The relevance of DEA benchmarking information and the Least-Distance Measure: Comment

Recently, in a Data Envelopment Analysis (DEA) framework, Baek and Lee (2009) [1]introduced a weighted Least-Distance Efficiency Measure to obtain the “shortest” projection from a considered unit to the strongly efficient production frontier. The mentioned authors tried to show that the proposed mea...

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Bibliographic Details
Published in:	Mathematical and computer modelling Vol. 52; no. 1; pp. 397 - 399
Main Authors:	Pastor, Jesus T., Aparicio, Juan
Format:	Journal Article
Language:	English
Published:	Kidlington Elsevier Ltd 01-07-2010 Elsevier
Subjects:	Data Envelopment Analysis Efficiency measure Exact sciences and technology Least Distance Mathematical analysis Mathematics Methods of scientific computing (including symbolic computation, algebraic computation) Monotonicity Numerical analysis. Scientific computation Sciences and techniques of general use Least Distance Efficiency measure Monotonicity Data Envelopment Analysis Data analysis Applied mathematics Mathematical model Computer aided analysis
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Summary:	Recently, in a Data Envelopment Analysis (DEA) framework, Baek and Lee (2009) [1]introduced a weighted Least-Distance Efficiency Measure to obtain the “shortest” projection from a considered unit to the strongly efficient production frontier. The mentioned authors tried to show that the proposed measure is well defined. Unfortunately, they did not succeed, because it lacks monotonicity, as we will show in what follows.
ISSN:	0895-7177 1872-9479
DOI:	10.1016/j.mcm.2010.03.010