caa a22 4500 445349859 CHVBK 20180317142840.0 cr unu---uuuuu 170323e20111001xx s 000 0 eng 10.1007/s11192-011-0419-5 doi (NATIONALLICENCE)springer-10.1007/s11192-011-0419-5 Improving quality assessment of composite indicators in university rankings: a case study of French and German universities of excellence [Elektronische Daten] [M. Benito, R. Romera] Composite indicators play an essential role for benchmarking higher education institutions. One of the main sources of uncertainty building composite indicators and, undoubtedly, the most debated problem in building composite indicators is the weighting schemes (assigning weights to the simple indicators or subindicators) together with the aggregation schemes (final composite indicator formula). Except the ideal situation where weights are provided by the theory, there clearly is a need for improving quality assessment of the final rank linked with a fixed vector of weights. We propose to use simulation techniques to generate random perturbations around any initial vector of weights to obtain robust and reliable ranks allowing to rank universities in a range bracket. The proposed methodology is general enough to be applied no matter the weighting scheme used for the composite indicator. The immediate benefit achieved is a reduction of the uncertainty associated with the assessment of a specific rank which is not representative of the real performance of the university, and an improvement of the quality assessment of composite indicators used to rank. To illustrate the proposed methodology we rank the French and the German universities involved in their respective 2008 Excellence Initiatives. Akadémiai Kiadó, Budapest, Hungary, 2011 Composite indicators nationallicence Rankings nationallicence Benchmarking nationallicence Higher Education Institutions nationallicence Weighting schemes nationallicence Simulation techniques nationallicence Benito M. Statistics Department, Universidad Carlos III de Madrid, C/Madrid 126, 28903, Getafe, Spain aut Romera R. Statistics Department, Universidad Carlos III de Madrid, C/Madrid 126, 28903, Getafe, Spain aut Scientometrics Springer Netherlands 89/1(2011-10-01), 153-176 0138-9130 89:1<153 2011 89 11192 https://doi.org/10.1007/s11192-011-0419-5 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11192-011-0419-5 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Benito M. Statistics Department, Universidad Carlos III de Madrid, C/Madrid 126, 28903, Getafe, Spain aut NATIONALLICENCE 700 1- Romera R. Statistics Department, Universidad Carlos III de Madrid, C/Madrid 126, 28903, Getafe, Spain aut NATIONALLICENCE 773 0- Scientometrics Springer Netherlands 89/1(2011-10-01), 153-176 0138-9130 89:1<153 2011 89 11192 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer