Measuring the performances of decision-making units using geometric average efficiency

Y. M. Wang; K. S. Chin; J. B. Yang

doi:10.1057/palgrave.jors.2602205

Measuring the performances of decision-making units using geometric average efficiency

Y. M. Wang, K. S. Chin, J. B. Yang

Research output: Contribution to journal › Article › peer-review

Abstract

The performances of decision-making units (DMUs) can be measured from two different points of view: optimistic or pessimistic, which leads to two different efficiencies for each DMU: the best relative efficiency and the worst relative efficiency. The conventional data envelopment analysis (DEA) considers only the best relative efficiency. It is argued that the two different efficiencies should be considered together and any approach considers only one of them is biased. This paper proposes to integrate the two different efficiencies into a geometric average efficiency, which measures the overall performance of each DMU. It is found that the geometric average efficiency has better discriminating power than either of the two efficiencies. This is illustrated by two numerical examples. © 2007 Operational Research Society Ltd. All rights reserved.

Original language	English
Pages (from-to)	929-937
Number of pages	8
Journal	Journal of the Operational Research Society
Volume	58
Issue number	7
DOIs	https://doi.org/10.1057/palgrave.jors.2602205
Publication status	Published - Jul 2007

Keywords

Data envelopment analysis
Discriminating power
Geometric average efficiency
Ranking

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10.1057/palgrave.jors.2602205

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title = "Measuring the performances of decision-making units using geometric average efficiency",

abstract = "The performances of decision-making units (DMUs) can be measured from two different points of view: optimistic or pessimistic, which leads to two different efficiencies for each DMU: the best relative efficiency and the worst relative efficiency. The conventional data envelopment analysis (DEA) considers only the best relative efficiency. It is argued that the two different efficiencies should be considered together and any approach considers only one of them is biased. This paper proposes to integrate the two different efficiencies into a geometric average efficiency, which measures the overall performance of each DMU. It is found that the geometric average efficiency has better discriminating power than either of the two efficiencies. This is illustrated by two numerical examples. {\textcopyright} 2007 Operational Research Society Ltd. All rights reserved.",

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AU - Chin, K. S.

AU - Yang, J. B.

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N2 - The performances of decision-making units (DMUs) can be measured from two different points of view: optimistic or pessimistic, which leads to two different efficiencies for each DMU: the best relative efficiency and the worst relative efficiency. The conventional data envelopment analysis (DEA) considers only the best relative efficiency. It is argued that the two different efficiencies should be considered together and any approach considers only one of them is biased. This paper proposes to integrate the two different efficiencies into a geometric average efficiency, which measures the overall performance of each DMU. It is found that the geometric average efficiency has better discriminating power than either of the two efficiencies. This is illustrated by two numerical examples. © 2007 Operational Research Society Ltd. All rights reserved.

AB - The performances of decision-making units (DMUs) can be measured from two different points of view: optimistic or pessimistic, which leads to two different efficiencies for each DMU: the best relative efficiency and the worst relative efficiency. The conventional data envelopment analysis (DEA) considers only the best relative efficiency. It is argued that the two different efficiencies should be considered together and any approach considers only one of them is biased. This paper proposes to integrate the two different efficiencies into a geometric average efficiency, which measures the overall performance of each DMU. It is found that the geometric average efficiency has better discriminating power than either of the two efficiencies. This is illustrated by two numerical examples. © 2007 Operational Research Society Ltd. All rights reserved.

KW - Data envelopment analysis

KW - Discriminating power

KW - Geometric average efficiency

KW - Ranking

U2 - 10.1057/palgrave.jors.2602205

DO - 10.1057/palgrave.jors.2602205

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SP - 929

EP - 937

JO - Journal of the Operational Research Society

JF - Journal of the Operational Research Society

IS - 7

ER -

Measuring the performances of decision-making units using geometric average efficiency

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Keywords

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