Finding the right fit: A comparison of process assumptions underlying popular drift-diffusion models

Area of Science:

• Cognitive Psychology
• Decision Science
• Consumer Behavior

Background:

• Eye-tracking is increasingly used to study decision-making processes.
• Attention, measured by gaze duration, is hypothesized to be crucial for preference formation.
• Existing research presents diverse methodologies for investigating attention's role.

Purpose of the Study:

• To empirically test prominent processing assumptions of preference formation.
• To compare different evidence accumulation models against base models.
• To investigate the role of attention and evidence accumulation in choice behavior.

Main Methods:

• Utilized eye-tracking data to analyze decision-making processes.
• Empirically tested prototypical versions of prominent processing assumptions.
• Compared evidence accumulation models, including those with leakage and temporal variability, against base models.

Main Results:

• General evidence accumulation processes provided a good fit to aggregate choice and decision time data.
• A model incorporating leakage and primacy effects explained aggregate data across various choice types and option numbers.
• Simpler models were found to better capture individual-level choice data for a majority of participants.

Conclusions:

• Evidence accumulation models, particularly those accounting for temporal dynamics, are valuable for understanding aggregate choice.
• Individual decision-making may be better represented by simpler models, highlighting heterogeneity in cognitive processes.
• Findings have implications for both theoretical models of preference and practical applications in marketing and behavioral economics.