Estimativa Do Custo Rodoviário Da Soja: Uma Análise Da Rota Sorrisosantos

Oliveira, Andrea; Cicolin, Lucas de Oliveira Melo; Santos, Maraisa Cristina dos

doi:10.25070/rea.v11i2.221

Cited by 3 publications

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“…In addition to this predominance in the transport matrix, road freight is the reference of freight of other modes; that is, it is an indicator of the freight market. The operators of both rail and waterway modes associate their prices with the one practiced by the road mode (OLIVEIRA et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Multidimensionality of agricultural grain road freight price: a multiple linear regression model approach by variable selection

Macarringue,

Oliveira,

Dias

et al. 2024

Cienc. Rural

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The road system is the main mode used for the transportation of agricultural cargo, and in some cases, it is the only option for handling this type of product. This dependence means that the implementation of tools to support the management of logistical costs can reduce the financial impact with the transport felt by the economic agents operating in the soybean chain. This study contributed to a better understanding of the variables that make up the cost of road freight, generating a system of road freight prediction from a multiple linear regression model using the selection of variables Stepwise, Forward, and Backward elimination. This being said, this research intends to evaluate whether the behavior of soybean road freight is influenced by the variables that make up the productive, economic, and infrastructure dimensions in price formation. The regression models had an explanatory power of 87.20%. In the infrastructure dimension, the most impact variable in soybean road freight was the distance traveled; in the economic dimension, the variables of inflation and fuel price stood out; while in the productive dimension, the main contribution was the volume of production. A more assertive predictability of logistical costs and better understanding of the dynamics of freight price formation helps industry agents in planning and decision-making. Another contribution of this study is that it can be used as a practical tool for predicting soybean road freight on several transportation routes.

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Section: Introductionmentioning

confidence: 99%

Multidimensionality of agricultural grain road freight price: a multiple linear regression model approach by variable selection

Macarringue,

Oliveira,

Dias

et al. 2024

Cienc. Rural

View full text Add to dashboard Cite

show abstract

“…Isso porque as tradings agrícolas, em sua maioria empresas transnacionais, possuem grande volume de carga agrícola a ser escoada por um grande número de pequenas empresas de transporte e caminhoneiros autônomos. Esta pulverização dos ofertantes de transporte traz vantagens às tradings agrícolas no momento da negociação dos fretes rodoviários (OLIVEIRA et al, 2013).…”

Section: Introductionunclassified

Predição de fretes agrícolas baseado na aplicação de técnicas de aprendizado de máquina

Eduardo Souza Moreira

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The grain freight cost is one of the biggest obstacles for the Brazil's competitiveness in international scenario. The road freight still is majority adopted on agricultural products transporting, and not unusual, that is the only choice to carry them. The cost weight, felt by the agribusiness operators, which work with supply chains might be decreased after the adoption of a freight management system. A promising alternative to deal with this challenge is the use of data mining techniques, which are able to extract patterns and trends in large amounts of data, which is why they have been increasingly used to support management decision in different areas, in place of intuition and resolutions based on experience. Thus, the project major goal is to develop and implement an intelligent system for forecasting road freight prices for agricultural grains. Thus, the aim of this research is predicting the freight price of agricultural commodities using models generated from Multi Layer Perceptron (MLP) and Support Vector Regression (SVR). The massive use of freight road in the logistic and grain distribution, reinforces the importance of predicting freight prices, therefore a system that could provide that kind of information to agribusiness managers and decision makers, would be critical on their daily activities. he results indicated that both techniques were efficient in estimating agricultural grain road freight prices in terms of R-squared and root mean square error (RMSE). Comparing the techniques, the SVR technique outperformed achieving an R-squared of 0.8921 and RMSE of 8.0464 for the range of routes up to 600km and 0.8924 and 21.1167 for routes longer than 600km, adopting specialized models for each data partition. In the other hand MLP resulted an R-squared 0.8785 and 8.5404 RMSE for short routes and 0.8506 and 24.8818 for long routes also making use of specialized models. In terms of using the general model or with partitioning the dataset as a function of distance traveled on the transportation route, using two individual models specialized in partitioning the set of routes into two ranges of up to 600km or greater, performed better when compared to adopting a general model for all two ranges of distances. This confirms the hypothesis that road freight prices show different behavior for different distance ranges.

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Serviço de transporte de cargas agropecuárias e os investimentos necessários no Brasil

et al. 2021

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O presente trabalho focou em tracar um panorama atual do serviço de transporte de cargas agropecuárias devido a importância econômica que a agropecuária e a logística possuem no Brasil. Através disso foi possível constatar a existentencia de fatores limitantes que ocasionam perdas nas vantagens competitivas e comparatica adquiridas na produção agrícola brasileira. Para minimizar estas perdas, investimentos em infraestrutura nos serviços de transportes são indispensáveis, porém estão aquém do necessário para a realidade atual.

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Estimativa Do Custo Rodoviário Da Soja: Uma Análise Da Rota Sorrisosantos

Cited by 3 publications

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Multidimensionality of agricultural grain road freight price: a multiple linear regression model approach by variable selection

Multidimensionality of agricultural grain road freight price: a multiple linear regression model approach by variable selection

Predição de fretes agrícolas baseado na aplicação de técnicas de aprendizado de máquina

Serviço de transporte de cargas agropecuárias e os investimentos necessários no Brasil

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