Constructing preference from sequential samples: The impact of evaluation format on risk attitudes

Yonatan Vanunu, Thorsten Pachur, Marius Usher

Research output: Contribution to journalArticlepeer-review

Abstract

The cognitive mechanism underlying decisions based on sequential samples has been found to be affected by whether multiple alternatives are evaluated together or whether each alternative is evaluated individually. In this experiment, we examined whether evaluation format can also lead to different preference orders among risky alternatives. We hypothesized that because of differences in computational demands posed by the 2 evaluation formats, there would be differences in the type of the cognitive mechanism deployed: a risk-return mechanism, that trades off the mean reward and risk of an alternative, or a selective-accumulator mechanism, that sums the rewards of each alternative, with a higher weight to more extreme payoffs. Each participant rated the same set of alternatives (sequences of payoffs from slot machines) in both a one-by-one and a grouped evaluation format. The mean and the variance of the payoff distributions of each alternative were varied orthogonally. As predicted, in the grouped (but not in the one-by-one) condition, the impact of the variance on participants' ratings interacted with the mean payoff. Specifically, participants were risk averse for alternatives with a low mean payoff and risk seeking for alternatives with a high mean payoff. Computational modeling showed that the majority of participants were best described by a risk-return model in the one-by-one condition but by a selective-accumulator model in the grouped condition. Our results underline the importance of studying the cognitive foundations of risk attitudes in order to understand how they are shaped by the structure of a given decision task.

Original languageEnglish
Pages (from-to)223-236
Number of pages14
JournalDecision
Volume6
Issue number3
DOIs
StatePublished - Jul 2019

Keywords

  • Computational modeling
  • Evaluation format
  • Preference construction
  • Risk attitudes
  • Value integration

All Science Journal Classification (ASJC) codes

  • Social Psychology
  • Neuropsychology and Physiological Psychology
  • Applied Psychology
  • Statistics, Probability and Uncertainty

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