Volume de Vendas X Eficiência Financeira: Análise das 500 Maiores Empresas de 2018 a Partir de um Método Multicritério

Hein, Nelson; Moreno, Gleice Carvalho de Lima; Santos, Leonardo dos; Panosso, Oderson; Kroenke, Adriana

doi:10.12819/2021.18.03.5

Cited by 1 publication

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References 13 publications

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“…Many scholars have carried out relevant research on financial efficiency to solve the problems in the operation of new rural financial institutions. Hein et al [ 6 ] assessed whether the uniformity of financial metrics had an ordinal correlation with the sales ranking of the 500 largest companies corresponding to 2018 published by Exame magazine. To clarify this doubt, the author used the TOPSIS multicriteria method to evaluate the scale of financial indicators.…”

Section: Introductionmentioning

confidence: 99%

Application of Three-Stage DEA Model Combined with BP Neural Network in Microfinancial Efficiency Evaluation

Yang

Mei

et al. 2022

Computational Intelligence and Neuroscience

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The research performed here intends to explore the future development model of new rural financial institutions and determine the financial efficiency goals, thereby providing a huge stage for the development of new rural financial institutions. It applies data envelopment analysis (DEA) to assess financial efficiency to make up for the research gap. First, the relevant theories of rural finance are discussed. Then, some indicators are selected to build an evaluation system. In addition, the DEA method is used to evaluate the rural financial efficiency in Hebei Province by listing the input indexes and output indexes. After training, the backpropagation neural network (BPNN) model is designed and simulated to obtain the evaluation results. The research results show that before 2015, the comprehensive efficiency of Xingtai, Hengshui, Shijiazhuang, and Langfang showed a downward trend. After 2015, the comprehensive efficiency of all cities in Hebei Province tended to be stable, generally stable at about 0.95. It suggests that rural finance in Hebei Province has developed stably in recent years, and the overall efficiency of rural finance has been improved to a certain extent. The simulation results of BPNN demonstrate that the operation efficiency evaluation result of the poverty alleviation development model in the financial support industry is 0.6995, in the interval (0.6, 0.8). In addition, the model operation efficiency is better, indicating that the poverty alleviation development model of the financial support industry has achieved good results and promoted the development of poor rural areas. The research content can provide reference and inspiration for the continuous promotion of rural finance and the formulation and implementation of financial institution reform policies.

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Section: Introductionmentioning

confidence: 99%

Application of Three-Stage DEA Model Combined with BP Neural Network in Microfinancial Efficiency Evaluation

Yang

Mei

et al. 2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

show abstract

Volume de Vendas X Eficiência Financeira: Análise das 500 Maiores Empresas de 2018 a Partir de um Método Multicritério

Abstract: Artigo recebido em 04/02/2021. Última versão recebida em 17/02/2021. Aprovado em 18/02/2021. Avaliado pelo sistema Triple Review: a) Desk Review pelo Editor-Chefe; e b) Double Blind Review (avaliação cega por dois avaliadores da área). Revisão: Gramatical, Normativa e de Formatação

Cited by 1 publication

References 13 publications

Application of Three-Stage DEA Model Combined with BP Neural Network in Microfinancial Efficiency Evaluation

Application of Three-Stage DEA Model Combined with BP Neural Network in Microfinancial Efficiency Evaluation

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