Diagnostic for measuring influence in data envelopment analysis

Liam O'Neill; Holly S. Lewis; J. Keith Ord

Diagnostic for measuring influence in data envelopment analysis

Liam O'Neill, Holly S. Lewis, J. Keith Ord

School of Public Health

Research output: Contribution to conference › Paper › peer-review

1 Scopus citations

Abstract

The superefficiency (SE) model for data envelopment analysis (DEA) measures the influence of each decision-making unit on the efficient frontier and identifies those observations exerting the most influence. As such, the SE model is useful in identifying potential data errors. It also obviates the need for non-Archimedian infinitesimal constraints and eliminates the inherent problem of primal multiple optimal solutions and dual degeneracy characteristic of other DEA model versions.

Original language	English
Pages	1041-1043
Number of pages	3
State	Published - 1 Dec 1996
Event	Proceedings of the 1996 27th Annual Meeting of the Decision Sciences Institute. Part 2 (of 3) - Orlando, FL, USA Duration: 24 Nov 1996 → 26 Nov 1996

Other

Other	Proceedings of the 1996 27th Annual Meeting of the Decision Sciences Institute. Part 2 (of 3)
City	Orlando, FL, USA
Period	24/11/96 → 26/11/96

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title = "Diagnostic for measuring influence in data envelopment analysis",

abstract = "The superefficiency (SE) model for data envelopment analysis (DEA) measures the influence of each decision-making unit on the efficient frontier and identifies those observations exerting the most influence. As such, the SE model is useful in identifying potential data errors. It also obviates the need for non-Archimedian infinitesimal constraints and eliminates the inherent problem of primal multiple optimal solutions and dual degeneracy characteristic of other DEA model versions.",

author = "Liam O'Neill and Lewis, {Holly S.} and Ord, {J. Keith}",

year = "1996",

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AU - Lewis, Holly S.

AU - Ord, J. Keith

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N2 - The superefficiency (SE) model for data envelopment analysis (DEA) measures the influence of each decision-making unit on the efficient frontier and identifies those observations exerting the most influence. As such, the SE model is useful in identifying potential data errors. It also obviates the need for non-Archimedian infinitesimal constraints and eliminates the inherent problem of primal multiple optimal solutions and dual degeneracy characteristic of other DEA model versions.

AB - The superefficiency (SE) model for data envelopment analysis (DEA) measures the influence of each decision-making unit on the efficient frontier and identifies those observations exerting the most influence. As such, the SE model is useful in identifying potential data errors. It also obviates the need for non-Archimedian infinitesimal constraints and eliminates the inherent problem of primal multiple optimal solutions and dual degeneracy characteristic of other DEA model versions.

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M3 - Paper

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SP - 1041

EP - 1043

Y2 - 24 November 1996 through 26 November 1996

ER -

Diagnostic for measuring influence in data envelopment analysis

Abstract

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