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Random Consideration Set Model We operationalize a microfounded consumer choice model—the random consideration set (RCS) choice model of Manzini and Mariotti Manzini P, Mariotti M (2014) Stochastic choice and consideration sets. Econometrica 82(3):1153–1176—that captures the limited attention of consumers, assuming that purchases are based on fixed preference orderings with consideration sets formed from independent attentions. We provide a condition for uniquely identifying model parameters and design an efficient algorithm for model parameters estimation. We offer a greedy-like algorithm for assortment optimization, adaptable for optimal assortment subject to cardinality constraint or discovering efficient sets. We extend the model to consider random product preferences, with a 1/2 performance-guaranteed approximation algorithm. Using data from a major U.S. airline, we find that the RCS model outperforms the mixed multinomial logit model in approximately half of the markets, particularly with smaller, less varied data sets.
Gallego et al. (Mon,) studied this question.