OPERATIONS, TECHNOLOGY, AND INFORMATION MANAGEMENT


Temporal Fairness in Learning and Earning: Price Protection Guarantee and Phase


RUIHAO ZHU ASSISTANT PROFESSOR


Cornell Peter and Stephanie Nolan School of Hotel Administration


Cornell SC Johnson College of Business Cornell University


Co-authors • Ruihao Zhu


Assistant Professor, Cornell Peter and Stephanie Nolan School of Hotel Administration, Cornell SC Johnson College of Business, Cornell University


• Qing Feng, School of Operations Research and Inforomation Engineering, Cornell University


• Stafanus Jasin, Ross School of Business, University of Michigan, Ann Arbor


Summary Price protection guarantee policy (in which a customer who purchased a


prodct in the past can receive a refund if the seller lowers the price during a prescribed period of time) helps to promote temporal fairness in dynamic pricing. Te authors study the impact of the policy on the design of online learning algorithms for data-driven dynamic pricing with initially unknown customer demand.


Te authors consider a setting where a firm sells a product over a horizon of T time steps, characterizing how the value of M, the length of the price protec- tion period, can affect the optimal regret of the learning process. Tey derive the optimal regret by first establishing a fundamental impossible regime with the novel refund-aware regret lower bound analysis. Ten, they propose LEAP, a phased exploration type algorithm for Learning and EArning under Price Protection, to match this lower bound up to logarithmic factors or even doubly logarithmic factors (when only two prices are available to the seller).


Tese results reveal the surprising phase transitions of the optimal regret with respect to M. Specifically, when M is not too large, the optimal regret has no major difference when compared with that of the classic setting with no price protection guarantee. In addition, there also exists an upper limit on how much the optimal regret can deteriorate when M grows large.


Transitions Operations Research, 73, 2, March 2025 LINK TO PAPER


CONTENTS TO MAIN


| RESEARCH WITH IMPACT: CORNELL SC JOHNSON COLLEGE OF BUSINESS • 2025 EDITION


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