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|a (JST)40295717
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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|a Dulá, J. H.
|e verfasserin
|4 aut
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|a A Geometrical Approach for Generalizing the Production Possibility Set in DEA
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|c 2009
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|a Text
|b txt
|2 rdacontent
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|a Online-Ressource
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|a Consider a Data Envelopment Analysis (DEA) study with n Decision Making Units (DMUs) and a model with m inputs plus outputs. The data for this study are a point set, {a¹, ..., $a^n $ ], in $R^m $ . A DMU is efficient if its data point is located on the efficient frontier portion of the boundary of an empirical production possibility set, a polyhedral envelopment hull described by the data. From this perspective, DEA efficiency is a purely geometric concept that can be applied to general point sets to identify records with extreme properties. The generalized approach permits new applications for nonparametric frontiers. Examples of such applications are fraud detection, auditing, security, and appraisals. We extend the concept of DEA efficiency to frontier outliers in general envelopment hulls.
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|a Copyright 2009 Operational Research Society Ltd
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|a Data Envelopment Analysis
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|a convex analysis
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|a polyhedral set theory
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|a Business
|x Business economics
|x Commercial production
|x Production management
|x Production possibilities
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|a Information science
|x Data products
|x Datasets
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|a Business
|x Business economics
|x Commercial production
|x Production factors
|x Production efficiency
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|a Behavioral sciences
|x Psychology
|x Cognitive psychology
|x Decision theory
|x Operations research
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|a Mathematics
|x Pure mathematics
|x Geometry
|x Geometric shapes
|x Polytopes
|x Polyhedrons
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|a Philosophy
|x Applied philosophy
|x Philosophy of mathematics
|x Mathematical concepts
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650 |
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4 |
|a Mathematics
|x Pure mathematics
|x Geometry
|x Non Euclidean geometry
|x Hyperplanes
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650 |
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|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Descriptive statistics
|x Statistical distributions
|x Outliers
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|a Mathematics
|x Pure mathematics
|x Linear algebra
|x Vector analysis
|x Mathematical vectors
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650 |
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4 |
|a Applied sciences
|x Research methods
|x Modeling
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650 |
|
4 |
|a Business
|x Business economics
|x Commercial production
|x Production management
|x Production possibilities
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650 |
|
4 |
|a Information science
|x Data products
|x Datasets
|
650 |
|
4 |
|a Business
|x Business economics
|x Commercial production
|x Production factors
|x Production efficiency
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650 |
|
4 |
|a Behavioral sciences
|x Psychology
|x Cognitive psychology
|x Decision theory
|x Operations research
|
650 |
|
4 |
|a Mathematics
|x Pure mathematics
|x Geometry
|x Geometric shapes
|x Polytopes
|x Polyhedrons
|
650 |
|
4 |
|a Philosophy
|x Applied philosophy
|x Philosophy of mathematics
|x Mathematical concepts
|
650 |
|
4 |
|a Mathematics
|x Pure mathematics
|x Geometry
|x Non Euclidean geometry
|x Hyperplanes
|
650 |
|
4 |
|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Descriptive statistics
|x Statistical distributions
|x Outliers
|
650 |
|
4 |
|a Mathematics
|x Pure mathematics
|x Linear algebra
|x Vector analysis
|x Mathematical vectors
|
650 |
|
4 |
|a Applied sciences
|x Research methods
|x Modeling
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|a research-article
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|i Enthalten in
|t The Journal of the Operational Research Society
|d Taylor & Francis, Ltd.
|g 60(2009), 11, Seite 1546-1555
|w (DE-627)320465098
|w (DE-600)2007775-0
|x 14769360
|7 nnns
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1 |
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|g volume:60
|g year:2009
|g number:11
|g pages:1546-1555
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|u https://www.jstor.org/stable/40295717
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|d 60
|j 2009
|e 11
|h 1546-1555
|