Evaluating the performance of Tunisian higher Institutes of Technological Studies (ISETs) using a stochastic frontier analysis.

Efficiency Higher education institutions Stochastic frontier analysis Tunisia

Journal

Evaluation and program planning
ISSN: 1873-7870
Titre abrégé: Eval Program Plann
Pays: England
ID NLM: 7801727

Informations de publication

Date de publication:
24 Aug 2024
Historique:
received: 11 06 2023
revised: 11 08 2024
accepted: 19 08 2024
medline: 31 8 2024
pubmed: 31 8 2024
entrez: 28 8 2024
Statut: aheadofprint

Résumé

Benefiting from low repetition and dropout rates, as well as their excellent employability rate of their students, the Higher Institutes of Technological Studies (ISETs) have acquired a strategic position in the Tunisian higher education system. This paper aims to use the Stochastic Frontier Analysis (SFA) method to measure the efficiency of Tunisian Higher Institutes of Technological Studies (ISETs) and to determine the factors that cause performance differences. The results indicate that ISETs appear well managed, although some of them warrant a more detailed analysis (below-average efficiency). Also, it was found that the ISETs situated in the most industrialized part of the country, the Central-East, record highest scores of efficiency, while those in the South-East show more homogeneous efficiency. The results underscore the importance of focusing support and improvement efforts on ISETs located in less developed regions or those with lower efficiency levels. Moreover, the negative relationship between the age of institutions and their efficiency suggests that reforms to institutional practices may be necessary for older establishments. Finally, institutes that are located in one of the main cities will not necessarily be more efficient than the others. The findings presented in this paper have targeted and practical implications for the development of the ISET network in Tunisia.

Identifiants

pubmed: 39197406
pii: S0149-7189(24)00082-X
doi: 10.1016/j.evalprogplan.2024.102480
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

102480

Informations de copyright

Copyright © 2024. Published by Elsevier Ltd.

Auteurs

Anis Bouzouita (A)

Department of Quantitative Methods, Higher Institute of Management of Sousse (ISG), University of Sousse, Sousse, Tunisia. Electronic address: anisbouzouita2005@yahoo.fr.

Imen Kooli (I)

Department of Quantitative Methods, Higher Institute of Management of Sousse (ISG), University of Sousse, Sousse, Tunisia. Electronic address: imene.kooli@gmail.com.

Classifications MeSH