Issue |
RAIRO-Oper. Res.
Volume 56, Number 4, July-August 2022
|
|
---|---|---|
Page(s) | 2543 - 2556 | |
DOI | https://doi.org/10.1051/ro/2022090 | |
Published online | 18 August 2022 |
Network data envelopment analysis with two-level maximin strategy
School of Management, University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui 230026, P.R. China
* Corresponding author: wdw1996@mail.ustc.edu.cn
Received:
1
November
2021
Accepted:
28
May
2022
Network data envelopment analysis (NDEA), one of the most important branches of recent DEA developments, has been developed for examining the decision making units (DMUs) of a system with complex and internal component divisions. In this study we apply a maximin strategy to network DEA at two levels. At the individual DMU level, we evaluate the system’s performance by maximizing the minimum of the divisions efficiencies, which is based on the weak-link approach. At the all DMUs level, we evaluate the system’s performance by maximizing the minimum of the DMUs’ efficiencies, which is based on the maximin ratio efficiency model. With such two-level maximin strategy, we propose the two-level maximin NDEA model to evaluate efficiencies of all divisions as well as all DMUs at the same time. The model will provide unique and unbiased efficiency scores for all divisions in a system and improve incomparable efficiency scores and weak discrimination power of traditional DEA models. In addition, we discuss the cross efficiency evaluation based on the two-level maximin NDEA model. The proposed models are applied to the efficiency evaluation of supply chains for illustrations.
Mathematics Subject Classification: 90B030
Key words: Data envelopment analysis / weak-link approach / maximin efficiency ratio model / cross efficiency / supply chains
© The authors. Published by EDP Sciences, ROADEF, SMAI 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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