ABSTRACT

This paper uses Data Envelopment Analysis (DEA) to evaluate how the technical efficiency of forest harvesting operations is influenced by terrain conditions and forest attributes, in addition to exploring the existence of other influencing factors. To this end, 643 shift-level observations of harvesting operations on 253 distinct harvested sites were used. The aim of this study is to highlight the harvester’s ability to maximize the outputs, represented by the number of assortments for various tree species, given inputs such as harvest volume, harvest time for various tree species, and distance traveled by the harvester. Operational environment variables such as harvest, or decision-making unit (DMU) size, shape, and terrain characteristics were included. We found large variations in efficiency scores, and that inefficient harvest operations could theoretically be improved by reducing input by up to ca. 80%. A second stage regression estimation was applied to identify which factors significantly affected inefficiency. It was found that the inefficiency decreases with increasing stem-volume for pine and broadleaves, increasing stand density, and increasing share of pulpwood and non-marketable timber, while it increases with the number of logs produced per tree (in broadleaves). Inefficiency increases also with an increasing ratio of actual travel distance to minimal travel distance. The study shows how adopting DEA methods in forest operations might be used in combining efficiency analysis and environmental factors, by identifying and measuring inefficiency due to, for example, difficult terrain.

摘要

本文使用数据包络分析（DEA）来评估森林采伐作业的技术效率如何受地形条件和森林属性的影响，此外还探讨了其他影响因素的存在。为此，对 253 个不同收获地点的收获作业进行了 643 次轮班观察。本研究的目的是强调收割机最大限度地提高产量的能力，由各种树种的分类数量表示，给定输入，如收割量、各种树种的收获时间和收割机行进的距离。包括收获或决策单元 (DMU) 大小、形状和地形特征等操作环境变量。我们发现效率得分差异很大，理论上可以通过减少高达约 80%。应用第二阶段回归估计来确定哪些因素显着影响了低效率。研究发现，低效率随着松树和阔叶树的茎体积增加、林分密度的增加以及纸浆木材和非销售木材的份额增加而降低，而随着每棵树（阔叶树）生产的原木数量增加，这种情况会增加。低效率也随着实际行驶距离与最小行驶距离之比的增加而增加。该研究表明，如何在森林作业中采用 DEA 方法，通过识别和测量因地形复杂等导致的低效率，将效率分析和环境因素结合起来。