Ranking resilience: assessing the impact of scientific performance and the expansion of the Times Higher Education Word University Rankings on the position of Czech, Hungarian, Polish, and Slovak universities

被引:0
|
作者
Toth, Barbara [1 ]
Motahari-Nezhad, Hossein [1 ]
Horseman, Nicki [2 ]
Berek, Laszlo [3 ,4 ]
Kovacs, Levente [5 ]
Holgyesi, Aron [1 ,6 ]
Pentek, Marta [1 ]
Mirjalili, Seyedali [6 ,7 ]
Gulacsi, Laszlo [1 ]
Zrubka, Zsombor [1 ]
机构
[1] Univ Res & Innovat Ctr, Obuda Univ, HECON Hlth Econ Res Ctr, Budapest, Hungary
[2] Horseman Bruce Associates Ltd, Torquay, Devon, England
[3] Obuda Univ, Doctoral Sch Safety & Secur, Budapest, Hungary
[4] Univ Lib, Obuda Univ, Budapest, Hungary
[5] Univ Res & Innovat Ctr, Obuda Univ, Physiol Controls Res Ctr, Budapest, Hungary
[6] Univ Res & Innovat Ctr, Obuda Univ, Budapest, Hungary
[7] Torrens Univ, Ctr Artificial Intelligence Res & Optimizat, Brisbane, Australia
关键词
University rankings; Bibliometric indicators; Higher education; Ranking prediction model; predictive factors; I21; I23; I28; ACADEMIC RANKING; INDICATORS; EXCELLENCE; ARWU; KEY;
D O I
10.1007/s11192-023-04920-1
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
University rankings are gaining importance worldwide. While the top-ranked universities are the subject of numerous academic publications, very little literature is available on universities in the lower two-thirds of the ranking list. In this study, we analysed the sensitivity of year to year changes in position in the Times Higher Education World University Rankings (THE) of universities from the Czech Republic, Hungary, Poland, and Slovakia using hypothetical scenarios of potential changes in their research outputs. A regression model was developed that quantifies the effect of the inclusion of institutions that are new to ranking as well as dropouts on the ranking list. We also developed a method to allow customized sensitivity analysis of the subsequent year's rank from an institution's projected research output, given its current rank and research output, assuming that other ranking indicators remain unchanged over 1-2 years. It should be noted that most universities in the region have ranked below 800, and while research output has been increasing, it was observed that ranks worsened for most universities from these four countries. The Field-Weighted Citation Impact and the total volume of publications had the highest effect on rankings, while the proportion of Scimago Q1 publications did not have a consistent effect on the projected next year's ranks. In most universities, the growth in research performance indicators were below the level that would be required to offset the rank changes due to the inclusion of new entrants in ranking. The findings of this research suggest that universities have to consider complex strategies to improve their ranking focusing on other activities than research such as reputation, internationalization, or industry income. With due caution, our results might be generalized to most of the universities below 800 in the THE. The rank prediction tool presented in this article is available online at https://hecon.uni-obuda.hu/en/rank-calculator/.
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页码:1739 / 1770
页数:32
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