A new reliable performance evaluation model: IFB-IER–DEA

Abstract

Data envelopment analysis (DEA) is a well-known performance evaluation model for measuring the relative efficiency of multiple homogeneous decision making units (DMUs). Input/output of the DMUs can be uncertain especially when they are obtained from subjective human judgments. In this paper, Evidential Reasoning approach with interval assessment score and linguistic interval fuzzy belief degree (IFB-IER approach) is proposed to deal with the uncertainties. This approach does not restrict experts to give a precise point and provides more reliable and realistic performance evaluation. Eventually, the IFB-IER data are converted to standard interval data. Then, the efficiency of the DMUs is calculated using interval DEA model and Anderson Peterson model is applied to rank them. Finally, a numerical example is given to illustrate the validity and applicability of the proposed model.