Year: 2026
Type: dissertation
Abstract: This thesis explores the role of self-reported affect in recurrent decision-making, with a particular focus on how both current and expected emotions influence choices over time. Three studies were conducted to investigate the impact of current and expected valence on decision-making in various contexts. The first study examined the predictive power of expected affect in a recurrent gambling task, where expected valence was found to be the strongest predictor of choice. The second study expanded on this by exploring the interaction between current and expected affect, revealing that both types of emotions contribute to decision-making depending on task context. The third study emphasized the importance of time horizons, showing that short-term and long-term expectations interact differently based on the nature of the decision, such as point-loss versus point-omission scenarios. These findings suggest that emotional ex-pectations, as well as current emotional states, are essential components in predicting choices and that the subjective affective system adapts to varying contextual demands. The results also highlight the need for a more nuanced approach to measuring affect, integrating both expected and current emotions to better understand decision-making across a range of contexts. This work provides valuable insights into how emotions guide choices in both financial and non-financial domains, offering implications for fu-ture research on emotion-driven decision-making.
DOI: 10.20378/irb-112535
Author: Jäger, Daniel
Language: English
Subfield: General Decision Sciences
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
OpenAlex ID: W7124941435