Dynamic choice under familiarity-based attention

Evidence from consumer research indicates that people tend to focus their attention on options with which they are familiar; for this reason, they are also more likely to choose them. To study this phenomenon axiomatically, we extend the standard choice data to specify the timing of choices. This allows us to consider several (nested) time-evolving, experience-based choice models. Specifically, the agent in our theory first considers only the subset of available options with which he is familiar, and only if none of the options in this subset is satisfying (according to a fixed threshold) does he consider the entire possibility set. Importantly, we allow the set of familiar options to expand as the agent acquires experience. We provide choice-theoretic foundations for maximizing a single preference relation under this dynamic, familiarity-based attention, and show how one can reveal from the observed behavior an agent’s preferences and his threshold level. We also provide a comparative measure of preference for familiar options that is observable from choice and relate it to our main representation.