Objetivo: Objetiva-se comparar a eficiência relativa das ferrovias especializadas em transporte de minério de ferro (MFe) e pelota (PLMFe), que fazem parte do patrimônio das empresas de mineração e usinas de pelotização considerando o cenário de 2016. Métodos: Foi utilizada a técnica Análise Envoltória de Dados (DEA), com aplicação do modelo de retornos constantes de escala (CCR) e orientação a saída (output); o método multicritério combinatório inicial para escolha das variáveis de entrada e a regressão Tobit como estratégia de validação do modelo DEA. Resultados: Das doze ferrovias avaliadas, três ferrovias foram identificadas como eficientes: Estrada de Ferro Carajás, Fortescue e Mount Newman. Conclusões: O modelo aplicado foi considerado como um bom método para avaliar a eficiência das ferrovias especializadas em transporte de MFe e PLMFe, pois determinou a eficiência de cada ferrovia, sugerindo o aumento necessário na variável de saída ou ajustes nas variáveis de entrada para que as ferrovias atinjam a fronteira de eficiência. Com isso, as empresas podem utilizar os resultados deste estudo para guiar melhorias futuras para tornar sua ferrovia mais eficiente ou se manter na fronteira de eficiência.
Objective: the objective is to compare the relative efficiency of the railways specialized in transporting iron ore (MFe) and pellets (PLMFe), which are part of the assets of mining companies and pellet plants considering the 2016 scenario. Methods: the methods used were the data envelopment analysis (DEA) technique, with the application of the output-oriented constant returns scale (CRS) model; the initial combinatorial multicriteria method for choosing the input variables; and Tobit regression as a validation strategy for the DEA model. Results: of the twelve railways evaluated, three railways were identified as efficient: Estrada de Ferro Carajás, Fortescue, and Mount Newman. Conclusions: the applied model was considered a good method to evaluate the efficiency of railways specialized in transporting MFe and PLMFe, as it determined the efficiency of each railway, suggesting the necessary increase in the output variable or adjustments in the input variables so that the railways reach the efficiency frontier. With that, companies can use the results of this study to guide future improvements to make their railways more efficient or maintain them on the frontier of efficiency.
Objective: the objective is to compare the relative efficiency of the railways specialized in transporting iron ore (MFe) and pellets (PLMFe), which are part of the assets of mining companies and pellet plants considering the 2016 scenario. Methods: the methods used were the data envelopment analysis (DEA) technique, with the application of the output-oriented constant returns scale (CRS) model; the initial combinatorial multicriteria method for choosing the input variables; and Tobit regression as a validation strategy for the DEA model. Results: of the twelve railways evaluated, three railways were identified as efficient: Estrada de Ferro Carajás, Fortescue, and Mount Newman. Conclusions: the applied model was considered a good method to evaluate the efficiency of railways specialized in transporting MFe and PLMFe, as it determined the efficiency of each railway, suggesting the necessary increase in the output variable or adjustments in the input variables so that the railways reach the efficiency frontier. With that, companies can use the results of this study to guide future improvements to make their railways more efficient or maintain them on the frontier of efficiency.
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