Elimination-By-Cutoffs

This paper presents Elimination-By-Cutoffs (EBC), an individual-level model of choice which derives choice probabilities from the location of choice alternatives in a perceptual space. EBC is a multidimensional operationalization of Tversky’s feature-based set-theoretic Elimination-By-Aspects (EBA) model of choice. It employs monotonic and noninteractive utilities of perceptual attributes in a sequential elimination strategy to determine choice. EBC like EBA is free from the property of independence from irrelevant alternatives. Unlike the independent multinomial logit model (IML), EBC takes into consideration the effect of product similarities on the computation of choice probabilities. An empirical application is also presented in this paper. The EBC model is parameterized from readily available data and is computationally tractable. A comparison between predictions from EBC and IML is drawn using a holdout sample. Approaches for assessing the implications of alternative product positioning strategies are also developed. Finally, extensions to nonmonotonic utility functions, interactive utility functions and other directions for further work with the EBC model are discussed.