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

Authors: Bibi Faheema Luckhoo; Arshad Ahmud Iqbal Peer

Addresses: Department of Applied Mathematical Sciences, University of Technology, Mauritius La Tour Koenig, Pointe-aux-Sables 11134, Mauritius ' Department of Applied Mathematical Sciences, University of Technology, Mauritius La Tour Koenig, Pointe-aux-Sables 11134, Mauritius

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.

DOI: 10.1504/IJDS.2023.132285

International Journal of Data Science, 2023 Vol.8 No.3, pp.211 - 239

Received: 23 Dec 2021
Received in revised form: 21 Jun 2022
Accepted: 27 Oct 2022
Published online: 17 Jul 2023 *

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