We study a model of behavior-based price discrimination where firms can agree to share customer information that can be used for personalized pricing. We show that firms are better off sharing customer information as it softens up-front competition when they gather information, consumers are...

Platforms often use fee discrimination within their marketplace (e.g., Amazon, eBay, and Uber specify a variety of merchant fees). To better understand the impact of marketplace fee discrimination, we develop a model that allows us to determine equilibrium fee and category decisions that depend...

We develop a model for two-sided markets with consumers and producers, who interact through a platform. Typical settings for the model are the market for smartphones with phone users, app producers, and smartphone operating systems; or the video game market with game players, video game...

The phenomenon where a network's value escalates with each additional user, known as a direct network effect, exists across industries that may differ in terms of interoperability or compatibility. For instance, while email and telephone services benefit from seamless cross-network...

Fee discrimination is commonly used by marketplace platforms (e.g., Amazon, eBay, and Uber). To better understand how marketplace fee discrimination interacts with the hybrid platform business model, we model a marketplace platform that manages fees and categories across a continuum of retail...

In two-sided markets a platform allows consumers and sellers to interact by creating sub-markets within the platform marketplace. For example, Amazon has sub-markets for all of the different product categories available on its site, and smartphones have sub-markets for different types of...

We consider two-sided markets in which consumers and firms endogenously determine whether they single-home (patronize only one platform), or multi-home (join competing platforms). We find that the standard competitive bottleneck allocation in which all consumers single-home and all firms...