This paper is dedicated to the fond memory of A.A.J. Marley, who passed away on June 14, 2021 at the age of 81. Its topic was a major area of interest for Tony.

We propose a general mathematical framework for context-dependent random utility.

Context-dependent random utility models need not satisfy regularity.

We find an attraction effect in a new variation on a classic consumer choice problem.

The attraction effect is best explained by context-dependent, rational inferences.

Classical random utility models imply a consistency property called regularity. Decision makers who satisfy regularity are at least as likely to choose an option x from a set X of available options as from any larger set Y that contains X. In light of ample empirical evidence for context-dependent choice that violates regularity, some researchers have questioned the descriptive validity of all random utility models. In this article, we show that not all random utility models imply regularity. We propose a general framework for random utility models that accommodate context dependence and may violate regularity. Mathematically, like the classical models, context-dependent random utility models form convex polytopes. They yield behavioral predictions for those choice sets from which choices are made, by specifying combinations of preference rankings across two or more contexts. We discuss how context-dependent models can be less or more parsimonious than the classical models. Random utility models with or without regularity can be tested with contemporary methods of order-constrained inference.

Context effects

Decision making

Preference

Stochastic choice

Utility theory

The data are available at the project’s OSF site.

© 2025 The Authors. Published by Elsevier Inc.