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The authors test methods, based on cognitively simple decision rules, that predict which products consumers select for their consideration sets. Drawing on qualitative research, the authors propose disjunctions-of-conjunctions (DOC) decision rules that generalize well-studied decision models, such as disjunctive, conjunctive, lexicographic, and subset(More)
W e develop and test an active-machine-learning method to select questions adaptively when consumers use heuristic decision rules. The method tailors priors to each consumer based on a " configurator. " Subsequent questions maximize information about the decision heuristics (minimize expected posterior entropy). To update posteriors after each question, we(More)
(MIT) for their insights, inspiration, and help on this project. Abstract We propose and test an active-learning algorithm to estimate heuristic decision rules that consumers use to form consideration sets for automobile purchases. The complexity of the product (large number of features and levels) and the non-linearity in models of heuristic decisions lead(More)
With the proliferation of multiple sales channels, a firm's operational decisions must account for the switching of consumers between different channels during their purchase process. This paper considers the assortment problem faced by a firm selling products that vary on multiple features through an online and an offline channel. The firm carries a(More)
Kayande Ujwal, and from participants in a seminar given at University of Houston and a presen-Abstract We investigate the feasibility of unstructured direct-elicitation (UDE) of decision rules consumers use to form consideration sets. With incentives to think hard and answer truthfully, tested formats ask respondents to state non-compensatory, compensatory,(More)
Consumers often learn their preferences as they search. For example, after test driving new cars, a consumer might find she undervalued trunk space and overvalued sunroofs. Preference learning makes search complex because, each time a product is searched, updated preferences affect the value of all products and the value of subsequent (optimal) search.(More)
Acknowledgment: We thank the Keller Fay Group for the use of their data and their groundbreaking efforts to collect, manage, and share the TalkTrack data. We gratefully acknowledge our research assistants at the Hebrew University-Abstract Practitioners have a widely-held belief that brand advertising strongly influences the volume of word of mouth (WOM) the(More)
Most models of consumer purchase process that are used in operations focus on purchases from a single channel, typically the offline brick-and-mortar store [3]. However, there has been a proliferation of multiple retail channels, such as online and mobile. This proliferation has created the need for operational decisions to model consumer switching between(More)
This research focuses on consumers who do not have well-formed preferences. As they search and evaluate potential products, they may become exposed to previously unconsidered attributes, and incorporate them into their decision criteria. We model this phenomenon by allowing the consumer to change the weights she assigns to different attributes during the(More)