ABC analysis is a famous technique for inventory classification. However, this technique on the inventory classification only considering one indicator even though other important factors may affect the classification. To address this issue, researchers have proposed multiple criteria inventory classification (MCIC) solutions based on data envelopment analysis (DEA)-like methods. However, previous models almost evaluate items by different weight sets, and the index system only contains quantitative criteria and output indicators. To avoid these shortcomings, we propose an improved common-weight DEA model for MCIC issue. This model simultaneously considers quantitative and qualitative criteria as well as establishes a comprehensive index system that includes inputs and outputs. Apart from its improved discriminating power and lack of subjectivity, this non-parametric and linear programming model provides the performance scores of all items through a single computation. A case study is performed to validate and compare the performance of this new model with that of traditional ABC analysis, DEA–CCR and DEA–CI. The results show that apart from the highly improved discriminating power and significant reduction in computational burden, the proposed model has achieved a more comprehensive ABC inventory classification than the traditional models.
Accepté le :
DOI : 10.1051/ro/2018105
Mots-clés : ABC inventory classification, multiple criteria inventory classification (MCIC), data envelopment analysis (DEA), common-weight, qualitative criteria
@article{RO_2019__53_5_1775_0,
author = {An, Qingxian and Wen, Yao and Hu, Junhua and Lei, Xiyang},
title = {A common-weight {DEA} model for multi-criteria {ABC} inventory classification with quantitative and qualitative criteria},
journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
pages = {1775--1789},
publisher = {EDP-Sciences},
volume = {53},
number = {5},
year = {2019},
doi = {10.1051/ro/2018105},
mrnumber = {4017404},
zbl = {1430.90006},
language = {en},
url = {http://www.numdam.org/articles/10.1051/ro/2018105/}
}
TY - JOUR AU - An, Qingxian AU - Wen, Yao AU - Hu, Junhua AU - Lei, Xiyang TI - A common-weight DEA model for multi-criteria ABC inventory classification with quantitative and qualitative criteria JO - RAIRO - Operations Research - Recherche Opérationnelle PY - 2019 SP - 1775 EP - 1789 VL - 53 IS - 5 PB - EDP-Sciences UR - http://www.numdam.org/articles/10.1051/ro/2018105/ DO - 10.1051/ro/2018105 LA - en ID - RO_2019__53_5_1775_0 ER -
%0 Journal Article %A An, Qingxian %A Wen, Yao %A Hu, Junhua %A Lei, Xiyang %T A common-weight DEA model for multi-criteria ABC inventory classification with quantitative and qualitative criteria %J RAIRO - Operations Research - Recherche Opérationnelle %D 2019 %P 1775-1789 %V 53 %N 5 %I EDP-Sciences %U http://www.numdam.org/articles/10.1051/ro/2018105/ %R 10.1051/ro/2018105 %G en %F RO_2019__53_5_1775_0
An, Qingxian; Wen, Yao; Hu, Junhua; Lei, Xiyang. A common-weight DEA model for multi-criteria ABC inventory classification with quantitative and qualitative criteria. RAIRO - Operations Research - Recherche Opérationnelle, Tome 53 (2019) no. 5, pp. 1775-1789. doi : 10.1051/ro/2018105. http://www.numdam.org/articles/10.1051/ro/2018105/
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