Abstract
Previous research demonstrates that feedback in decisions under risk leads people to behave as if they give less weight to rare events. We clarify the boundaries of this phenomenon and shed light on the underlying mechanisms. In a preregistered experiment, participants faced 60 different decisions-under-risk choice tasks. Each task was a choice between a safe prospect (e.g., “59 with certainty”) and a “rare disaster” gamble (“60 with p =.98; 10 otherwise”). Additionally, each option also incurred a small cost (a draw from the set {-8, -6, -4, -2, 0} was added to the payoff). After each choice, participants received full feedback concerning the (total) realized payoffs of each option. The experiment compared 2 conditions that differed in the dependency between the 2 added costs. The results reveal high sensitivity to this dependency. Underweighting of rare events (preference for the rare disaster gamble) emerged with experience only when this dependency implied that in most cases, the rare disaster alternative provides a higher outcome than the safe alternative. In contrast, when in most cases the final outcomes from the safer option were higher, feedback appeared to increase the weighting of rare events (i.e., increased preference for the safe option). Common decisions-under-risk models (e.g., prospect theory) that assume the value of each prospect is judged only as a function of its own payoff distribution cannot account for this difference. Yet, the results can be explained with the hypothesis that choice reflects reliance on small samples of past experiences with similar decision tasks.
| Original language | English GB |
|---|---|
| Pages (from-to) | 153-162 |
| Number of pages | 10 |
| Journal | Decision |
| Volume | 7 |
| Issue number | 2 |
| DOIs | |
| State | Published - 2019 |
Keywords
- Decisions from experience
- Feedback in risky choice
- The description- experience gap
ASJC Scopus subject areas
- Social Psychology
- Neuropsychology and Physiological Psychology
- Applied Psychology
- Statistics, Probability and Uncertainty
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