Evaluation efficiency of the internal structure of decision making units in the past, present and future using dynamic network data envelopment analysis and artificial neural network
Subject Areas :javad niknafs 1 , mphammadali keramati 2 , jalal haghighatmonfared 3
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Keywords: Network data envelopment analysis, dynamic network data envelopment analysis, artificial neural network, evaluation efficiency , bank,
Abstract :
Network data envelopment analysis models and dynamic network data envelopment analysis models cannot evaluated the future performance of the internal structure of decision-making units .In other words, all NDEA and DNDEA models evaluate the past performance of their DMUs and their internal structure, and measure their efficiency and inefficiency, and ultimately rank them based on that assessment .In this paper, we are going to evaluation the future efficiency of deposit and lending sections in bank branches. In order to notified inefficiencies in the internal structure of a unit before the occurrence, we will prevent it.This approach can change the role of managers from the evaluator to the planner .First, using the literature of the subject and opinion of the experts, the structure of the bank branches and the network variables were determined .Then, the values of variables are forecasted using the artificial neural network for the next two periods.Finally, a DNDEA model is formulated using the values of past periods and predicted values.Using its efficiency, its branches and its internal structure have been evaluated in the past, present and future.
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