An objective-free outlying point detection model in data envelopment analysis

Chin Chia Kuo, Wen-Chih Chen*

*Corresponding author for this work

研究成果: Article同行評審

1 引文 斯高帕斯(Scopus)

摘要

Data envelopment analysis (DEA) is a mathematical programming approach for benchmarking. Using extreme observations to identify superior performance makes DEA vulnerable to outliers. While there are many studies on detecting outliers for DEA, most focus on specific applications and objectives, e.g. orientation, and thus have limitations. We address the limits of conventional objective-dependent approaches and the need for an objective-free outlier detection mechanism, and propose an outlier detecting method that requires no pre-specified objectives. In addition to allowing for the identification of outliers, the method described is consistent with a relaxed set of DEA axioms.

原文English
頁(從 - 到)294-303
頁數10
期刊Journal of the Chinese Institute of Industrial Engineers
27
發行號4
DOIs
出版狀態Published - 1 七月 2010

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