.png){kind=icon}
Return
Additive super-efficiency in integer-valued data envelopment analysis
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ejor.2011.10.023.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Conventional data envelopment analysis (DEA) methods assume that input and output variables are continuous. However, in many real managerial cases, some inputs and/or outputs can only take integer values. Simply rounding the performance targets to the nearest integers can lead to misleading solutions and efficiency evaluation. Addressing this kind of integer-valued data, the current paper proposes models that deal directly with slacks to calculate efficiency and super-efficiency scores when integer values are present. Compared with standard radial models, additive (super-efficiency) models demonstrate higher discrimination power among decision making units, especially for integer-valued data. We use an empirical application in early-stage ventures to illustrate our approach. (C) 2011 Elsevier B.V. All rights reserved.
Keywords:
Data envelopment analysis
Early-stage ventures
Integer-valued data
Slacks
Super-efficiency
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
6
Papers:
2.2W
Citations:
6.4W
Organization
Cited Papers
.png){kind=icon}
ShareSaveShareSaveShareSaveShareSave
View more