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• W791424211 abstract "In this chapter we present an overview of the different approaches that have considered translation invariant Data Envelopment Analysis (DEA) models. Translation invariance is a relevant property for dealing with non-positive input and/or non-positive output values. We start by considering the classical approach and continue revising recent contributions. We also consider non-translation invariant DEA models that are able to deal with negative data at the expense of modifying the model itself. Finally, we propose to study translation invariance in a general framework through a recently introduced distance function: the linear loss distance function." @default.
• W791424211 created "2016-06-24" @default.
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• W791424211 date "2015-01-01" @default.
• W791424211 modified "2023-09-29" @default.
• W791424211 title "Translation Invariance in Data Envelopment Analysis" @default.
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• W791424211 doi "https://doi.org/10.1007/978-1-4899-7553-9_8" @default.
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