Estimating Malmquist Productivity Index of Decision Making Units using Artificial Neural Networks

In this paper we examined the capability of Artificial Neural Networks (ANNs) in estimating Malmquist Productivity Index (MPI) for Decision Making Units (DMUs). An algorithm is proposed using DEA and ANN for efficiency analysis and MPI estimation. ANN is used for estimating the coordination of DMUs on the efficiency frontier for future. Then considering the past and future frontiers, the efficiency score of DMUs is computed using DEA models. At the end the MPI is calculated for each DMU. So by these results the managers could take new strategies for improving the productivity of their organizations.

کلیدواژه ها:

Malmquist Productivity Index ، Data Envelopment Analysis and Artificial Neural Networks