Applying Stochastic Multicriteria Acceptability Analysis to Forest Ecosystem Management with Both Cardinal and Ordinal Criteria

Jyrki Kangas*, Joonas Hokkanen, Annika S. Kangas, Risto Lahdelma, Pekka Salminen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

35 Citations (Scopus)

Abstract

Multicriteria decision analysis is applied to ecosystem management planning in a forest landscape. Ten alternative action plans were evaluated employing five criteria. For some criteria, cardinal measures with their associated uncertainties were obtained. For other criteria, only ordinal (ranking) information was available. The Stochastic Multicriteria Acceptability Analysis with Ordinal criteria (SMAA-O) method was used, as it accommodates both cardinal and ordinal data. This is the first application of SMAA methods to forest management. SMAA-O represents inaccurate or uncertain cardinal criteria measurements by a joint probability distribution. Ordinal data is converted into stochastic cardinal data by simulating mappings between ordinal and cardinal scales that preserve the given rankings. At the same time, the unknown or partly known preferences of the decision maker are simulated by choosing weights randomly from appropriate distributions. The main results of the analysis are "acceptability indices" that describe the variety of different weights that support an alternative for a given rank. The special characteristics of SMAA-O are best utilized in problems involving uncertainty and where both cardinal and ordinal data are to be employed. It also serves well as an analysis tool in interactive planning processes, especially when criteria weights are not known or they are difficult to assess.

Original languageEnglish
Pages (from-to)928-937
Number of pages10
JournalForest Science
Volume49
Issue number6
Publication statusPublished - Dec 2003
MoE publication typeA1 Journal article-refereed

Keywords

  • Decision analysis
  • Forest planning
  • Landscape ecology
  • Multicriteria decision support
  • Sustainable forestry

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