Exploring group dynamics in deliberative choice experiments

© 2016 Elsevier B.V. Deliberative monetary valuation has emerged as a promising alternative to conventional stated preference studies of ecosystem services. It promises to give respondents a better basis for decision-making by exposing them to a more diverse set of knowledge, arguments and opinions...

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Bibliographic Details
Main Authors: Marc Völker, Nele Lienhoop
Other Authors: Helmholtz Zentrum für Umweltforschung
Format: Article
Published: 2018
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Online Access:https://repository.li.mahidol.ac.th/handle/123456789/40573
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Institution: Mahidol University
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Summary:© 2016 Elsevier B.V. Deliberative monetary valuation has emerged as a promising alternative to conventional stated preference studies of ecosystem services. It promises to give respondents a better basis for decision-making by exposing them to a more diverse set of knowledge, arguments and opinions through group discussion. However, under certain conditions, small groups may fail to effectively pool the individual knowledge of their members. This paper examines the impact of the initial distribution of individual preferences in discussion groups on the outcome of deliberative choice experiments. Drawing on a deliberative monetary valuation study of forest ecosystem services in West Saxony, Germany, it is shown that the initial preference distribution in groups influences both the diversity of arguments exchanged during group discussions and respondents' consideration of the costs of environmental policies. Furthermore, results indicate that respondents' post-discussion willingness-to-pay is affected by the initial preference distribution in groups, though these changes were not statistically significant. The choice certainty of respondents was found to remain largely unaffected. Overall, the empirical findings of this study provide preliminary evidence about the need to conduct future deliberative monetary valuation studies with groups with heterogeneous initial preferences as this may provide respondents with a more complete set of decision-relevant information.