This study proposes a non-parametric efficiency
frontier analysis method based on the adaptive neural network
technique for measuring efficiency as a complementary tool for
the common techniques of the efficiency studies in the previous
studies. The proposed computational method is able to find a
stochastic frontier based on a set of input–output observational
data and do not require explicit assumptions about the
function structure of the stochastic frontier. In this algorithm,
for calculating the efficiency scores, a similar approach to
econometric methods has been used. Moreover, the effect of
the return to scale of decision making unit (DMU) on its
efficiency is included and the unit used for the correction is
selected by notice of its scale (under constant return to scale
assumption). Also for increasing DMUs’ homogeneousness,
Fuzzy C-means method is used to cluster DMUs. An example
using real data is presented for illustrative purposes. In the
application to the wireless telecommunication and auto
industries, we find that the neural network provide more
robust results and identifies more efficient units than the
conventional methods since better performance patterns are
explored .
کلید واژگان :
Performance assessment; Neural networks; Fuzzy C-mean clustering; Telecommunication; Auto Industries
