Detecting the weak and strong congestion statuses of decision-making units (DMUs) and measuring them via data envelopment analysis (DEA) is an important issue that has been discussed in several studies and with different views. The efficiency frontier is a concept derived from the underlying production possibility set (PPS), and the congestion concept is related to them. Still, researchers have defined congestion for each DMU in many previous studies and ignored that congestion is linked with the underlying production technology. In the congestion measurement matter, this paper presents two new insights into a congestion area and non-congestion area for production technology and two new mathematical definitions of congestion based on the PPS properties and detecting the weak and strong congestion status of DMUs (CSOD). We prove our definitions are equal to the original definition of congestion. First, we describe the congestion and non-congestion areas based on the PPS; then provide full details of how to measure congestion built on these new insights. Our approaches are very accurate and fast to calculate; they are theoretically elementary and efficient in performance. Our proposed methods can deal with both non-negative and negative data. Finally, an empirical example is provided to illustrate our approaches.
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DOI : 10.1051/ro/2022093
Keywords: Data envelopment analysis (DEA), congestion starting point (CSP), efficiency, congestion area (CA), non-congestion area (NCA), production possibility set (PPS)
@article{RO_2022__56_4_2067_0,
author = {Moosavi, Seyed Rahim and Valami, Hadi Bagherzadeh},
editor = {Mahjoub, A. Ridha and Laghrib, A. and Metrane, A.},
title = {Congestion and non-congestion areas: identify and measure congestion in {DEA}},
journal = {RAIRO. Operations Research},
pages = {2067--2092},
year = {2022},
publisher = {EDP-Sciences},
volume = {56},
number = {4},
doi = {10.1051/ro/2022093},
mrnumber = {4450248},
zbl = {1492.90086},
language = {en},
url = {https://www.numdam.org/articles/10.1051/ro/2022093/}
}
TY - JOUR AU - Moosavi, Seyed Rahim AU - Valami, Hadi Bagherzadeh ED - Mahjoub, A. Ridha ED - Laghrib, A. ED - Metrane, A. TI - Congestion and non-congestion areas: identify and measure congestion in DEA JO - RAIRO. Operations Research PY - 2022 SP - 2067 EP - 2092 VL - 56 IS - 4 PB - EDP-Sciences UR - https://www.numdam.org/articles/10.1051/ro/2022093/ DO - 10.1051/ro/2022093 LA - en ID - RO_2022__56_4_2067_0 ER -
%0 Journal Article %A Moosavi, Seyed Rahim %A Valami, Hadi Bagherzadeh %E Mahjoub, A. Ridha %E Laghrib, A. %E Metrane, A. %T Congestion and non-congestion areas: identify and measure congestion in DEA %J RAIRO. Operations Research %D 2022 %P 2067-2092 %V 56 %N 4 %I EDP-Sciences %U https://www.numdam.org/articles/10.1051/ro/2022093/ %R 10.1051/ro/2022093 %G en %F RO_2022__56_4_2067_0
Moosavi, Seyed Rahim; Valami, Hadi Bagherzadeh. Congestion and non-congestion areas: identify and measure congestion in DEA. RAIRO. Operations Research, Tome 56 (2022) no. 4, pp. 2067-2092. doi: 10.1051/ro/2022093
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