A Statistical Learning Approach to Personalization in Revenue Management
Xi Chen (),
Zachary Owen (),
Clark Pixton () and
David Simchi-Levi ()
Additional contact information
Xi Chen: Leonard N. Stern School of Business, New York University, New York, New York 10012-1126
Clark Pixton: Marriott School of Business, Brigham Young University, Provo, Utah 84602
David Simchi-Levi: Institute for Data, Systems, and Society, Department of Civil and Environmental Engineering and Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142
Management Science, 2022, vol. 68, issue 3, 1923-1937
Abstract:
We consider a logit model-based framework for modeling joint pricing and assortment decisions that take into account customer features. This model provides a significant advantage when one has insufficient data for any one customer and wishes to generalize learning about one customer’s preferences to the population. Under this model, we study the statistical learning task of model fitting from a static store of precollected customer data. This setting, in contrast to the popular learning and earning paradigm, represents the situation many business teams encounter in which their data collection abilities have outstripped their data analysis capabilities. In this learning setting, we establish finite-sample convergence guarantees on the model parameters. The parameter convergence guarantees are then extended to out-of-sample performance guarantees in terms of revenue, in the form of a high-probability bound on the gap between the expected revenue of the best action taken under the estimated parameters and the revenue generated by a decision maker with full knowledge of the choice model. We further discuss practical implications of these bounds. We demonstrate the personalization approach using ticket purchase data from an airline carrier.
Keywords: assortment optimization; personalization; price discrimination; statistical learning (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (4)
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:68:y:2022:i:3:p:1923-1937
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