Cost allocation in collaborative forest transportation

Abstract

Transportation planning is an important part of the wood flow chain in forestry. There are often several forest companies operating in the same region and co-ordination between two or more companies is rare. However, there is an increasing interest in collaborative planning as the potential savings are large, often in the range 5-15%. A key question is how savings should be distributed among the participants. In this paper we investigate a number of possibilities based on economic models including Shapley value, the nucleolus, separable and non-separable costs, shadow prices and volume weights. We also propose a new allocation method based on finding as equal relative profits as possible among the participants. A case study including eight forest companies is described and analyzed.

Quantitative Analysis of Uncertainty in Financial Risk Assessment of Road Transportation of Wood in Uruguay

“…The quantification of these uncertainties is a basic premise to determine the risk of the investment project. This is associated with the probability distribution of each component of the operational cost, because the transportation cost corresponds to a large proportion of the total raw material cost in wood processing plants [3].…”

“…DEP " v iwt´v f wt k u (3) where: DEP-cost of depreciation; v iwt -initial value of LCC without the value of tires; v f wt -final value of LCC without the value of tires.…”

“…Transportation cost corresponds to about one-third of the raw material cost within a wood processing plant, and it is complex to calculate because of a great deal of variables involved in the transport operation [3][4][5]. This cost is derived from the relationship between the amount of transported wood and the operational cost of the vehicle.…”

Estimates of residual fibre supply and the impacts of new bioenergy capacity from a forest sector transportation model of the Canadian Prairie Provinces

“…2 The model we have developed is essentially a forest sector supply chain optimization model (see D'Amours et al (2009) for a comprehensive review). These are often concerned with tactical and operational-level improvements, such as making more efficient use of logging trucks (Carlsson and Rönnqvist, 2007), determining the benefits of wood supply exchanges (Frisk et al, 2010), finding the best combination of possible production-distribution modifications (Vila et al, 2006), and the impact of production planning on supply chain costs (Bredström et al, 2004). However, rather than looking for efficiency gains, our objective is to develop a strategic-level tool that can be used to examine the sector-wide implications of changes to prices, costs, processing capacity and fibre supply.…”

Optimizing the Wood Value Chain in Northern Norway Taking Into Account National and Regional Economic Trade-Offs

“…Few approaches take such a point of view. Frisk et al [29] analyze models stimulating collaborative transport planning between forest companies operating in the same region. Developing an optimization problem to coordinate supply chain actors' procurement decisions, Kong et al [30] find a trade-off between alternative uses of forest products in an integrated market.…”