ABSTRACT

The forestry sector is constantly looking for ways for making data-driven decisions and improving efficiency. The application of Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) allow the users to go beyond looking at simple key performance indicators. Benchmarking is one of the most common tools in business for improving efficiency and competitiveness. This study searched for benchmarking studies in Web of Science until December 2020. It reviewed 56 benchmarking studies in forestry and discusses the potential advantages of using benchmarking in forestry. More than 80% of the studies apply DEA. This review found that almost half of the benchmarking studies in forestry have attempted to estimate the efficiency of forest management organizations at regional scale, mostly being public or state-owned forest districts. A bit more than one-third of the studies have focused on benchmarking forest industries and one-fifth, benchmarking of forest operations. Forest management organizations mainly applied benchmarking for internal comparison and forest industries entirely focused on competitive benchmarking. Surprisingly, in most cases the studies do not necessarily overlap geographically with forest rich countries (e.g., Russian Federation or Brazil). A number of studies address multiple criteria. The future potential for applying automatic data transfer from harvest machines to interactive benchmarking systems are discussed. Finally, the paper discusses the advantages and weaknesses of benchmarking and future research on improving usefulness and usability of benchmarking in forest businesses.

摘要

林业部门一直在寻找制定数据驱动决策和提高效率的方法。数据包络分析 (DEA) 和随机前沿分析 (SFA) 的应用使用户能够超越简单的关键性能指标。基准测试是企业提高效率和竞争力的最常用工具之一。本研究在 2020 年 12 月之前在 Web of Science 中搜索了基准研究。它回顾了 56 项林业基准研究，并讨论了在林业中使用基准的潜在优势。超过 80% 的研究应用了 DEA。该审查发现，几乎一半的林业基准研究试图估计区域范围内森林管理组织的效率，主要是公共或国有林区。超过三分之一的研究侧重于对森林工业进行基准测试，五分之一侧重于对森林作业进行基准测试。森林经营组织主要采用对标进行内部比较，林业完全侧重于竞争对标。令人惊讶的是，在大多数情况下，这些研究在地理上并不一定与森林丰富的国家（例如俄罗斯联邦或巴西）重叠。许多研究涉及多个标准。讨论了将自动数据传输从收割机应用到交互式基准测试系统的未来潜力。最后，本文讨论了基准测试的优缺点，以及未来关于提高基准测试在林业企业中的有效性和可用性的研究。