@Article{IJNAM-15-3,
author = {W., Shen, F. and Zhou, Z., B. and P., Liu, D. and Y., Q., Jin and W., Liu, B. and Niu, Huayong},
title = {A Unified Parallel DEA Model and Efficiency Modeling of Multi-Activity and/or Non-Homogeneous Activity},
journal = {International Journal of Numerical Analysis and Modeling},
year = {2018},
volume = {15},
number = {3},
pages = {370--391},
abstract = {<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>},
issn = {2617-8710},
doi = {https://doi.org/2018-IJNAM-12521},
url = {https://global-sci.com/article/83117/a-unified-parallel-dea-model-and-efficiency-modeling-of-multi-activity-andor-non-homogeneous-activity}
}