TY - JOUR
T1 - A Unified Parallel DEA Model and Efficiency Modeling of Multi-Activity and/or Non-Homogeneous Activity
AU - Shen , W. F.
AU - Zhou , Z. B.
AU - Liu , P. D.
AU - Jin , Q. Y.
AU - Liu , W. B.
AU - Niu , Huayong
JO - International Journal of Numerical Analysis and Modeling
VL - 3
SP - 370
EP - 391
PY - 2018
DA - 2018/03
SN - 15
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/ijnam/12521.html
KW - Data envelopment analysis, parallel model, multi-activity, non-homogeneous.
AB - <p style="text-align: justify;">Data envelopment analysis (DEA), as originally proposed, is a methodology for evaluating
the relative efficiencies of peer decision making units (DMUs) under some general assumptions.
DEA models with non-homogeneous DMUs and multi-activity structures are two different
subjects referring to relaxing various assumptions. In this paper, we show that these two formulations
are both derived by embedding the corresponding process into a general parallel DEA model.
Furthermore, following the parallel DEA framework, general DEA models for multi-activity and
non-homogeneity are proposed, which are able to handle many situations where different aspects
of non-homogeneity or multi-activities exist. This study provides important insights into the
existing DEA models for non-homogeneity and multi-activity.</p>