Abstract:The uncertainty in road transportation of wood is inherent to its operational costs, to the amount of transported wood, to the traveled distance, to its revenue, and more. Although it is not possible to measure this uncertainty fully, it can be quantified by the investment risk, which is the probability and degree of financial loss. The objective of this study is to quantify the financial risk of the investment in wood transportation through Monte Carlo simulation, which uses realistic situations to estimate the operational cost of vehicles used for road transportation of wood. We quantify these uncertainties by assessing financial risk and building pseudorandom scenarios with the Monte Carlo simulation method, in addition to the Net Present Value techniques, the Modified Internal Rate of Return, and the Profitability Index, all commonly used in financial investment projects. The results show that the estimated operational costs are equivalent to the actual ones, along with the evidence that the cost of fuel, the driver's manpower, and tires are components that mainly increase the degree of financial risk for an investment project in road transportation of wood. In contrast, optimizing the amount of transported wood and maximizing wood transportation cost have a significant and positive correlation with the volume of transported wood and the average price of wood transportation, leading to a reduction in the degree of financial risk.

The constant technical and economic analysis of timber harvesting operations is essential and determining, due to the monetary magnitude. Traditionally, these analyses are conducted deterministically, which does not allow obtaining values with probabilities of occurrence. Considering this issue, stochastic models were built in order to analyze the behavior of probabilistic production cost in felling operations with feller-buncher, through the Monte Carlo method. The study was conducted in the Central-West region of the state of São Paulo in a forest of Eucalyptus sp., with six years of age, planted in 3 x 2 m spacing. Technical analysis was based on the study of time and movements, which determined the effective productivity and economy in the hourly operating cost of the feller-buncher and in the production costs of the operation. Due to uncertainties, probability distributions were assigned to these results, which identified the most relevant variables and quantified the probabilities of the production cost. The results demonstrated that the fuel cost had a statistically significant strong positive correlation coefficient ( = 0.91) (p-value < 0.01). The hourly cost, consequently, was directly proportional to the production cost of the operation. The production cost of the operation in flat relief was 18% lower than the production cost of the operation in undulating relief. Keywords: Harvest, time and movements, productivity, operational risk, cost. ResumoIncorporação da incerteza na análise técnica e econômica de um feller buncher. A constante análise técnica e econômica das operações de colheita florestal possui caráter essencial e determinante, devido à magnitude dos valores monetários. Tradicionalmente, essas análises são realizadas de forma determinística, o que não permite a obtenção de valores com probabilidades de ocorrência. Nesse sentido, foram construídos modelos estocásticos para analisar o comportamento do custo probabilístico de produção na operação de derrubada com feller buncher, por meio do método de Monte Carlo. O estudo foi conduzido na região Centro-Oeste do estado de São Paulo em uma floresta de Eucalyptus sp. com seis anos de idade, plantada em espaçamento de 3 x 2 m. A análise técnica foi pautada no estudo de tempos e movimentos, determinando-se a produtividade efetiva e a econômica no custo operacional horário do feller buncher e nos custos de produção da operação. Por conterem incertezas, a esses resultados, foram atribuídas distribuições de probabilidade, que permitiram identificar as variáveis mais relevantes e quantificar as probabilidades do custo de produção. Constatou-se que o custo com combustível possui coeficiente de correlação positiva forte ( = 0,91), estatisticamente significativo (valor p < 0,01). O custo horário, por consequência, foi diretamente proporcional ao custo de produção da operação. O custo de produção da operação em relevo plano foi 18% inferior ao custo de produção da operação em relevo ondulado. Palavras-chaves: Colheita, tempos e movimentos, produtivi...

Atualmente a matriz energética brasileira é considerada limpa, quando comparada às matrizesde outros países. Nos últimos anos houve uma diversificação nas fontes primárias, reduzindoa dependência do petróleo, utilizando-se da hidroeletricidade e, mais recentemente, dabiomassa para gerar energia elétrica. Por meio do levantamento de dados secundários, estetrabalho apresenta uma reflexão a respeito da disponibilidade hídrica brasileira para geraçãode energia elétrica. Verifica-se que, apesar da ideia de abundância, sua distribuição não éhomogênea e a real necessidade de expansão da geração de energia elétrica apresenta-se comcustos cada vez mais crescentes.

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Goal: In this paper, a binomial model is proposed to evaluate the option of deferring an investment and expanding the operational scale of a forest-based company that will perform the de-duplication of Pinus sp. and will market packaging for storage and transportation of vegetables. Design/Methodology/Approach: The proposed model measured the options of deferring an investment and expanding the operational scale of the forest-based company. In this perspective, the model of evaluation used was the binomial model in discrete time using the Real Options. Results: It was observed that the inclusion of management flexibilities in the decision making process has added value to the investment project; therefore, the project of investments in real assets proved to be economically feasible. Limitations of the investigation: The studies that address the corporate finance framework based on real data are a restrictive factor, due to the lack of collaboration of companies, that is, the availability of information that is usually classified. Practical implications: The study was based on the real data of a company; therefore, it can be adopted as a stimulus to the Real Options approach to the decision making of entrepreneurs or researchers. Originality/value: The focus of the study was to contemplate the managerial flexibilities of an industry of the secondary sector of the Brazilian economy, which performs the unfolding of wood, demonstrating the innovation of the technique approach used in this market segment.

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The processing of Eucalyptus logs is a stage that follows the full tree system in mechanized forest harvesting, commonly performed by grapple saw. Therefore, this activity presents some associated uncertainties, especially regarding technical and silvicultural factors that can affect productivity and production costs. To get around this problem, Monte Carlo simulation can be applied, or rather a technique that allows to measure the probabilities of values from factors that are under conditions of uncertainties, to which probability distributions are attributed. The objective of this study was to apply the Monte Carlo method for determining the probabilistic technical-economical coefficients of log processing using two different grapple saw models. Field data were obtained from an area of forest planted with Eucalyptus, located in the State of São Paulo, Brazil. For the technical analysis, the time study protocol was applied by the method of continuous reading of the operational cycle elements, which resulted in production. As for the estimated cost of programmed hour, the applied methods were recommended by the Food and Agriculture Organization of the United Nations. The incorporation of the uncertainties was carried out by applying the Monte Carlo simulation method, by which 100,000 random values were generated. The results showed that the crane empty movement is the operational element that most impacts the total time for processing the logs; the variables that most influence the productivity are specific to each grapple saw model; the difference of USD 0.04 m3 in production costs was observed between processors with gripping area of 0.58 m2 and 0.85 m2. The Monte Carlo method proved to be an applicable tool for mechanized wood harvesting for presenting a range of probability of occurrences for the operational elements and for the production cost.