Efficiency Analysis of Public Universities in Iran Using DEA Approach: Importance of Stakeholder’s Perspective

Document Type: Research Paper

Authors

School of Engineering,Alzahra University,Tehran, Iran

Abstract

Our primary aim, in this paper, is to propose and investigate, for the first time, the application of Data Envelopment Analysis (DEA) technique in assessing Iranian public universities. We provide an analysis on the importance of the stakeholder’s perspective on the structure of DEA and the variations of efficiency results. For illustrations, we perform efficiency analysis on a sample of public universities in Iran from three different perspectives of importance, i.e., teaching quality, research productivity, and cost efficiency by using available data.

Keywords

Main Subjects


[1] Abbott M., Doucouliagos C., (2003),The efficiency of Australian Universities: A Data Envelopment
Analysis;Economics of Education review 22;89-97.
[2] Ahn T., ArnoldV., CharnesA., CooperW. W. (1989), DEA and ratio efficiency analyses forpublic
institutions of higher learning in Texas;Research in Governmental andNonprofit Accounting 5; 165–
185.
[3] Ahn T., Charnes A., Cooper W.W. (1988),Some statistical and DEA evaluations of relative
efficiencies of public and private institutions of higher learning;Socio-Economic Planning Sciences22;
259–69.
[4] Avkiran NK. (2001), Investigating technical and scale efficiencies of Australian universities through
data envelopmentanalysis; Socio-Economic Planning Sciences35; 57–80.
[5] Beasley J.E. (1995),Determining teaching and research efficiencies; Journal of the Operational
Research Society46(4); 441–52.
[6] Celik O., AlaattinEcer. (2009), Efficiency in accounting education: evidence from Turkish
Universities; Critical Perspectives on Accounting20;614–634.
[7] Charnes A, Cooper W. W., Rhodes E. (1979), Short Communication: Measuring Efficiency of
Decision Making Units; European Journal of Operational Research 3; 339.
[8] Cook W.D., Liang L., Zhu J.(2009), Measuring Performance of Two-Stage Network Structures by
DEA: A Review and Future Perspective; Omega doi:10.1016/j.omega2009.12.001.
[9] Cook W.D., SeifordL.M. (2009), Data Envelopment Analysis (DEA)-Thirty Years on; EJOR 192; 1-
17.
[10] Cooper W.W.,SeifordL. M., Karou Tone (2006), Introduction to Data Envelopment Analysis and its
uses with DEA-Solver Software and References;Springer; New York.
[11] Dyson.R.G.,AllenR.,CamanhoA.S, PondinovskiV.V.,SaricoC.S.,ShaleE.A.(2001), Pitfall and protocols
in DEA; European Journal of Operational Research 132; 245-259.
[12] Giannoulis, C., Alessio Ishizaka.(2010), A Web-based decision support system with ELECTRE III for
a personalized ranking of British universities; Decision Support Systems48; 488–497.
[13] Glass, J. Colin, Gillian McCallion, Donal G. McKillop, SyamarlahRasaratnam, Karl S. Stringer.
(2006), Implications of variant efficiency measures for policy evaluations in UK higher education;
Socio-Economic Planning Sciences 40;119–142.

[14] Glass J.C., McKillop DG, O’Rourke G. (1998), A cost indirect evaluation of productivity change in
UK universities; Journal of Productivity Analysis10; 153–75.
[15] Johnes G.(1996), Multiproduct cost functions and the funding of tuition in UK universities; Applied
Economics Letters 3; 557–61.
[16] Johnes J.(2006), Data envelopment analysis and its application to the measurement ofefficiency in
higher education; Economics of Education Review 25 (3); 273–288.
[17] Johnes J., Johnes G. (1995), Research funding and performance in U.K. university departments of
economics: a frontier analysis; Economics of Education Review 14; 301–14.
[18] Johnes J., YuL. (2008), Measuring the research performance of Chinese higher educationinstitutions
using data envelopment analysis; China Economic Review 19 (4); 679–696.
[19] Kao H. (2008), Hsi-Tai Hung, Efficiency analysis of university departments: An empirical study;
Omega 36; 653 – 664.
[20] Katharaki and Katharakis (2010), A comparative assessment of Greek universities’ efficiency using
quantitative analysis; International Journal of Educational Research 49; 115–128.
[21] Kong.W.,Fu.T. (2012), Assessing the performance of business colleges in Taiwan using data
envelopment analysis and student based value-added performance indicators; Omega 40; 541–549.
[22] Liu. J. Lu.L,Lu.W,Lin.B. (2012), A Survey of DEA Applications; Omega; Accepted Manuscript.
[23] LukmanR,Krajnc D. G. (2010), University ranking using research, educational and environmental
indicators, Journal of Cleaner Production 18; 619–628.
[24] Mehregan M.R. (2009), Quantitative Models for Organizational Performance Evaluation, University of
Tehran Publishing House, (in Farsi).
[25] Meng W., Zhang D.,Qi L., Liu W. (2008), Two-level DEA Approaches in research Evaluation;
Omega; 950-957.
[26] Monfared M.A.S., Gharneh N.S.,MirkhaniS.N. (2006), Ranking Analysis and Modeling of State Run
Universities; ScientiaIranica13(1); 91-104.
[27] Monfared M.A.S.,Mahdavi F. (2004), Measurement of College Quality Using 3 Different MCDM
Methods, Proceeding of 3rd International Conference on Industrial Engineering, Amirkabir University
of Technology; 63-83, (in Farsi).
[28] Muñiz M.A. (2002), Separating managerial inefficiency and external conditions in data envelopment
analysis; European Journal of Operational Research; 143:625–43.
[29] Sarrico C. S., Dyson R. G. (2003), Restricting virtual weights in data envelopment analysis; European
Journal of Operational Research159(1)1; 17–34.
[30] Seiford L.M. (1996), Data envelopment analysis: the evolution of the state of the art (1978–1995);
Journal of Productivity Analysis;7:99–137.
[31] Sinuany-Stern Z. (1994), Mehrez A., Barboy A., Academic departments efficiency via DEA;
Computers and Operations Research;21:543–56.
[32] Tam M. (2001), Measuring Quality and Performance in Higher Education; Quality in Higher
Education7(1).
[33] The league table of UK universities, The Complete University Guide,
http://www.thecompleteuniversityguide.co.uk/single.htm?ipg=6310#HowtheLeagueTableworks, 2009.