Multistage network DEA: Decomposition and aggregation weights of component performance

Guo, Chuanyin; Wei, Fajie; Ding, Tao; Zhang, Linyan; Liang, Liang

doi:10.1016/j.cie.2017.08.019

Cited by 18 publications

(2 citation statements)

References 21 publications

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“…As suggestions for future studies, we propose the analysis of the multiple optimal weights for the relational model and its representations in the graph. Besides that, we propose extending the model presented for different types of return to scale (Benicio and Soares de Mello, 2019) and other Network DEA models, as the additive model (Chen et al, 2009), the relational model (Kao, 2009), multi-stage processes (Despotis et al, 2016b;Zhang et al, 2019;Guo et al, 2017) and other models (Tone and Tsutsui, 2009;Guo and Zhu, 2017;Wang et al, 2019). Another suggestion for future studies is to verify how to determine the target for inefficient DMUs at the efficient frontier, for that, it can be applied the method proposed in Chen et al ( 2010).…”

Section: Discussionmentioning

confidence: 99%

Two-Dimensional Representation for Two-Stage Network Dea Models

2022

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We propose two-dimensional representations for the efficient frontier for two different Network DEA (NDEA) models. Both representations follow a previous study that developed a generalization of the two-dimensional representation method for the classic DEA using a new form of linearization. The graphical representation of the efficient frontier allows managers and decision-makers unfamiliar with linear programming and DEA to understand the results obtained simply and clearly. In this study, we can obtain graphs that provide information about the efficiencies of each DMU. Furthermore, for the NDEA with an efficiency decomposition approach, it is possible to obtain a graph to evaluate the technical efficiency for each stage, as well as for the overall efficiency. The NDEA model based on efficiency composition only produces one graph. However, this unique representation shows the stage-level and the overall process level information within the same graph.

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Section: Discussionmentioning

confidence: 99%

Two-Dimensional Representation for Two-Stage Network Dea Models

2022

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“…Although a considerable amount of research applies DEA models to analyze the performance of the banking industry (Liu et al, 2013b;Guo et al, 2017;da Silva Fernandes et al, 2018;Li et al, 2018), few have focused on Brazil (Wanke and Barros, 2014). Brazil has the largest and most complex financial system in Latin America, and its banking industry has experienced an accelerated process of deep restructuring since the first half of the 1990s (Tecles and Tabak, 2010).…”

Section: Introductionmentioning

confidence: 99%

Efficiency and productivity of the Brazilian banks: A new approach based on two-stage network DEA

Valério

Pamplona

Fonseca³

et al. 2021

Braz. Rev. Fin.

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This article creates a conceptual model, called a network system, to represent the Brazilian banking production system, based on its internal operational processes. The first, called the intermediation process, measures a bank's efficiency in extending loans from its available resources. The second, called the revenue process, measures a bank's efficiency in earning profit, mainly from loans granted. We adopt a two-stage DEA model. In the first stage, a relational network DEA model measures both the network system efficiency scores and internal processes. This technique, associated with the Malmquist Index, assesses performance changes over time. In the second stage, these efficiency scores are considered dependent variables, such that Tobit models can determine how the Brazilian credit market's characteristics can explain the network system and internal processes' efficiency. Results show not only a growing trend toward greater efficiency in the revenue process, but also an increase in productivity accompanied by a decline in the intermediation process technology. Given the high banking spreads in Brazil, these results indicate deterioration in the quality of the credit portfolio and the prospect of future insolvency. We discuss implications of this scenario for domestic banks and collateral policy.

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A Taxonomy and Review of the Network Data Envelopment Analysis Literature

Koronakos

2019

Learning and Analytics in Intelligent Systems

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Multistage network DEA: Decomposition and aggregation weights of component performance

Cited by 18 publications

References 21 publications

Two-Dimensional Representation for Two-Stage Network Dea Models

Two-Dimensional Representation for Two-Stage Network Dea Models

Efficiency and productivity of the Brazilian banks: A new approach based on two-stage network DEA

A Taxonomy and Review of the Network Data Envelopment Analysis Literature

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