2017
DOI: 10.1007/s12351-017-0339-0
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Estimating and decomposing overall inefficiency by determining the least distance to the strongly efficient frontier in data envelopment analysis

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Cited by 10 publications
(3 citation statements)
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“…■ By Proposition 1, it is obvious that if the input-output market prices   However, as with the previous proposals (8) and (32), profit inefficiency must be normalized (deflated) in order to obtain an appropriate measuresee Aparicio et al (2016). Accordingly, we propose the following solution, which was proved in Aparicio et al (2017a).…”
Section: Profit Cross-inefficiency Measure Based On the Hölder Distanmentioning
confidence: 93%
“…■ By Proposition 1, it is obvious that if the input-output market prices   However, as with the previous proposals (8) and (32), profit inefficiency must be normalized (deflated) in order to obtain an appropriate measuresee Aparicio et al (2016). Accordingly, we propose the following solution, which was proved in Aparicio et al (2017a).…”
Section: Profit Cross-inefficiency Measure Based On the Hölder Distanmentioning
confidence: 93%
“…The literature on DEA approaches to compute closest efficient targets is abundant, dating back to Frei and Harker (1999). The reader is referred to Aparicio (2016) and Aparicio et al (2017aAparicio et al ( , 2017b…”
Section: Meffp Target Setting Modelmentioning
confidence: 99%
“…For recent and up-to-date developments on the least distance projections, the reader is referred to Aparicio (2016) and Aparicio et al (2017d).…”
Section: Introductionmentioning
confidence: 99%