标题：Increasing discrimination of DEA evaluation by utilizing distances to anti-efficient frontiers
作者：Shen, Wan-fang; Zhang, Da-qun; Liu, Wen-bin; Yang, Guo-liang
作者机构：[Shen, Wan-fang] Shandong Univ Finance & Econ, Sch Math & Quantitat Econ, Jinan 250014, Peoples R China.; [Zhang, Da-qun] Texas A&M Univ, Accounting 更多
通讯作者地址：[Yang, GL]Chinese Acad Sci, Inst Policy & Management, Beijing 100190, Peoples R China.
来源：COMPUTERS & OPERATIONS RESEARCH
关键词：Data envelopment analysis; Discrimination; Efficient frontier;; Anti-efficient frontier
摘要：This paper develops three DEA performance indicators for the purpose of performance ranking by using the distances to both the efficient frontier and the anti-efficient frontier to enhance discrimination power of DEA analysis. The standard DEA models and the Inverted DEA models are used to identify the efficient and anti-efficient frontiers respectively. Important issues like possible intersections of the two frontiers are discussed. Empirical studies show that these indicators indeed have much more discrimination power than that of standard DEA models, and produce consistent ranks. Furthermore, three types of simulation experiments under general conditions are carried out in order to test the performance and characterization of the indicators. The simulation results show that the averages of both the Pearson and Spearman correlation coefficients between true efficiency and indicators are higher than those of true efficiency and efficiency scores estimated by the BCC model when sample size is small. (C) 2016 Elsevier Ltd. All rights reserved.