We study the problem of learning shared structure across a sequence of dynamic pricing experiments for related products. We consider a practical formulation where the unknown demand parameters for each product come from an unknown distribution (prior) that is shared across products. We then...

We consider a firm that sells a product over T periods without knowing the demand function. The firm sequentially sets prices to earn revenue and to learn the underlying demand function simultaneously. In practice, this problem is commonly solved via greedy iterative least squares (GILS). At...

In this paper we study the implications of service level guarantees (SLGs) in a model of oligopoly competition where providers compete to deliver a service to congestion-sensitive consumers. The SLG is a contractual obligation on the part of the service provider: regardless of how many customers...

We study optimal pricing strategies for ride-sharing platforms, such as Lyft, Sidecar, and Uber. Analysis of pricing in such settings is complex: On one hand these platforms are two-sided -- this requires economic models that capture the incentives of both drivers and passengers. On the other...

When a new product or technology is introduced, potential consumers can learn its quality by trying the product, at a risk, or by letting others try it and free-riding on the information that they generate. We propose a dynamic game to study the adoption of technologies of uncertain value, when...

Online platforms collect rich information about participants and then share some of this information back with them to improve market outcomes. In this paper we study the following information disclosure problem in two-sided markets: If a platform wants to maximize revenue, which sellers should...