Data filtering in data envelopment analysis

Wen-Chih Chen*

*Corresponding author for this work

研究成果: Paper同行評審

摘要

Data envelopment analysis (DEA) is an useful performance assessment tool, which is able to consider multiple inputs and outputs simultaneously while requiring neither a priori weights nor a pre-specified functional form. To conduct a successful DEA study, data quality plays a key role but has not drawn much attention. Outlier detection not only identifies the suspicious data point to avoid erroneous conclusion, but also possibly leads to the discovery of unexpected knowledge. The objective of the paper is to develop a comprehensive data filtering scheme to DEA. We first examine several preliminary outlier detection procedures in DEA and discuss some unsolved issues. Then we develop the inefficient outlier detection which is yet unsolved. Besides providing a solution, this method is funded on the ground of DEA theory.

原文English
頁面1521-1530
頁數10
出版狀態Published - 1 十二月 2006
事件36th International Conference on Computers and Industrial Engineering, ICC and IE 2006 - Taipei, Taiwan
持續時間: 20 六月 200623 六月 2006

Conference

Conference36th International Conference on Computers and Industrial Engineering, ICC and IE 2006
國家Taiwan
城市Taipei
期間20/06/0623/06/06

指紋 深入研究「Data filtering in data envelopment analysis」主題。共同形成了獨特的指紋。

引用此