Discriminating DEA efficient candidates by considering their least relative total scores

Ying-Ming Wang; Kwai-Sang Chin

doi:10.1016/j.cam.2006.06.012

Discriminating DEA efficient candidates by considering their least relative total scores

Ying-Ming Wang
, Kwai-Sang Chin

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

35 Citations (Scopus)

Abstract

Data envelopment analysis very often identifies more than one candidate in a voting system to be DEA efficient. In order to choose a winner from among the DEA efficient candidates, this paper proposes a new method that discriminates the DEA efficient candidates by considering their least relative total scores. The proposed method is illustrated with two numerical examples and proves to be effective and practical. © 2006 Elsevier B.V. All rights reserved.

Original language	English
Pages (from-to)	209-215
Journal	Journal of Computational and Applied Mathematics
Volume	206
Issue number	1
DOIs	https://doi.org/10.1016/j.cam.2006.06.012
Publication status	Published - 1 Sept 2007

Research Keywords

Data envelopment analysis (DEA)
Preference ranking
The least relative efficiency
Voting

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AU - Chin, Kwai-Sang

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N2 - Data envelopment analysis very often identifies more than one candidate in a voting system to be DEA efficient. In order to choose a winner from among the DEA efficient candidates, this paper proposes a new method that discriminates the DEA efficient candidates by considering their least relative total scores. The proposed method is illustrated with two numerical examples and proves to be effective and practical. © 2006 Elsevier B.V. All rights reserved.

AB - Data envelopment analysis very often identifies more than one candidate in a voting system to be DEA efficient. In order to choose a winner from among the DEA efficient candidates, this paper proposes a new method that discriminates the DEA efficient candidates by considering their least relative total scores. The proposed method is illustrated with two numerical examples and proves to be effective and practical. © 2006 Elsevier B.V. All rights reserved.

KW - Data envelopment analysis (DEA)

KW - Preference ranking

KW - The least relative efficiency

KW - Voting

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U2 - 10.1016/j.cam.2006.06.012

DO - 10.1016/j.cam.2006.06.012

M3 - RGC 21 - Publication in refereed journal

SN - 0377-0427

VL - 206

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EP - 215

JO - Journal of Computational and Applied Mathematics

JF - Journal of Computational and Applied Mathematics

IS - 1

ER -

Discriminating DEA efficient candidates by considering their least relative total scores

Abstract

Research Keywords

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