A DEA-WEI Cross-Efficiency Approach for Ranking Universities in the Presence of Imprecise Data

Abstract

Abstract Recently, the popularity of university rankings has grown significantly. They are considered a significant source of guidance for various stakeholders.Some of the most well-known rankings are the Academic Ranking of World Universities (ARWU), Quacquarelli Symonds World University Rankings (QS), and Times Higher Education Rankings (THE). These ranking systems usedifferent parameters and methodologies, producing different ranking results.Here, we use data envelopment analysis (DEA) to obtain anaggregate ranking of universities based on the data of these established systems.Because of DEA's lack of discriminatory power, we considered the cross-efficiency method, which allows ordering among entities and removes unrealistic weight schemes without weight restrictions.Cross-efficiency evaluation is usually applied only to precise inputs and outputs.Since our data set does not include any input measures, DEA-WEI (Without Explicit Input) modelsare studied. To consolidate the classification, we consider the rankings of thethree systems, which are ordinal data. Hence, we develop a new cross-efficiency approach torank entities with imprecise data and WEI. In order to illustrate the applicability of our proposed model, we apply it to the rankings data and institutes of the Chinese Academy of Sciences. MSC Classification: 90C08 , 90C90