Department of Natural Resources and Environmental Sciences, University of Illinois, Urbana, Illinois 61801, USA, US.
Environ Manage. 2000 Dec;26(6):659-73. doi: 10.1007/s002670010123.
This paper describes an application of multiple criteria analysis (MCA) in assessing criteria and indicators adapted for a particular forest management unit. The methods include: ranking, rating, and pairwise comparisons. These methods were used in a participatory decision-making environment where a team representing various stakeholders and professionals used their expert opinions and judgements in assessing different criteria and indicators (C&I) on the one hand, and how suitable and applicable they are to a forest management unit on the other. A forest concession located in Kalimantan, Indonesia, was used as the site for the case study. Results from the study show that the multicriteria methods are effective tools that can be used as structured decision aids to evaluate, prioritize, and select sets of C&I for a particular forest management unit. Ranking and rating approaches can be used as a screening tool to develop an initial list of C&I. Pairwise comparison, on the other hand, can be used as a finer filter to further reduce the list. In addition to using these three MCA methods, the study also examines two commonly used group decision-making techniques, the Delphi method and the nominal group technique. Feedback received from the participants indicates that the methods are transparent, easy to implement, and provide a convenient environment for participatory decision-making.
本文描述了一种多标准分析（MCA）在评估特定森林管理单元适应的标准和指标中的应用。该方法包括：排名、评分和成对比较。这些方法在一个参与式决策环境中使用，代表各种利益相关者和专业人员的团队一方面利用他们的专家意见和判断来评估不同的标准和指标（C&I），另一方面评估它们对森林管理单元的适宜性和适用性。印度尼西亚加里曼丹的一个森林特许权被用作案例研究的地点。研究结果表明，多标准方法是有效的工具，可以用作结构化决策辅助工具来评估、优先排序和选择特定森林管理单元的标准和指标集。排名和评分方法可用作筛选工具来制定标准和指标的初始清单。另一方面，成对比较可用于进一步缩小列表的更细的筛选器。除了使用这三种 MCA 方法外，本研究还考察了两种常用的群体决策技术，即德尔菲法和名义群体技术。参与者的反馈表明，这些方法是透明的，易于实施，并为参与式决策提供了便利的环境。
