Data Envelopment Analysis and Higher Education: A Systematic Review of the 2018–2022 Literature and Bibliometric Analysis of the Past 30 Years of Literature

The interest in Data Envelopment Analysis (DEA) has grown since its first put forward in 1978. In response to the overwhelming interest, systematic literature reviews, as well as bibliometric studies, have been performed in describing the state-of-the-art and offering quantitative outlines with rega...

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Bibliographic Details
Published in:SAGE Open
Main Author: Ahmad A.M.; Nana Khurizan N.S.
Format: Review
Language:English
Published: SAGE Publications Inc. 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203525696&doi=10.1177%2f21582440241271153&partnerID=40&md5=abe7fa421fad55ddf70b9fd4ba6c476a
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Summary:The interest in Data Envelopment Analysis (DEA) has grown since its first put forward in 1978. In response to the overwhelming interest, systematic literature reviews, as well as bibliometric studies, have been performed in describing the state-of-the-art and offering quantitative outlines with regard to the high-impact papers on global applications of DEA and the higher education system (DEA-HE). This study examines 75 systematic literature review (SLR) studies published between 2018 and 2022 and 508 bibliometric studies published between 1992and 2022. Four performance-focused areas are identified through SLR analysis: institutional performance, departmental performance, performance of study program, and performance of other higher education (HE) activities. This study highlights issues, methods, and resolutions in selected SLR literature. Bibliometric analysis revealed an increasing trend in DEA-HE since 2003, with the highest number of publications in 2021. Tommaso Agasisti was the most productive author, and Jill Johnes was the most influential. The journal Scientometric had the most publications in the area. This study lays the groundwork for future research. Future reviewers may find the common practises, constraints, and underlying assumptions presented in this study useful for the selection and analysis of relevant studies. © The Author(s) 2024.
ISSN:21582440
DOI:10.1177/21582440241271153