Using Eye-Tracking to Understand Decision-Making in Conjoint Experiments

Abstract

Conjoint experiments are popular, but there is a paucity of research on respondents’ underlying decision-making processes. We leverage eye-tracking methodology and a series of conjoint experiments, administered to university students and local community members, to examine how respondents process information in conjoint surveys. There are two main findings. First, attribute importance measures inferred from the stated choice data are correlated with attribute importance measures based on eye movement. This validation test supports the interpretation of common conjoint metrics, such as average marginal component effects (AMCEs), as measures of attribute importance. Second, when we experimentally increase the number of attributes and profiles in the conjoint table, respondents view a larger absolute number of cells but a smaller fraction of the total cells displayed. Moving from two to three profiles, respondents search more within-profile, rather than within-attribute, to build summary evaluations. However, respondents’ stated choices remain fairly stable regardless of the number of attributes and profiles in the conjoint table. Together, these patterns speak to the robustness of conjoint experiments and are consistent with a bounded rationality mechanism. Respondents adapt to complexity by selectively incorporating relevant new information to focus on important attributes, while ignoring less relevant information to reduce cognitive processing costs.