Robust Dynamic Pricing with Demand Learning in the Presence of Outlier Customers

51 Pages Posted: 13 Aug 2020

See all articles by Xi Chen

Xi Chen

New York University (NYU) - Leonard N. Stern School of Business

Yining Wang

University of Florida - Warrington College of Business Administration

Date Written: July 14, 2020

Abstract

This paper studies the dynamic pricing problem under model mis-specifi cation settings. To characterize the model mis-specification, we extend the "eps-contamination model | the most fundamental model in robust statistics and machine learning, to the online setting. In particular, for a selling horizon of length T, the online "eps-contamination model assumes that the demands are realized according to a typical unknown demand function only for (1-eps)T periods. For the rest of eps T periods, an outlier purchase can happen with arbitrary demand functions. Under this model, we develop new robust dynamic pricing policies to hedge against outlier purchase behavior. For the dynamic pricing problem, there are two critical prices, the revenue-maximizing price and inventory clearance price, and the optimal price is the larger price. The challenge is that the seller has no information about which price is larger, and the revenues near these two prices behave entirely differently. To address this challenge, we propose robust online policies for both cases when the optimal price is the revenue-maximizing price and when the optimal price is the clearance price, and then develop a meta algorithm that combines these two cases. Our algorithm is a fully adaptive policy that does not require any prior knowledge of the outlier proportion parameter ". Our simulation study shows that our policy outperforms existing policies in the literature.

Keywords: dynamic pricing, regret analysis, robustness, eps-contamination model

Suggested Citation

Chen, Xi and Wang, Yining, Robust Dynamic Pricing with Demand Learning in the Presence of Outlier Customers (July 14, 2020). NYU Stern School of Business , Available at SSRN: https://ssrn.com/abstract=3650656 or http://dx.doi.org/10.2139/ssrn.3650656

Xi Chen

New York University (NYU) - Leonard N. Stern School of Business ( email )

44 West 4th Street
Suite 9-160
New York, NY NY 10012
United States

Yining Wang (Contact Author)

University of Florida - Warrington College of Business Administration ( email )

Gainesville, FL 32611
United States

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