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}...

We introduce a new distributionally robust optimization model to address a two-period, multi-item joint pricing and production problem, which can be implemented in a data-driven setting using historical demand and side information pertinent to the prediction of demands. Starting from an additive...

Problem definition: We study personalized product recommendations on platforms when customers have unknown preferences. Importantly, customers may disengage when offered poor recommendations.Academic / Practical Relevance: Online platforms often personalize product recommendations using bandit...

This chapter presents some recent developments in retail promotions. We first discuss the different types of promotion used in retail, and then survey the related literature. We next formulate the promotion optimization problem for multiple items. This formulation is directly motivated from...

Promotions are a critical decision for supermarket managers who must decide the price promotions for a large number of items. Retailers often use promotions to boost the sales of the different items by leveraging the cross-item effects. We formulate the promotion optimization problem for...

We study a multi-period, multi-item dynamic pricing problem faced by a retailer. The objective is to maximize the total profit by choosing prices, while satisfying several business rules. The strength of our work lies in our graphical model reformulation, which allows us to use ideas from...

We study a common agency model with informed principals consisting of two capacity-constrained suppliers and a single retailer. The capacity of each supplier is her private information. Conditioned on their capacities, the suppliers simultaneously and non-cooperatively offer quantity-price...

Revenue management models traditionally assume that future demand is unknown but can be described by a stochastic process or a probability distribution. Demand is, however, often difficult to characterize, especially in new or nonstationary markets. In this paper, we develop robust formulations...

One of the greatest challenges of the COVID-19 pandemic has been the way evolving regulation, information and sentiment has driven waves of the disease. Traditional epidemiology models, such as the SIR model, are not equipped to handle these behavioral based changes. We propose a novel multipeak...