Moody experts — How mood and expertise influence judgmental anchoring
Journal Title: Judgment and Decision Making - Year 2009, Vol 4, Issue 1
Abstract
Anchoring effects, the assimilation of numerical estimates to previously considered standards, are highly robust. Two studies examined whether mood and expertise jointly moderate the magnitude of anchoring. Previous research has demonstrated that happy mood induces judges to process information in a less thorough manner than sad mood, which means that happy judges tend to be more susceptible to unwanted influences. However, this may not be true for anchoring effects. Because anchoring results from an elaborate process of selective knowledge activation, more thorough processing should lead to more anchoring; as a result, sad judges should show stronger anchoring effects than happy judges and happy judges may even remain uninfluenced by the given anchors. Because information processing of experts may be relatively independent of their mood, however, mood may influence anchoring only in non-experts. Results of two studies on legal decision-making (Study 1) and numeric estimates (Study 2) are consistent with these expectations. These findings suggest that, at least for non-experts, positive mood may eliminate the otherwise robust anchoring effect.
Authors and Affiliations
Birte Englich and Kirsten Soder
Keywords
Related Articles
- EP ID EP677659
- DOI -
- Views 151
- Downloads 0
Naturalness judgments by lay Americans: Process dominates content in judgments of food or water acceptability and naturalness
This study directly tests the hypothesis that, at least within the domains of food and drink for Americans, the judgment of naturalness has more to do with the history of an object, that is the processes that it has unde...
The collective intelligence of random small crowds: A partial replication of Kosinski et al. (2012)
We examined the trade-off between the cost of response redundancy and the gain in output quality on the popular crowdsourcing platform Mechanical Turk, as a partial replication of Kosinski et al. (2012) who demonstrated...
A shift in strategy or “error”? Strategy classification over multiple stochastic specifications
We present a classification methodology that jointly assigns to a decision maker a best-fitting decision strategy for a set of choice data as well as a best-fitting stochastic specification of that decision strategy. Our...
Number preferences in lotteries
We explore people’s preferences for numbers in large proprietary data sets from two different lottery games. We find that choice is far from uniform, and exhibits some familiar and some new tendencies and biases. Players...
Actor/observer asymmetry in risky decision making
Are people willing to gamble more for themselves than what they deem reasonable for others? We addressed this question in a simplified computer gambling task in which subjects chose from a set of 10 cards. Subjects selec...