublisherSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1007/s11192-022-04551-y
OpenAlexW4308115734
LanguageEN
References cited31

We propose an innovative use of the Leiden Rankings (LR) in institutional management. Although LR only consider research output of major universities reported in Web of Science (WOS) and share the limitations of other existing rankings, we show that they can be used as a base of a heuristic approach to identify “outlying” institutions that perform significantly below or above expectations. Our approach is a non-rigorous intuitive method (“heuristic”) because is affected by all the biases due to the technical choices and incompleteness that affect the LR but offers the possibility to discover interesting findings to be systematically verified later. We propose to use LR as a departure base on which to apply statistical analysis and network mapping to identify “outlier” institutions to be analyzed in detail as case studies. Outliers can inform and guide science policies about alternative options. Analyzing the publications of the Politecnico di Bari in more detail, we observe that “small teams” led by young and promising scholars can push the performance of a university up to the top of the LR. As argued by Moed (Applied evaluative informetrics. Springer International Publishing, Berlin, 2017a), supporting “emerging teams”, can provide an alternative to research support policies, adopted to encourage virtuous behaviours and best practices in research. The results obtained by this heuristic approach need further verification and systematic analysis but may stimulate further studies and insights on the topics of university rankings policy, institutional management, dynamics of teams, good research practice and alternative funding methods

Bibliometrics · Data mining · Data science · Economics · Heuristic · Informetrics · Management science · Operations research · Outlier · Artificial Intelligence · Computer Science · Mathematics · scientometrics and bibliometrics research

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