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    Evaluating expert advice in forecasting: users' reactions to presumed vs. experienced credibility

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    Onkal_International_Journal_of_Forecasting.pdf (1.118Mb)
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    Publication date
    2017-01
    Author
    Onkal, Dilek
    Gonul, M.S.
    Goodwin, P.
    Thomson, M.
    Esra, O.
    Keyword
    Source credibility; Presumed credibility; Experienced credibility; Advice; Forecasting; Information use
    Rights
    © 2016 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license.
    Peer-Reviewed
    Yes
    
    Metadata
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    Abstract
    In expert knowledge elicitation (EKE) for forecasting, the perceived credibility of an expert is likely to affect the weighting attached to their advice. Four experiments have investigated the extent to which the implicit weighting depends on the advisor’s experienced (reflecting the accuracy of their past forecasts), or presumed (based on their status) credibility. Compared to a control group, advice from a source with a high experienced credibility received a greater weighting, but having a low level of experienced credibility did not reduce the weighting. In contrast, a high presumed credibility did not increase the weighting relative to a control group, while a low presumed credibility decreased it. When there were opportunities for the two types of credibility to interact, a high experienced credibility tended to eclipse the presumed credibility if the advisees were non-experts. However, when the advisees were professionals, both the presumed and experienced credibility of the advisor were influential in determining the weight attached to the advice.
    URI
    http://hdl.handle.net/10454/13388
    Version
    Accepted Manuscript
    Citation
    Onkal D, Gonul MS, Goodwin P et al (2017) Evaluating expert advice in forecasting: users' reactions to presumed vs. experienced credibility. International Journal of Forecasting. 33(1): 280-297.
    Link to publisher’s version
    https://doi.org/10.1016/j.ijforecast.2015.12.009
    Type
    Article
    Collections
    Management and Law Publications

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