A DEA-WEI method for ranking universities in the presence of imprecise data

Bibi Faheema Luckhoo and Arshad Ahmud Iqbal Peer

International Journal of Data Science, 2023, vol. 8, issue 3, 211-239

Abstract: Ranking universities has become increasingly common in recent years as it is considered a significant source of comparative information for various stakeholders. The three main university rankings differ by methodology and results since different parameters are considered. In this paper, data envelopment analysis (DEA) is used to obtain a unified ranking of universities based on the data of these ranking systems. Due to the absence of input measures in the dataset, DEA-WEI (without explicit input) models are studied. In order to consolidate the classification, the established rankings of the three ranking systems, which are ordinal data, are considered. As such, we suggest a new approach to rank the universities in situations where imprecise data and only output measures are present.

Keywords: DEA; data envelopment analysis; university rankings; imprecise data; ordinal data; WEI; without explicit inputs. (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijdsci:v:8:y:2023:i:3:p:211-239

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