Pricing is central to many industries and academic disciplines ranging from Operations Research to Computer Science and Economics. In the present paper, we study data-driven optimal pricing in low informational environments. We analyze the following fundamental problem: how should a...

We study the following fundamental data-driven pricing problem. How can/should a decision-maker price its product based on observations at a single historical price? The decision-maker optimizes over (potentially randomized) pricing policies to maximize the worst-case ratio of the revenue it can...

Auctions are widely used in practice. While also extensively studied in the literature, most of the developments rely on the significant common prior assumption. We study the design of optimal prior-independent selling mechanisms: buyers do not have any information about their competitors and...

Equipment manufacturers offer different types of maintenance service plans (MSPs) that delineate payment structures between equipment operators and maintenance service providers. These MSPs allocate risks differently and thus induce different kinds of incentives. A fundamental question,...

We study a firm's optimal pricing policy under price commitment. The firm's objective is to maximize its long-term average revenue given a steady arrival of strategic customers. In particular, customers arrive over time, are strategic in timing their purchases and are heterogeneous along two...