Eye-Tracking Reveals How Respondents Simplify Conjoint Choices

Conjoint Experiments Experimental Methodseye-trackingMethodology @Pol. An.Dataverse

🔎 What Was Studied and How

Conjoint experiments were paired with eye-tracking to uncover how respondents process information when making choices. The experiments were administered to university students and local community members. The design manipulated the number of attributes and the number of profiles shown in the conjoint table while recording visual attention to individual cells.

🧩 Key Findings From Attention and Choice Data

Attribute importance measures inferred from stated choices are correlated with attribute importance measures based on eye movements, supporting the interpretation of common conjoint metrics such as average marginal component effects (AMCEs) as indicators of attribute importance.
Increasing the number of attributes and profiles leads respondents to view a larger absolute number of cells but a smaller fraction of the total cells displayed.
When moving from two to three profiles, visual search shifts: respondents look more within profiles (comparing attributes inside a profile) rather than across the same attribute row, indicating a within-profile strategy for building summary evaluations.
Despite these shifts in visual search and attention, stated choices remain fairly stable across different numbers of attributes and profiles.

🧠 Why It Matters

These patterns point to robustness in conjoint experiments and align with a bounded rationality explanation: respondents adapt to increased complexity by selectively incorporating newly relevant information for important attributes while ignoring less relevant information to reduce cognitive processing costs. The eye-tracking validation bolsters confidence that AMCEs reflect attribute importance rather than being mere statistical artifacts.

🔬 Sample and Experimental Design Details

Participants: university students and local community members
Methods: series of conjoint experiments combined with eye-tracking
Manipulation: varied number of attributes and number of profiles in the conjoint table
Outcome: visual attention measures and stated choice data were compared to assess decision processes and metric validity

Article card for article: Using Eye-Tracking to Understand Decision-Making in Conjoint Experiments

Using Eye-Tracking to Understand Decision-Making in Conjoint Experiments was authored by Libby Jenke, Kirk Bansak, Jens Hainmueller and Dominik Hangartner. It was published by Cambridge in Pol. An. in 2021.