Motivated by online labor markets, we consider the online assortment optimization problem faced by a two-sided matching platform that hosts a set of suppliers waiting to match with a customer. Arriving customers are shown an assortment of suppliers, and may choose to issue a match request to one...

Motivated by ride-hailing marketplaces, we present a model of two-sided matching platforms that participate in a duopoly market with spatial frictions. Both platforms face disjoint streams of service requests, but they share the same resources on the supply side, i.e., suppliers multi-home. Due...

An important operational decision for online service platforms is how much control they have over pricing decisions. Motivated by recent regulations and increased public scrutiny on platform control, we study the effects of decentralized pricing using a fluid model of dynamic two-sided matching....

We introduce the click-based MNL choice model, a novel framework for capturing customer purchasing decisions in e-commerce settings. We augment the classical Multinomial Logit choice model with the assumption that customers only consider the items they have clicked on before they proceed to...

We study the dynamic assortment planning problem under the widely-utilized Multinomial Logit choice model (MNL). In this single-period assortment optimization and inventory management problem, the retailer jointly decides on an assortment, i.e., a subset of products to be offered, as well as on...