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    Value of the stochastic efficiency in data envelopment analysis

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    Vincent_ESA (272.8Kb)
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    Publication date
    2017-09-15
    Author
    Vincent, Charles
    Keyword
    Data envelopment analysis
    Stochastic
    Input-output analysis
    Performance/productivity
    Rights
    © 2017 Elsevier Ltd. All rights reserved. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license.
    Peer-Reviewed
    Yes
    
    Metadata
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    Abstract
    This article examines the potential benefits of solving a stochastic DEA model over solving a deterministic DEA model. It demonstrates that wrong decisions could be made whenever a possible stochastic DEA problem is solved when the stochastic information is either unobserved or limited to a measure of central tendency. We propose two linear models: a semi-stochastic model where the inputs of the DMU of interest are treated as random while the inputs of the other DMUs are frozen at their expected values, and a stochastic model where the inputs of all of the DMUs are treated as random. These two models can be used with any empirical distribution in a Monte Carlo sampling approach. We also define the value of the stochastic efficiency (or semi-stochastic efficiency) and the expected value of the efficiency.
    URI
    http://hdl.handle.net/10454/17538
    Version
    Accepted manuscript
    Citation
    Vincent C and Cornillier F (2017) Value of the stochastic efficiency in data envelopment analysis. Expert Systems with Applications. 81: 349-357.
    Link to publisher’s version
    https://doi.org/10.1016/j.eswa.2017.03.061
    Type
    Article
    Collections
    Management and Law Publications

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