EconPapers    
Economics at your fingertips  
 

Data envelopment analysis of the efficiency of academic departments at a public university in Iran

Abolghasem Naderi

International Journal of Education Economics and Development, 2019, vol. 10, issue 1, 57-75

Abstract: This paper examines the performance efficiency of 77 academic departments at a public university in Iran using data envelopment analysis (DEA), which applies a multiple input and output variables approach. To conduct reasonable analyses, four types of academic staff accompanied with salary paid were used as the input measures and two indexed measures of output which include students taught and research performance. Using various DEA models, we obtained different estimates for efficiency scores which show that the type of model used affects the efficiency scores. We also found that average efficiency is relatively high and about one half of all academic departments at the university, based on the results of input-oriented variable return to scale models, perform efficiently. The results of the DEA models employed also illustrate the existence of scale inefficiencies and the relatively large heterogeneity among the departments. However, we did not find sufficient evidence supporting efficiency heterogeneity across different fields of study (i.e., humanities and social sciences against sciences and engineering). The determinants of departmental efficiency were also examined.

Keywords: data envelopment analysis; DEA; efficiency evaluation; scale effects; Iranian academic departments; education and research performance; Iran. (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.inderscience.com/link.php?id=97128 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijeded:v:10:y:2019:i:1:p:57-75

Access Statistics for this article

More articles in International Journal of Education Economics and Development from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().

 
Page updated 2025-03-19
Handle: RePEc:ids:ijeded:v:10:y:2019:i:1:p:57-75