Abstract
Article history: Received March 25, 2012 Received in revised format 17 October 2012 Accepted 17 October 2012 Available online October 17 2012 Measuring relative efficiency of various universities has been a subject for years. In fact, when there is a growing competition among educational units, it is important to find facts on each university for making managerial decisions. In this paper, we present an empirical study to measure the relative efficiencies among different private universities in Iran. The proposed study of this paper uses data envelopment analysis along with Malmquist productivity index to measure the relative efficiencies of these units over the period 2004-2007. The method uses three inputs including number of students, number of university professors and the number of employees. The model also includes the number of educated people as well as research outputs for outputs of the DEA model. The results indicate that there are some big gaps among various units in terms of the number of research products and the number of graduated students. © 2013 Growing Science Ltd. All rights reserved.
Highlights
For over three decades, data envelopment analysis (DEA) has been a technique for measuring the relative efficiency of decision making units (DMUs) with multiple inputs and multiple outputs (Charnes et al, 1978, 1994; Banker et al, 1984)
We present an application of DEA method for measuring the relative efficiencies of various universities
We study the relative efficiencies of different educational systems based on the implementation of data envelopment analysis (DEA) over the period of 2004-2007
Summary
Data envelopment analysis (DEA) has been a technique for measuring the relative efficiency of decision making units (DMUs) with multiple inputs and multiple outputs (Charnes et al, 1978, 1994; Banker et al, 1984). DEA methods have been implemented for non-for-profit organizations where similar units are operating with various input/output and there is basically no revenue. Governmental agencies such as schools, hospitals, public libraries are instances of these cases. The input measures were built from the number of teachers and from universities' spending while the outputs measures were associated with undergraduate success rate and on the number of doctoral dissertations They used frontier analysis to separate universities that might qualify, as performing well from those were some improvement might be possible based on efficiency. Using 1995 data and applying DEA method, they reported that the university sector was performing well on technical and scale efficiency but there was place for improving performance on fee-paying enrolments.
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