Two-Sided Pricing and Learning with Inventory Constraints

December 4, 2024 2:00 PM Singapore (Registration starts at 1:50 PM)

Abstract

Motivated by online used-car platforms, we study pricing decisions for purchasing and selling a product in a two-sided market. With uncertainty and incomplete information from both supply and demand, a platform sequentially adjusts purchase and selling prices to maximize profit while satisfying inventory constraints. Despite the two sides of uncertainty, we show that a fixed-price policy is asymptotically optimal when supply and demand functions are known. We further propose a learning algorithm that targets the fixed-price policy and achieves the best possible regret. Our work provides insights into how the platform can manage demand and supply in the presence of the two sides of uncertainty and learning.

PAPERS

Available at SSRN: https://ssrn.com/abstract=4727809

About the Speaker

Meichun Lin is an Assistant Professor of Operations Management at Lee Kong Chian School of Business, Singapore Management University. Her research focuses on data-driven decision making with applications such as dynamic pricing and inventory management. Her work has been published in top-tier journals such as Operations Research, Management Science, and Production and Operations Management.

For more information about the ESD Seminar, please email esd_invite@sutd.edu.sg