Abstract
ABSTRACT This study aimed to analyze the variables that influence freight cost in the forest supply chain and to fit nonlinear regression models to estimate the freight cost of wood transportation from the production areas to the processing units. The data used for cost analysis considered the following variables: volume of wood (m3); average fuel consumption (km/l) and average speed of the complete journey (km/h) per round trip. The results showed that there is a strong positive correlation between the variables transport distance and the freight cost of the wood, as well as between the moisture content of the wood and the freight cost of the wood. The load capacity of the vehicle combinations showed a mean negative correlation with the freight cost of the wood, and the length of the wood did not show a correlation with the cost of the transported wood. The fitted models for estimating the value of wood freight showed a high degree of adjustment of the dependent variable, indicating a good capacity for extrapolating the results from these variables. Such results emphasize the importance of optimizing transport routes, controlling wood moisture, maximizing vehicle volumetric load capacity, and using cost forecast models in order to make correct and efficient decisions in the forest supply chain context.
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