[1] Aigner, D.J., & Chu, S.F. (1968) On Estimating the Industry Production Function. American Economic Review, 58, 826-839.
[2] Aigner, D., Lovell, C. K., & Schmidt, P. (1977). Formulation and estimation of stochastic frontier production function models. Journal of Econometrics, 6(1), 21–37.
[3] Amirteimoori, A., Kordrostami, S., & Nasrollahian, P. A. (2017). Method for solving super-Efficiency infeasibility by adding virtual DMUs with mean values. Iranian journal of management studies, 10(4), 905-916.
[4] Banker, R. D., Charnes, A., &Cooper, W. W. (1984). Some models for estimating technical and scale inefficiency in data envelopment analysis. Management Science, 30, 1078–1092.
[5] Battese, G., & Coelli, T. (1992). Frontier production functions, technical efficiency and panel data: With application to paddy farmers in India. Journal of Productivity Analysis, 3, 153–169.
[6] Charnes, A., Cooper, W.W., & Rhodes, E. (1978). Measuring the efficiency of decision making
units. European Journal of Operational Research, 2(6), 429–444.
[7] Coelli, T., Rao, D.S.P., & Battese, G.E. (1998). An introduction to efficiency and productivity analysis. Boston: Kluwer Academic.
[8] Deprins, D., Simar, L., and Tulkens, H. (1984). Measuring labor-efficiency in post office. In North Holland, editor, The Performance of Public Enterprises. Amsterdam: M. Marchand and P. Pestieau and H. Tulkens.
[9] Didehkhani, H., Hosseinzadeh Lotfi, F., Sadi-Nezhad, S. (2019). Practical benchmarking in DEA using artificial DMUs. Journal of Industrial Engineering International, 15, 293–301.
[10] Fethi, M., Jackson, P. M., & Weyman-Jones, T. G. (2001). European airlines: a stochastic dea study of efficiency with market liberalisation. Tech. rep., University of Leicester Efficiency and Productivity Research Unit
[11] Farrell, M. J. (1957). The measurement of productive efficiency.Journal of the Royal Statistical Society, 120(3), 253–281.
[12] Greene, W. H. (1980). Maximum likelihood estimation of econometric frontier functions. Journal of Econometrics, 13(1), 27–56.
[13] Greene, W. H. (1990). A Gamma-distributed stochastic frontier model. Journal of Econometrics, 46, 141–163.
[14] Greene, W. H. (2008). Econometric Analysis, sixth edn. Pearson Prentice Hall.
[15] Krivonozhko, V. E., Forsund, F. R. and Lychev, A. V. (2015). On comparison of different sets of units used for improving the frontier in DEA models. Ann. Operat. Res. Doi: 10.1007/s10479 - 015- 1875-8
[16] Krivonozhko, V. E., Forsund, F. R. and Lychev, A. V. (2016). Improving the Frontier in DEA Models. Doklady Mathematics, 94(3), 715–719. Doi: 10.1134/S1064562416060181
[17] Land, K. C., Lovel CAK, & Thore, S. (1993). Chance-constrained data envelopment analysis. Managerial and Decision Economics, 14, 541–554.
[18] Lovell CAK (1993). Production Frontiers and Productive Efficiency. In: Fried H, Lovell CAK, Schmidt S (eds) The Measurement of Productive Efficiency. New York: Techniques and Applications, Oxford University Press.
[19] Olesen, O. B., & Petersen, N.C. (1995). Chance Constrained Efficiency Evaluation. Management Science, 41, 442-457.
[20] Bogetoft, P., & Otto, L. (2011). Benchmarking with DEA, SFA, and R. New York: Springer.
[21] Sexton, T.R., Silkman, R.H., & Hogan, A.J. (1986(. Data envelopment analysis: Critique and extensions. In: Silkman, R.H. (Ed.), Measuring Efficiency: An Assessment of Data Envelopment Analysis. Jossey-Bass, San Francisco, CA, 73–105.
[22] Sowlati, T., &Paradi, J. C. (2004). Establishing the “practical frontier” in data envelopment analysis. Omega, 32, 261–272.