.png){kind=icon}
.png){kind=icon}
Return
Within-group common benchmarking using DEA
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ejor.2016.06.074.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Cook and Zhu (2007) extend the DEA structure to apply to the more general setting where DMUs fall into distinct groups whose members experience similar circumstances. As these authors state, in those cases the DMUs of a group are to be treated uniformly in terms of multiplier allocation. In the same contextual setting, the present paper proposes a DEA-based approach which is primarily focused on benchmarking and the setting of targets. Models are developed for situations where a common best-practice frontier is identified for a group of DMUs as a result of the choice of facets that yields the closest targets. The example examined is concerned with the evaluation of research performance of Spanish universities, by assuming a common framework for the benchmarking of those in the same autonomous region. (C) 2016 Elsevier B.V. All rights reserved.
Keywords:
DEA
Groups
Benchmarking
Target setting
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
View more organizations