Comparison of four measures designed for assessing the fit between the demand and output distributions of logs

In recent years, as customer-oriented production strategies have gained ground, especially in the sawmill industry, the fit between the demand and the actual output for logs of different sizes and qualities has become an important criterion for evaluating bucking outcomes. In this paper, we present four measures for determining the similarity between the demand and output log distributions: (1) the apportionment degree, (2) the X^2 statistic, (3) Laspeyresʹ quantity index, and (4) the price-weighted apportionment degree. The potential of each measure for determining similarity was analyzed in two ways. (1) In an experiment involving 10 artificial Norway spruce (Picea abies (L.) Karst.) stands and two demand matrices for spruce logs, each study stand was harvested using a bucking simulator and the resulting log distributions were then compared with the desired distribution in each of the four measures. (2) The advantages and disadvantages of the measures were analyzed in relation to the requirements for an ideal goodness-of-fit measure. Both analyses suggested that not one of the four measures tested is superior, but that all can be used in actual wood procurement.