benchmark forecasting in data envelopment analysis for decision making units

The purpose of this paper is to develop a benchmark model for efficiency evaluation in future. with forecasting the efficiency of organizations, managers could plan and determine that strategy. one of the most important methods for evaluating decision making units (dmus) is dea. although dea is a powerful method in evaluating dmus, it does have some limitations. one of the most important limitations of this method is the result of the evaluation is that the efficiency calculated was based on previously existing data and the results are not proper for forecasting the future changes regarding inputs and outputs required for the units to be considered as efficient. the aim of this paper is to propose a model to enlighten and forecast how inputs and outputs alter through system dynamics and simulation. for this purpose, we design feedback loops for forecasting inputs and outputs. then we use ccr model to forecast the efficiency.