An ensemble model for efficiency evaluation of enterprise performance based on evidential reasoning approach

Abstract

Performance evaluation is one of the most important standards to measure the competitiveness and productivity of enterprises. Although existing studies could obtain the specific values of enterprises performance based on historical data, they usually failed to effectively evaluate enterprises performance in the consideration of different indicators. Meanwhile, as the characteristics of existing performance evaluation models are uneven, how to choose a reasonable data envelopment analysis (DEA) model for enterprises performance evaluation must be considered. Therefore, a new ensemble model on the basis of homogeneous, heterogeneous, and hybrid efficiency evaluation together with the evidential reasoning (ER) approach is proposed in this study for enterprises performance evaluation, so called the ER-based ensemble model. The ER-based ensemble model can overcome the inconsistency results caused by the application of different indicators and different DEA models. In case study, 40 state-own holding enterprises in China are selected and all these enterprises are evaluated and ranked using the integrated efficiency obtained from the ER-based ensemble model. Comparative analysis demonstrates that the ER-based model is better than some traditional efficiency evaluation models in enterprises performance evaluation and performance ranking.