A distribution-free approach to stochastic efficiency measurement with inclusion of expert knowledge

This paper proposes a new efficiency benchmarking methodology that is capable of incorporating probability while still preserving the advantages of a distribution-free and nonparametric modeling technique. this new technique developed in this paper will be known as the dea-chebyshev model. the foundation of dea-chebyshev model is based on the model pioneered by charnes,cooper,and rhodes in 1978 known as data envelopment analysis (dea). the combination of normal dea with dea-chebyshev frontier (dcf) can successfully provide a good framework for evaluation based on quantitative data and qualitative intellectual management knowledge. the simulated dataset was tested on dea-chebyshev model. it has been statistically shown that this model is effective in predicting a new frontier,whereby dea efficient units can be further differentiated and ranked. it is an improvement over other methods,as it is easily applied,practical,not computationally intensive,and easy to implement. © 2013 kerry khoo-fazari et al.