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评估自然资源管理中决策者多目标偏好时替代评分技术的比较

Comparison of alternative scoring techniques when assessing decision maker's multi-objective preferences in natural resource management.

作者信息

Leskinen Pekka

机构信息

Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FIN-80101 Joensuu, Finland.

出版信息

J Environ Manage. 2007 Oct;85(2):363-70. doi: 10.1016/j.jenvman.2006.10.003. Epub 2006 Nov 22.

Abstract

A popular way to assess a decision maker's preferences in multi-objective natural resource management is to ask the decision maker to compare alternative management plans pairwisely in the ratio scale. Several numerical scoring techniques have been proposed for the ratio scale comparisons, but the performance of the alternative techniques is not fully understood. At the same time, the choice of scoring technique potentially impacts the description of the decision maker's preferences and therefore the actual management decisions. In this paper, the regression model for the ratio scale pairwise comparisons is used, and the differences between the alternative scoring techniques are studied based on two different viewpoints. The first idea is to interpret the scoring techniques as fixed models and then compare them under fixed numerical scaling. The applicability of several potential decision-making strategies is discussed in this context. The second idea is to parameterise the scoring techniques and then compare them under optimal scaling. This was possible in an artificial experiment, where the true values of the alternatives are known. The results supported the use of a geometric scoring technique. Also, the importance of assessing an appropriate scale parameter of the geometric progression is pointed out.

摘要

在多目标自然资源管理中,评估决策者偏好的一种常用方法是要求决策者在比率尺度上对替代管理计划进行两两比较。针对比率尺度比较,已经提出了几种数值评分技术,但对这些替代技术的性能尚未完全了解。同时,评分技术的选择可能会影响决策者偏好的描述,进而影响实际的管理决策。本文使用了比率尺度两两比较的回归模型,并从两个不同的角度研究了替代评分技术之间的差异。第一个思路是将评分技术解释为固定模型,然后在固定数值尺度下进行比较。在此背景下讨论了几种潜在决策策略的适用性。第二个思路是对评分技术进行参数化,然后在最优尺度下进行比较。这在一个人工实验中是可行的,在该实验中替代方案的真实值是已知的。结果支持使用几何评分技术。此外,还指出了评估几何级数适当尺度参数的重要性。

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