The Interval Efficiency Evaluation Model Based on Incentive Compatibility

Abstract

Data envelopment analysis (DEA) is a method of measuring the efficiency of peer decision-making units (DMUs). Conventional DEA evaluates the performance of each DMU only from the optimistic point of view. In this paper, the efficiency of a DMU is measured by using an interval efficiency evaluation model based on incentive compatibility, which considers both the optimistic and pessimistic attitude of the DMU during the evaluation process. The efficiency of a DMU, which is computed by combining the two attitudes, can be expressed by interval and provide a more reasonable assessment of the DMU. The lower bound of the interval efficiency are computed by measuring the worst relative efficiency of the ADMU, which is between the results of bounded DEA models from the optimistic or pessimistic points of view. Two numerical examples were examined using the proposed interval DEA model to show its potential application and validity.

Keywords

• Interval linear programming
• data envelopment analysis
• interval ranking