Price Competition and Assortment Display in Online Marketplace

Friday, October 1, 2021 – 1pm
Speaker:
Hanwei Li
Room:
https://mit.zoom.us/j/94112513921

Abstract: Online platforms have been expanding the product assortment to match the individual preferences of the consumers. Nevertheless, the widening product selection and the increasing number of sellers intensify the competition on the platform and result in sellers setting lower prices for the products. Thus, it is unclear if the current practice employed by most platforms, i.e., displaying all the products to the entire customer base, maximizes the platform revenue. Motivated by the unique setting of Airbnb, we consider a game theoretical setup in which each seller on the platform provides a single-unit product and competes with each other through price. We investigate sellers’ optimal pricing decisions given the platform’s assortment display policy. More importantly, we study if and how the platform should group each seller into different partitions, and how much traffic each partition should receive so as to maximize the revenue. We demonstrate that the platform should display the entire assortment to all the customers when the demand is sufficiently large. In addition, we provide a mixed-integer programming formulation to characterize the sellers’ as well as the platform’s optimal decisions. Meanwhile, we introduce two fairness definitions for the display policy, namely alpha-fairness and delta-fairness, to gauge how the requirements on the closeness of the attractiveness of each partition and the traffic allocated to each partition affect the total platform revenue. Finally, we extend the case where each seller supplies a distinct product with inventory size of one by considering scenarios in which each product has more than one unit.​

Bio: Hanwei is a final year Ph.D. candidate in Social and Engineering System from Institute of Data, System and Society (IDSS) at MIT. His research explores the combination of econometrics and optimization, in the field of empirical operations management, with applications in platform operations and revenue management. Prior to attending MIT, he received his bachelor’s degree in Engineering Systems from Singapore University of Technology and Design (SUTD).