Comparative Analysis of the Public Funding for Greek Universities: An Ordinal DEA/MCDM Approach

Authors: Yiannis Smirlis, Dimitris K. Despotis

Abstract:

This study performs a comparative analysis of the 21 Greek Universities in terms of their public funding, awarded for covering their operating expenditure. First it introduces a DEA/MCDM model that allocates the fund into four expenditure factors in the most favorable way for each university. Then, it presents a common, consensual assessment model to reallocate the amounts, remaining in the same level of total public budget. From the analysis it derives that a number of universities cannot justify the public funding in terms of their size and operational workload. For them, the sufficient reduction of their public funding amount is estimated as a future target. Due to the lack of precise data for a number of expenditure criteria, the analysis is based on a mixed crisp-ordinal data set.

Keywords: Data envelopment analysis, Greek universities, operating expenditures, ordinal data.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1086647

References:

[1] A. Charnes, W.W. Cooper and E. Rhodes, "Measuring the efficiency of decision-making units”, European Journal of Operational Research, Vol. 2, 1978, pp. 429–444.
[2] D. Bouyssou, "Using DEA as a tool for MCDM: some remarks”, Journal of the Operational Research Society, Vol.50, 1999, pp. 974- 978.
[3] M. Katharaki, G. Katharakis, "A comparative assessment of Greek universities’ efficiency using quantitative analysis”, International Journal Of Educational Research, Vol. 49, 2010, pp. 115-128.
[4] M. Aubyn, A. Pina, F. Garcia and J. Pais, "Study on the efficiency and effectiveness of public spending on tertiary education”, Economic Papers 390. European Commission Directorate-General for Economic and Financial Affairs Publications, 2009, (http://ec.europa.eu/economy_finance/publications/publication16267_en .pdf).
[5] C. Salerno, "Using Data Envelopment Analysis to Improve Estimates of Higher Education Institution’s Per‐student Education Costs”, Education Economics, vol. 14 (3), 2006, pp. 281–295.
[6] M. Abbott M., C. Doucouliagos, "The efficiency of Australian universities: a data envelopment Analysis”, Economics of Education Review, vol.22, 2003 pp. 89–97.
[7] T. Sav, "Managing Operating Efficiencies of Publicly Owned Universities: American University Stochastic Frontier Estimates Using Panel Data”, Advances in Management & Applied Economics, vol. 2 (1), 2012, pp. 1-23.
[8] B. Casua , E. Thanassoulis "Evaluating cost efficiency in central administrative services in UK universities”, Omega vol. 34, 2006, pp. 417 – 426.
[9] B. Taylor, G. Harris, "Relative efficiency among South African Universities: A data envelopment analysis”, Higher Education vol. 47, 2004, pp.73–89.
[10] W.D. Cook, M. Kress, "A multiple criteria composite index model for quantitative and qualitative data”, European Journal of Operations Research, vol. 78, 1994, pp.367-379.
[11] D.K. Despotis, Y.G. Smirlis "Data envelopment analysis with imprecise data”, European Journal of Operational Research vol. 140, 2002, pp.24–36.
[12] W.D. Cook, M. Kress, "A multiple criteria decision model with ordinal preference data”, European Journal of Operational Research vol. 54, 1991, pp. 191-198.
[13] W.D. Cook , M. Kress, L.M. Sheiford, "Data Envelopment Analysis in the Presence of Both Quantitative and Qualitative Factors”, Journal of Operational Research Society, vol. 47(7), 1996, pp.945-953.
[14] Lotfi F Hosseinzadeh, GR Jahanshahloo, A.Memariani, "Method for finding common set of weights by multiple objective programming in data envelopment analysis”, Southwest Journal of Applied Mathematics vol.1, 2000, pp.44–54
[15] C. Kao , H-T Hung, "Data Envelopment Analysis with common weights : the compromise solution approach”, Journal of Operational Research Society vol.56, 2005, pp.1196-1203
[16] D.K. Despotis "Improving the discriminating power of DEA: focus on globally efficient units”. Journal of Operational Research Society, vol.53, 2002, pp.314–323
[17] W.D. Cook, M. Kress, "Characterizing an equitable allocation of shared costs: a DEA approach”, European Journal of Operational Research, 119, 1999, pp.652–661
[18] W.D. Cook, J. Zhu, "Allocation of shared costs among decision making units: a DEA approach”. Computers and Operations Research, vol.32, 2005, pp. 2171–2178
[19] R. Lin, "Allocating fixed costs or resources and setting targets via data envelopment analysis”, Applied Mathematics and Computation, vol. 217 (13), 2011, pp. 6349–6358
[20] Lotfi F. Hosseinzadeh, A.Hatami-Marbini, P.J.Agrell, N.Aghayi, K. Gholami, "Allocating fixed resources and setting targets using a common-weights DEA approach”, Computers and Industrial Engineering, vol. 64 (2) , 2013, pp. 631-640