Biased expectations about future choice options predict sequential economic decisions.

ABSTRACT: Considerable research has shown that people make biased decisions in "optimal stopping problems", where options are encountered sequentially, and there is no opportunity to recall rejected options or to know upcoming options in advance (e.g. when flat hunting or choosing a spouse). Here, we used computational modelling to identify the mechanisms that best explain decision bias in the context of an especially realistic version of this problem: the full-information problem. We eliminated a number of factors as potential instigators of bias. Then, we examined sequence length and payoff scheme: two manipulations where an optimality model recommends adjusting the sampling rate. Here, participants were more reluctant to increase their sampling rates when it was optimal to do so, leading to incre

SUBMITTER: van de Wouw DS 

PROVIDER: S-EPMC11655870 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature