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Beyond risk preferences in sequential decision-making: How probability representation, sequential structure and
Christiane Baumann1, René Schlegelmilch2, Bettina von Helversen2
1Harvard University, United States of America.
People’s choices in sequential decision-making tasks, or optimal stopping problems, are significantly influenced by how information is presented and the task structure, not just risk preferences. Contextual factors are crucial for understanding these complex sequential choices.
Area of Science:
- Cognitive Psychology
- Behavioral Economics
- Decision Science
Background:
- Sequential decision-making is prevalent in daily life, involving optimal stopping problems with inherent search risks.
- Previous research has not consistently linked individual search behavior in these tasks to measured risk preferences.
Purpose of the Study:
- To investigate how specific characteristics of optimal stopping tasks influence decision-making beyond stable risk preferences.
- To identify contextual factors that bias choices in sequential search scenarios.
Main Methods:
- Examined optimal stopping problems with variations in information presentation (experience vs. description).
- Analyzed the impact of sequential option presentation and unequal choice frequencies (reject vs. accept).
Main Results:
- The presentation format of the sampling distribution significantly biases choices.
- Sequential presentation of options affects decision-making strategies.
- Unequal frequencies of accept/reject choices create biases in behavior.
Conclusions:
- Task-specific characteristics, such as information presentation and choice structure, play a critical role in sequential decision-making.
- Understanding human behavior in optimal stopping problems requires considering contextual factors alongside individual risk preferences.
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