Analytical group decision making in natural resources: Methodology and application

Citation
Dl. Schmoldt et Dl. Peterson, Analytical group decision making in natural resources: Methodology and application, FOREST SCI, 46(1), 2000, pp. 62-75
Citations number
69
Categorie Soggetti
Plant Sciences
Journal title
FOREST SCIENCE
ISSN journal
0015749X → ACNP
Volume
46
Issue
1
Year of publication
2000
Pages
62 - 75
Database
ISI
SICI code
0015-749X(200002)46:1<62:AGDMIN>2.0.ZU;2-L
Abstract
Group decision making is becoming increasingly important in natural resourc e management and associated scientific applications, because multiple value s are treated coincidentally in time and space, multiple resource specialis ts are needed, and multiple stakeholders must be included in the decision p rocess. Decades of social science research on decision making in groups hav e provided insights into the impediments to effective group processes and o n techniques that can be applied in a group context. Nevertheless, little i ntegration and few applications of these results have occurred in resource management decision processes, where formal groups are integral, either dir ectly or indirectly. A group decision-making methodology is introduced as a n effective approach for temporary, formal groups (e.g., workshops). It com bines the following three components: (1) brainstorming to generate ideas; (2) the analytic hierarchy process to produce judgments, manage conflict, e nable consensus, and plan for implementation; and (3) a discussion template (straw document). Resulting numerical assessments of alternative decision priorities can be analyzed statistically to indicate where group member agr eement occurs and where priority values are significantly different. An app lication of this group process to fire research program development in a wo rkshop setting indicates that the process helps focus group deliberations; mitigates groupthink, nondecision, and social loafing pitfalls; encourages individual interaction; identifies irrational judgments; and provides a lar ge amount of useful quantitative information about group preferences. This approach can help facilitate scientific assessments and other decision-maki ng processes in resource management.