We characterize a generalization of discounted logistic choice that incorporates a parameter to capture different views the agent might have about the costs and benefits of larger choice sets. The discounted logit model used in the empirical literature is the special case that displays a “preference for flexibility” in the sense that the agent always prefers to add additional items to a menu. Other cases display varying levels of “choice aversion,” where the agent prefers to remove items from a menu if their ex ante value is below a threshold. We show that higher choice aversion, as measured by dislike of bigger menus, also corresponds to an increased preference for putting off decisions as late as possible.

Perturbed utility functions—the sum of expected utility and a non-linear perturba-tion function—provide a simple and tractable way to model various sorts of stochastic choice. We provide easily understood conditions that characterize this representation by generalizing the acyclicity condition used in revealed preference theory. We show how to relax Luce’s IIA condition to model cases where the agent finds it harder to discriminate between items in larger menus, and how to extend the perturbation-function approach to model choice overload and nested decisions. We also show that these representations correspond to a form of ambiguity-averse preferences for an agent who is uncertain about her true utility