How to cite this paper
Azizi, Z & Paktinat, M. (2013). A DEA application for analyzing investment activities in higher educational organizations.Management Science Letters , 3(2), 435-442.
Refrences
Avkiran, N. K. (2010). Association of DEA super-efficiency estimates with financial ratios:
Investingating the case for Chinese banks. Omega, 39(3), 323–334.
Anderson, P., & Peterson, N. C. (1993). A procedure for ranking efficient units in data envelopment
analysis. Management Science, 39(10), 1261-1264.
Cook, W. D., & Kress, M. (1990). A data envelopment model for aggregating preference rankings.
Management Science, 36, 1302–1310.
Charnes A, Cooper, W. W., Rhodes, E. (1978). Measuring the efficiency of decision making units.
European Journal of the Operational Research, 2, 429–44.
Charnes A, Cooper W. W., Lewin, A., Seiford, L. M. (1994). Data envelopment analysis: theory,
methodology and applications. Massachusetts: Kluwer Academic Publishers.
Chen, S. J., & Hwang, C. L. (1992). Fuzzy multiple attribute decision making: Methods and
applications. Berlin: Springer-Verlag.
Fallah, M., Aryanezhadb, M.B., Najafi, S.E., & Shahsavaripour, N. (2011). An empirical study on
measuring the relative efficiency using DEA method: A case study of bank industry. Management
Science Letters, 1(1), 49-56.
Lin, T. T., Lee, Ch-Ch., & Chiu, T-F. (2009). Application of DEA in analyzing a bank & apos; s operating
performance. Expert Systems with Applications, 36(5), 8883-8891.
Saaty, T. L. (1992). How to make a decision: the analytic hierarchy process. European Journal of
Operational Research, 48, 9–26.
Staub, R. B., Da Silva e Souza, G. & Tabak, B. M. (2010). Evolution of bank efficiency in Brazil: A
DEA approach. European Journal of Operational Research, 202(1), 204-213.
Yang, J.B., Wong, B.Y.H., Xu, D.L., Liu, X.B. & Steuer, R.E. (2010). Integrated bank performance
assessment and management planning using hybrid minimax reference point – DEA approach.
European Journal of Operational Research, 207(3), 1506–1518.
Zaheri, F., Farughi, H., Soltanpanah, H., Alaniazar, S., & Naseri, F. (2012). Using multiple criteria
decision making models for ranking customers of bank network based on loyalty properties in
weighted RFM model. Management Science Letters, 2(1), 697-704.
Investingating the case for Chinese banks. Omega, 39(3), 323–334.
Anderson, P., & Peterson, N. C. (1993). A procedure for ranking efficient units in data envelopment
analysis. Management Science, 39(10), 1261-1264.
Cook, W. D., & Kress, M. (1990). A data envelopment model for aggregating preference rankings.
Management Science, 36, 1302–1310.
Charnes A, Cooper, W. W., Rhodes, E. (1978). Measuring the efficiency of decision making units.
European Journal of the Operational Research, 2, 429–44.
Charnes A, Cooper W. W., Lewin, A., Seiford, L. M. (1994). Data envelopment analysis: theory,
methodology and applications. Massachusetts: Kluwer Academic Publishers.
Chen, S. J., & Hwang, C. L. (1992). Fuzzy multiple attribute decision making: Methods and
applications. Berlin: Springer-Verlag.
Fallah, M., Aryanezhadb, M.B., Najafi, S.E., & Shahsavaripour, N. (2011). An empirical study on
measuring the relative efficiency using DEA method: A case study of bank industry. Management
Science Letters, 1(1), 49-56.
Lin, T. T., Lee, Ch-Ch., & Chiu, T-F. (2009). Application of DEA in analyzing a bank & apos; s operating
performance. Expert Systems with Applications, 36(5), 8883-8891.
Saaty, T. L. (1992). How to make a decision: the analytic hierarchy process. European Journal of
Operational Research, 48, 9–26.
Staub, R. B., Da Silva e Souza, G. & Tabak, B. M. (2010). Evolution of bank efficiency in Brazil: A
DEA approach. European Journal of Operational Research, 202(1), 204-213.
Yang, J.B., Wong, B.Y.H., Xu, D.L., Liu, X.B. & Steuer, R.E. (2010). Integrated bank performance
assessment and management planning using hybrid minimax reference point – DEA approach.
European Journal of Operational Research, 207(3), 1506–1518.
Zaheri, F., Farughi, H., Soltanpanah, H., Alaniazar, S., & Naseri, F. (2012). Using multiple criteria
decision making models for ranking customers of bank network based on loyalty properties in
weighted RFM model. Management Science Letters, 2(1), 697-704.