Economic assessment and risk management for different distances of timber transport by road

Abstract

Among the various activity involving in the forestry sector, the timber transport shows strategic importance in production costs. Through the economic expressiveness and the uncertainties related to the transport activity, the objective of this research was to carry out a financial analysis and risk simulation in the outsourced forest transport activity. Revenues were determined by the amount paid for freight to the outsourced company, considering three transport distances evaluated (US$/m³), as well as the volume of wood transported by cargo vehicle composition (50 m³). The cost was determined by calculating the operating cost per effective hour of work, through fixed, variable and administrative costs. The study was carried out in a forestry company located in the north coast of Bahia state, Brazil, that carries out the forest transportation through an outsourced service contract, to conduct the logs from the roadside to the furnace. The company belongs to the steel industry and uses, as raw material, eucalyptus wood from its own planting. Three transport distances were evaluated: 10 km, 14 km and 20 km. It was used the indicators NPV, IRR, VAE, RB/C and CMP for economic analysis and the indicator NPV for simulating risk scenarios in the forest transport activity. The results showed viability for all indicators: US$ 5.657,58 (NPV); 8,23% (IRR); US$ 824,23 (VAE); 1,05 (RB/C) and $ 2,24 (CMP), considering transport distance of 10 km; US$ 72.563,96 (NPV); 18,34% (IRR); $ 10.571,55 (VAE); 1.05 (RB / C) and $ 2.38 (CMP), considering the transport distance of 14 Km and $251.807,75 (NPV); 27,3% (IRR); $36.684,85 (VAE); 1.15 (RB/C) and $2.62 (CMP),considering the transport distance of 20 km. For the risk analysis, it was observed 49,0%, 30,9% and 7,4% of probability of negative NPVs for transport distances of 10, 14 and 20 km, respectively, being adopted triangular and uniform distribution and 10,000 iterations. The research showed greater risk scenario for the transport distance of 10 km being the most influential variable the vehicle acquisition value. The greater distances conditioned a scenario of lower risk and greater attractiveness for the outsourced forest transportation company.

Keywords:
Risk analysis; Cargo vehicle composition; Monte Carlo Technique