Evaluating the Efficiency of Firms with Negative Data in Multi-Period Systems: An Application to Bank Data

Data envelopment analysis (dea) is a mathematical technique to evaluate the performance of firms with multiple inputs and outputs. in conventional dea models, the efficiency scores of decision making units (dmus) with non-negative inputs and outputs are evaluated in a special period of time. however, in the real world there are situations wherein performance of firms must be evaluated in multiple periods of time while negative data are present; for this matter the current paper proposes an approach for assessing the efficiency of multi-period systems in the presence of positive and negative measures. to illustrate, the average efficiency of firms with some negative measures are calculated in multi-period production systems. the suggested approach utilizes the semi-oriented radial measure (sorm) model (emrouznejad et al. [4]) for incorporating some negative factors (inputs and outputs) and determining the efficiency of multi-period production systems. a real world data set related to banking sector is used to illustrate and clarify the proposed approach.