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 173
- Downloads 0
How different types of participant payments alter task performance
Researchers typically use incentives (such as money or course credit) in order to obtain participants who engage in the specific behaviors of interest to the researcher. There is, however, little understanding or agreeme...
Predicting elections: Experts, polls, and fundamentals
This study analyzes the relative accuracy of experts, polls, and the so-called ‘fundamentals’ in predicting the popular vote in the four U.S. presidential elections from 2004 to 2016. Although the majority (62%) of 452 e...
Recognition judgments and the performance of the recognition heuristic depend on the size of the reference class
In a series of three experiments, participants made inferences about which one of a pair of two objects scored higher on a criterion. The first experiment was designed to contrast the prediction of Probabilistic Mental M...
FFTrees: A toolbox to create, visualize, and evaluate fast-and-frugal decision trees
Fast-and-frugal trees (FFTs) are simple algorithms that facilitate efficient and accurate decisions based on limited information. But despite their successful use in many applied domains, there is no widely available too...
On emotion specificity in decision making: Why feeling is for doing
We present a motivational account of the impact of emotion on decision making, termed the feeling-is-for-doing approach. We first describe the psychology of emotion and argue for a need to be specific when studying emoti...