We consider the problem of a firm seeking to use personalized pricing to sell an exogenously given stock of a product over a finite selling horizon to different consumer types. We assume that the type of an arriving consumer can be observed but the demand function associated with each type is...

Personalized pricing analytics is becoming an essential tool in retailing. Upon observing the personalized information of each arriving customer, the firm needs to set a price accordingly based on the covariates such as income, education background, past purchasing history to extract more...

Dynamic pricing is designed to increase revenues or profits of the firm by adjusting prices in response to changes in the marginal value of capacity as described in Gallego and van Ryzin (1994). While thousands of papers have been written about dynamic pricing, this is to our knowledge the first...

Customer arrival patterns observed in the real world typically exhibit strong seasonal effects. It is therefore natural to ask: Can a nonhomogeneous Poisson process (NHPP) with a rate function that is the simple sum of sinusoids provide an adequate description of reality? If so, how can the...

Money back guarantees (MBGs), which allow customers to return products that do not meet their expectations, are widely used in the retail industry. In this paper, we study a retailer's MBG policy with dynamic pricing of a limited inventory. A key decision for the retailer is to decide whether to...

We analyze a firm's optimal pricing of a new service when consumers interact in a network and impose positive externality on one another. The firm initially provides its service for free, leveraging network externality to promote rapid service consumption growth. The firm raises the price and...