Results 231 to 240 of about 88,346 (265)
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Network DEA smallest improvement approach
Omega, 2021Abstract In this paper the smallest improvement DEA approach to general networks of processes is proposed. The corresponding projection direction is endogenously computed by the model so that the relative distance to the frontier is minimal. Both the cooperative and the non-cooperative scenarios for the intermediate products are considered.
Sebastián Lozano, Somayeh Khezri
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Proportional trade-offs in network DEA
Computers & Industrial Engineering, 2021Abstract This paper proposes a network Data Envelopment Analysis (DEA) framework for incorporating value-judgments in the form of production trade-offs, in order to, in detail, analyze the synchronized variations in the flows of production (input/output) factors among different divisions or sub-divisions.
Fatemeh Boloori +2 more
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Network DEA: Additive efficiency decomposition
European Journal of Operational Research, 2010zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Cook, Wade D. +3 more
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Ownership-specified network DEA models
Annals of Operations Research, 2011zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chang, Tsung-Sheng +2 more
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2014
The original DEA model by Charnes et al. (Eur. J. Oper. Res. 2:429–444, 1978) is set to analyze production as a black box, i.e., there is no information about the processes inside. Network DEA was proposed for analysis of the contents of the black box.
Rolf Färe +2 more
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The original DEA model by Charnes et al. (Eur. J. Oper. Res. 2:429–444, 1978) is set to analyze production as a black box, i.e., there is no information about the processes inside. Network DEA was proposed for analysis of the contents of the black box.
Rolf Färe +2 more
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Supply Chain Evaluation by Network DEA
2023In today’s competitive arena, performance evaluation is essential in all organizations, including the supply chain, to control, lead and plan organizations. As stated in Chap. 8, DEA is a widely used technique to evaluate the performance of DMUs, including the supply chain.
Hosseinzadeh Lotfi, F. +3 more
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2014
Traditional DEA models deal with measurements of relative efficiency of DMUs regarding multiple-inputs versus multiple-outputs. One of the drawbacks of these models is the neglect of intermediate products or linking activities. After pointing out needs for inclusion of them to DEA models, we propose a slacks-based network DEA model that can deal with ...
Kaoru Tone, Miki Tsutsui
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Traditional DEA models deal with measurements of relative efficiency of DMUs regarding multiple-inputs versus multiple-outputs. One of the drawbacks of these models is the neglect of intermediate products or linking activities. After pointing out needs for inclusion of them to DEA models, we propose a slacks-based network DEA model that can deal with ...
Kaoru Tone, Miki Tsutsui
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Range Adjusted Measure Network DEA Model
AIP Conference Proceedings, 2009In this paper, we propose a range adjusted measure network data envelopment analysis (DEA) model that can deal with the overall efficiencies as well as divisional ones in a unified framework. We show some properties of this model.
Yukihiro Maruyama +3 more
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DEA for non-homogenous parallel networks
Omega, 2015Abstract In practice, systems are often composed of a group of sub-units. Each sub-unit has a set of performance metrics that are classified as inputs and outputs in data envelopment analysis (DEA). Conventional DEA views such a system as a “black-box”, other DEA-based models are developed to investigate the inner structure, either with a serial ...
Juan Du, Yao Chen, Jiazhen Huo
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Pareto–Koopmans efficiency and network DEA
Omega, 2016Standard or black-box data envelopment analysis (DEA) evaluates the efficiency of the transformation of a DMU׳s exogenous inputs into its final outputs by ignoring what is going on in its divisions (sub-DMUs). To cope with this problem, network DEA (NDEA), which can provide adequate detail to management, has been developed and applied empirically ...
S. Morteza Mirdehghan, Hirofumi Fukuyama
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