Consistency in probability processing as a function of affective context and numeracy
Citations Over Time
Abstract
Abstract Processing information about probabilities is an integral part of decision making under risk. Even when objective probabilities are explicitly provided, people tend to distort them, which is reflected by an inverted S‐shaped probability weighting function. Such distortions depend on different factors such as numeracy and affect. The present study contributes to the understanding of how people use probabilities in risky decision making by introducing the concept of consistency in probability processing―a measure of how coherent people are in using objective probabilities. We hypothesized that consistency would depend on factors similar to those that influence the shape of the probability weighting function. Moreover, we predicted that probability processing consistency would be related to better decision outcomes in an experimental betting task. In three experiments, participants were presented with the probability of a potential gain/loss and had to place a bet on a given chance to maximize their total earnings. We defined probability processing consistency as the variance of bets placed on the same probability value, with higher variance indicating lower consistency. We found that consistency in probability processing was lower in relatively affect‐rich conditions and greater for people with higher numeracy. Additionally, people who exhibited more consistent processing of probabilities gained higher earnings from the experimental task irrespective of whether their betting strategy was optimal and of their risk preference. Our findings imply that consistency in processing probabilities may be an important factor in understanding betting strategies and the quality of decisions.
Related Papers
- → Extended implied weighting(2013)233 cited
- → Weighting in LCA – approaches and applications(2000)92 cited
- → The application of combination weighting approach in multiple attribute decision making(2009)9 cited
- → New Internet search volume-based weighting method for integrating various environmental impacts(2015)24 cited
- → A study of weighting factors of the quadratic performance index(1969)5 cited