Abstract

It is becoming increasingly easier for researchers and practitioners to collect eye tracking data during online preference measurement tasks. We develop a dynamic discrete choice model of information search and choice under bounded rationality, that we calibrate using a combination of eye-tracking and choice data. Our model extends the directed cognition model of Gabaix et al. (2006) by capturing fatigue, proximity effects, and imperfect memory encoding and by estimating individual-level parameters and partworths within a likelihood-based, hierarchical Bayesian framework. We show that modeling eye movements as the outcome of forward-looking utility maximization improves out-of-sample predictions, enables researchers and practitioners to use shorter questionnaires, and allows better discrimination between attributes.

Download PDF

Citation

Yang, Cathy, Olivier Toubia, and Martijn De Jong. "A Bounded Rationality Model of Information Search and Choice in Preference Measurement." Journal of Marketing Research 52, no. 2 (April 2015): 166-183.

Each author name for a Columbia Business School faculty member is linked to a faculty research page, which lists additional publications by that faculty member.

Each topic is linked to an index of publications on that topic.