Evaluating the Efficiency of DMUs with PCA and an Application in Real Data Set of Iranian Banks

This paper proposes a method for evaluating the efficiency of decision making units(DMUs) by using principal component analysis. This efficiency deals with undesirableoutputs and simultaneously reduces the dimensionality of data set. First, we change theundesirable outputs to be desirable by reversing. Then we do PCA on the ratios of a singledesirable output to a single input.In order to reduce the dimensionality of data set, the required principal components areselected out of the generated ones according to the lowest eigenvalues. Finally these chosen principal components are treated as virtual data set into data envelopment analysis(DEA). Then the utility of proposed approach is applied to real data set of some branchesof an Iranian bank.