N. Ramon, H. P. Guevel, J. Aparicio Baeza
The minimum distance models have undoubtedly represented a significant advance for the establishment of targets in Data Envelopment Analysis (DEA). These models may help in defining improvement plans that require the least overall effort from the inefficient Decision Making Units (DMUs). Despite the advantages that come with closest targets, in some cases unsatisfactory results may be given, since improvement plans, even in that context, differ considerably from the actual performances. In the absence of information, the most plausible and conservative solution would be the one where an equitable redistribution of efforts is possible. We propose different approaches with the aim of reaching an impartial distribution of efforts to achieve optimal operating levels without neglecting the overall effort required. Moreover, and as something new in the benchmarking DEA context, we will study which properties satisfy the targets generated by the different models proposed.
Palabras clave: Data Envelopment Analysis – Benchmarking – Targets – Balanced efforts
Programado
Análisis Envolvente de Datos. Sesión en honor del Prof. Jesús T. Pastor Ciurana
10 de noviembre de 2023 12:00
CC3: Sala 1