The bias in reversing the Box-Cox transformation in time series forecasting: An empirical study based on neural networks

The Box-Cox transformation is a technique mostly utilized to turn the probabilistic distribution of a time series data into approximately normal. And this helps statistical and neural models to perform more accurate forecastings. However, it introduces a bias when the reversion of the transformation is conducted with the predicted data. The statistical methods to perform a bias-free reversion require, necessarily, the assumption of Gaussianity of the transformed data distribution, which is a rare event in real-world time series. So, the aim of this study was to provide an effective method of removing the bias when the reversion of the Box-Cox transformation is executed. Thus, the developed method is based on a focused time lagged feedforward neural network, which does not require any assumption about the transformed data distribution. Therefore, to evaluate the performance of the proposed method, numerical simulations were conducted and the Mean Absolute Percentage Error, the Theil Inequality Index and the Signal-to-Noise ratio of 20-step-ahead forecasts of 40 time series were compared, and the results obtained indicate that the proposed reversion method is valid and justifies new studies. (C) 2014 Elsevier B.V. All rights reserved.

Are supplier selection criteria going green? Case studies of companies in Brazil

Purpose - The purpose of this paper is to verify if Brazilian companies are adopting environmental requirements in the supplier selection process. Further, this paper intends to analyze whether there is a relation between the level of environmental management maturity and the inclusion of environmental criteria in the companies' selection of suppliers.Design/methodology/approach - A review of mainstream literature on environmental management, traditional criteria in the supplier selection process and the incorporation of environmental requirements in this context. The empirical study's strategy is based on five Brazilian case studies with industrial companies. Face-to-face interviews and informal conversations are to be held, explanations made by e-mail with representatives from the purchasing, environmental management, logistics and other areas, and observation and the collection of company documents are also employed.Findings - Based on the cases, it is concluded that companies still use traditional criteria to select suppliers, such as quality and cost, and do not adopt environmental requirements in the supplier selection process in a uniform manner. Evidence found shows that the level of environmental management maturity influences the depth with which companies adopt environmental criteria when selecting suppliers. Thus, a company with more advanced environmental management adopts more formal procedures for selecting environmentally appropriate suppliers than others.Originality/value - This is the first known study to verify if Brazilian companies are adopting environmental requirements in the supplier selection process.

Modelo sistêmico de ocorrência de ações coletivas: um estudo multicaso na comercialização de frutas, legumes e verduras

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Environmental development in Brazilian companies: The role of human resource management

Specialized literature states that proper environmental management at companies requires support from human resource management. This occurs because the more efficient and effective human resource management is, the more it tends to contribute towards the organization's objectives. Considering that environmental management is an emerging organizational objective, human resource practices, when efficient and effective, tend to incorporate environmental goal and to become greener. In order to contribute to this emerging field of research, this paper reports on an empirical study about the relationship between human resources and environmental management at 75 Brazilian companies. The data collected were analyzed statistically using Structural Equation Modeling. The main results indicated that human resource management practices tend to statistically significant relate to environmental management at analyzed companies, through validation of H 1, but his relationship can be considered weak. © 2012 Elsevier B.V.

O revelar da paixão: as relações estabelecidas entre coreógrafo, bailarinos e obra no processo de criação do Pas de Deux de Bachiana n.1

Pós-graduação em Artes - IA

Perfil pessoal e profissional de professores do ensino fundamental e médio: uma investigação com profissionais pertencentes à diretoria de ensino de Jaú-SP

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Os espaços de medo e os de castigo nas pequenas cidades do estado de São Paulo: o caso Itirapina

Pós-graduação em Geografia - IGCE

A relação entre competitividade e território no circuito das malhas do sul de Minas

Pós-graduação em Geografia - IGCE

A saúde mental no Programa de Saúde da Família: estudo sobre práticas e significações de uma equipe

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Diretrizes para a criação de aplicações web com ênfase em portabilidade e eficiência

Pós-graduação em Ciência da Computação - IBILCE

A construção do regime ambiental internacional: mecanismo de desenvolvimento limpo e a cogeração de energia no setor sucroalcooleiro

Pós-graduação em Ciências Sociais - FFC

Divisão social e definição dos grupos sociais no meio rural - campesinato, proletariado rural e agricultura familiar: o caso de Conchas-SP

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise setorial: o caso da privatização do modal ferroviário brasileiro

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A produção rural familiar em Goiás: as comunidades rurais no município de Catalão

Pós-graduação em Geografia - FCT

Processos de revisão e reescritura em textos narrativos de alunos de quinta série do ensino fundamental

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)