Daria Dzyabura

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W 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)
  • Steven P. Gaskin, Min Ding, +4 authors STEVEN P. GASKIN
  • 2010
Vol. XLVIII (February 2011), 116 –127 *Min Ding is Smeal Research Fellow in Marketing and Professor of Marketing, Smeal College of Business, Pennsylvania State University (e-mail: minding@psu.edu). John R. Hauser is Kirin Professor of Marketing (e-mail: hauser@mit.edu), and Daria Dzyabura is a doctoral student (e-mail: dariasil@mit.edu), MIT Sloan School of(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)
We test methods, based on cognitively-simple decision rules, that predict which products consumers select for their consideration sets. Drawing on qualitative research we propose dis-junctions-of-conjunctions (DOC) decision rules that generalize well-studied decision models such as disjunctive, conjunctive, lexicographic, and subset conjunctive rules. We(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)
Business at MIT (ebusiness.mit.edu), and an anonymous US automobile manufacturer. We gratefully acknowledge the contributions of our industrial collaborators, research assistants, and faculty colleagues: Abstract Two field experiments examine whether providing information to consumers about competitive products builds trust. Established theory suggests that(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)
This paper presents a novel approach to combining search and recommendations methods into one integrated system to satisfy user information seeking needs. It is shown theoretically and experimentally using simulations that the proposed combined approach outperforms "pure" search and "pure" recommendations in those cases when search is hindered by the user's(More)