In this paper we develop an approach to dynamic pricing that combines ideas from data-driven and robust optimization to address the uncertain and dynamic aspects of the problem. In our setting, a firm offers multiple products to be sold over a fixed discrete time horizon. Each product sold...

We develop a framework for estimating price sensitivity in applications such as ticket reselling. This framework allows us to estimate heterogeneous price sensitivity that we subsequently embed in a price optimization model for ticket reselling. Due to the heterogeneous nature of tickets, the...

How should a firm price a new product for which little is known about demand? We propose a simple pricing rule: the firm only estimates the maximum price it can charge and still expect to sell at least some units, and then sets price as though the actual demand curve were linear. We show that if...

We consider the dynamic pricing problem of a retailer who does not have any information on the underlying demand for a product. The retailer aims to maximize cumulative revenue collected over a finite time horizon by balancing two objectives: \textit{learning} demand and \textit{maximizing}...

Problem Definition: Consumers often perceive higher-priced products to have higher quality. Less is known on how quality perception is affected by price markdowns. In addition, it is an open question whether and how consumers' ex-ante expectation on a future markdown affects their quality...