Discrete choice experiments with eye-tracking: How far we have come and ways forward

With the increased affordability of eye-tracking technology, its applications in discrete choice experiments (DCEs) are rapidly increasing. It is critical to understand the current state of research, challenges, and potential value of this technology for future studies. This article provides an interdisciplinary perspective on three main themes of this literature – (i) utilizing visual attention measures to identify the effect of top-down and bottom-up processing on information search and preferences, (ii) modelling advancements to incorporate visual attention measures into the discrete choice models, (iii) examining the effect of the DCE design on the consumer's information search processes. Then, we highlight four areas of improvement in these themes. First, visual attention measures alone might not be sufficient proxies for representing information processing. We lay out a research agenda to precisely measure information processing by integrating eye-tracking and electroencephalogram (EEG) data. Second, traditional static behaviour models do not effectively leverage the dynamic nature of eye-tracking data. We propose to adapt dynamic behavioural models from cognitive psychology where the mathematical representation of the decision-making process is consistent with the eye-tracking data. Third, existing studies provide descriptive (instead of prescriptive) insights about the effect of DCE design on information search. Thus, instead of DCE design, eye-tracking data can be used ex-post to select behavioural models aligned with observed search patterns. Fourth, convenience sampling protocols in eye-tracking studies raise questions about the internal validity of findings. Future DCEs with eye-tracking should adopt protocols used in randomised control trial studies.

Duke Scholars

Author Semra Ozdemir Population Health Sciences