机构:
Univ Massachusetts, Coll Management, Lowell, MA 01845 USAWorcester Polytech Inst, Dept Management, Worcester, MA 01609 USA
Chen, Yao
[2
]
Liang, Liang
论文数: 0引用数: 0
h-index: 0
机构:
Univ Sci & Technol China, Sch Business, Hefei 230026, Anhui, Peoples R ChinaWorcester Polytech Inst, Dept Management, Worcester, MA 01609 USA
Liang, Liang
[3
]
Zhu, Joe
论文数: 0引用数: 0
h-index: 0
机构:
Worcester Polytech Inst, Dept Management, Worcester, MA 01609 USA
Natl Cheng Kung Univ, Dept Ind & Informat Management, Tainan 70101, TaiwanWorcester Polytech Inst, Dept Management, Worcester, MA 01609 USA
Zhu, Joe
[1
,4
]
机构:
[1] Worcester Polytech Inst, Dept Management, Worcester, MA 01609 USA
[2] Univ Massachusetts, Coll Management, Lowell, MA 01845 USA
[3] Univ Sci & Technol China, Sch Business, Hefei 230026, Anhui, Peoples R China
[4] Natl Cheng Kung Univ, Dept Ind & Informat Management, Tainan 70101, Taiwan
Data envelopment analysis (DEA);
Efficiency;
Intermediate measure;
Two-stage;
DATA ENVELOPMENT ANALYSIS;
EFFICIENCY;
D O I:
10.1016/j.ejor.2007.11.040
中图分类号:
C93 [管理学];
学科分类号:
12 ;
1201 ;
1202 ;
120202 ;
摘要:
Data envelopment analysis (DEA) is a linear programming problem approach for evaluating the relative efficiency of peer decision making units (DMUs) that have multiple inputs and outputs. DMUs can have a two-stage structure where all the outputs from the first stage are the only inputs to the second stage, in addition to the inputs to the first stage and the outputs from the second stage. The outputs from the first stage to the second stage are called intermediate measures. This paper examines relations and equivalence between two existing DEA approaches that address measuring the performance of two-stage processes. (C) 2007 Published by Elsevier B.V.