A Multiattribute Utility Model for Incorporating Risk in Fire Management Planning
The potential variability of investment returns often perplexes the investment selection process. On national forests, the relative efficiency of alternative fire management strategies is investigated using a modification of traditional cost plus loss methods. Current procedures do not indicate potential variability in the performance of these alternatives, however. A multiattribute utility model is presented as the appropriate framework for evaluating alternatives when decision-makers are concerned with the risk and efficiency implications of selecting a particular strategy. Among fire management planners, the term risk usually relates a perception of the variability of potential damages. A risk measure is defined and an index is created to indicate the performance of each fire management strategy relative to the potential performance of a standard established as a benchmark. Utility functions for the risk attribute were assessed using hypothetical lotteries where the value (utility) of risk was a function of its deviation from a risk benchmark. Two-attribute utility functions indicated surveyed respondents' preferences for attaining risk and efficiency related objectives. Analysis yielded two conclusions: (1) that fire management planners are not risk-averse, and (2) including risk as an attribute of the decision problem can significantly influence investment selection. Forest Sci. 32:1032-1048.
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Document Type: Journal Article
Affiliations: Professor, Department of Forest and Wood Sciences, Colorado State University, Fort Collins, CO 80523
Publication date: 1986-12-01
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Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
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2016 Impact Factor: 1.782 (Rank 17/64 in forestry)
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June 1, 2016 to Feb. 28, 2017
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