:: Volume 13, Issue 2 (2021) ::
ihej 2021, 13(2): 31-71 Back to browse issues page
Evaluating the efficiency of Iranian industrial universities based on non-parametric and parametric approaches
Shahrbanoo Khoshkab
, khoshkab.sh@ut.ac.ir
Abstract:   (2213 Views)
The present study is the efficiency of Iranian industrial universities using non-parametric methods of data envelopment analysis and random border analysis parameter for input variables (number of incoming students, number of faculty members, number of staff and budget) and output (specific income, Has evaluated the number of students studying, the number of graduates and conference papers) and data extracted from statistical databases and documents of higher education for 20 industrial universities during the academic years 1392-1393 and 1393-1394 . Expressive research results; 1- Existence of inefficiency in university units; 2- Difference in the degree of inefficiency in different university units; 3- Decreasing the average efficiency of all selected universities in 1393 compared to 1394; 4- Decreasing the average educational efficiency and increasing the average research efficiency of selected universities at the time of the study; 6- No heterogeneity of data variance in random boundary analysis test; And 7- Coordination between some explanatory variables, including faculty members and budget in the variance inflation test. In the random border analysis method, in addition to technical inefficiency, random inefficiency and the coefficient of elasticity of inputs on education and research outputs were also estimated to draw a favorable roadmap for policy makers and decision makers of academic units to make effective decisions.
Keywords: Efficiency, Data Envelopment Analysis, Stochastic Boundary Analysis, University of Technology.
Full-Text [PDF 949 kb]   (636 Downloads)    
Type of Study: Research | Subject: Special
Received: 2020/09/8 | Accepted: 2022/04/4


XML   Persian Abstract   Print



Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 13, Issue 2 (2021) Back to browse issues page