Returning advice taking to the wild: Empirical, theoretical, and normative implications of an ecological perspective

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dc.contributor.advisor Hütter, Mandy (Jun. Prof. Dr.) Ache, Fabian 2017-10-05T05:29:50Z 2017-10-05T05:29:50Z 2019-10-04
dc.identifier.other 1678196401 de_DE
dc.identifier.uri de_DE
dc.description.abstract Advice taking constitutes a strategy to increase judgment accuracy that builds on existing ecological structures. Specifically, averaging the own judgment with that of others yields an increase in expected accuracy. Moreover, many decision situations are inherently interactive, thereby offering the opportunity to acquire advice before producing a final judgment. Theoretically, advice taking is thus highly adaptive. However, research on advice taking hinges on three core problems: the uncertain adaptivity of advice taking behavior; the lack of a unifying theoretical framework; and the conceptual constraints of existing research. First, whereas averaging the own judgment and the advice yields highest expected accuracy, individuals often place a relatively low weight on the advice during judgment revision. Second, there is no theoretical framework to integrate the many determinants of advice taking already identified. Third, advice taking research almost exclusively focused on the weighting of advice once it is received, thereby neglecting information search. The current thesis addresses these three problems from an ecological perspective. This perspective assumes that the interactive nature of advice taking affords the individual with the opportunity to seek additional information. Specifically, advice taking is conceptualized as a sequential process that can be truncated at different points in time, for example after consulting different amounts of advice. To this end, the current thesis introduces an expanded advice taking paradigm that allows individuals to sample any number of other people’s judgments before revising their own. The current thesis proposes an information integration account of advice taking that expands existing theoretical ideas, incorporates information search and integrates the most important determinants of advice taking as identified by existing research. The adaptivity of advice taking is re-evaluated from this ecological perspective. A simulation assesses which integration strategy fares best in an environment that accords to the ecological perspective advocated in this thesis. Experiments investigate whether individuals explore and adapt to the information ecology when given the opportunity. The results suggest that advice taking is much more adaptive than previously documented. Placing a low weight on the advice yields higher accuracy than weighting the own judgment and the advice equally when advice taking is a sequential process with several steps of updating. Moreover, individuals explore and adapt to the information ecology when given the opportunity. The experimental data also support the proposed theoretical framework of advice taking. This thesis provides strong evidence that the ecological nature of advice taking can no longer be neglected by advice taking research. Further discrepancies between advice taking in the laboratory and advice taking in the wild, necessary steps to further validate the proposed theoretical account, and future directions to investigating the adaptivity of advice taking are discussed. en
dc.language.iso en de_DE
dc.publisher Universität Tübingen de_DE
dc.rights ubt-podok de_DE
dc.rights.uri de_DE
dc.rights.uri en
dc.subject.classification Urteilen , Entscheidungsverhalten de_DE
dc.subject.ddc 150 de_DE
dc.subject.other advice taking en
dc.subject.other advice seeking en
dc.subject.other ecological perspective en
dc.subject.other sampling approach en
dc.title Returning advice taking to the wild: Empirical, theoretical, and normative implications of an ecological perspective en
dc.type Dissertation de_DE
dcterms.dateAccepted 2017-09-26
utue.publikation.fachbereich Psychologie de_DE
utue.publikation.fakultaet 7 Mathematisch-Naturwissenschaftliche Fakultät de_DE


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