Using uncertain preferential information from stakeholders to assess the acceptability of alternative forest management plans
Eyvindson, K., Öhman, K., & Nordström, E. (2018). Using uncertain preferential information from stakeholders to assess the acceptability of alternative forest management plans. Journal of Multi-Criteria Decision Analysis, 25(1-2), 43-52. https://doi.org/10.1002/mcda.1630
Published inJournal of Multi-Criteria Decision Analysis
© 2017 John Wiley & Sons. This is a final draft version of an article whose final and definitive form has been published by Wiley. Published in this repository with the kind permission of the publisher.
In forest management planning, participatory planning processes are often encouraged as a means to acquire relevant information and to enhance the stakeholders' acceptability of alternative plans. This requires the aggregation of the stakeholders' preferences that can be done in a wide variety of manners. The aggregation process strives to reduce the information into a single set of preferences that simplifies the information and allows for the use of discrete decision support tools. Depending on how the preferences are aggregated, a wide range of plan rankings can emerge. Although this range of ranking complicates the issue of plan selection, it does highlight the uncertainty involved in aggregating stakeholder preferences. In this study, we suggest an alternative method of deriving rankings for a set of alternative management options. Our proposed method suggests treating acquired preferences as the uncertain elements of a stochastic programming problem and the results provide the decision maker with the acceptability probability for each plan. The method is illustrated with a case of pairwise comparisons from a set of stakeholders representing preferences from different interest groups in a community planning process. ...
PublisherJohn Wiley & Sons Ltd.
Publication in research information system
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Related funder(s)Academy of Finland
Funding program(s)Academy Project, AoF
Additional information about fundingK. E. is grateful to the Academy of Finland (proj. 275329) for funding.
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