In this article, we describe representative contributions in several major application areas of
data analytics in operations management to summarize the recent development, discuss the …

Contextual dynamic pricing aims to set personalized prices based on sequential interactions
with customers. At each time period, a customer who is interested in purchasing a product …

We study the classic model of joint pricing and inventory control with lost sales over T
consecutive review periods. The firm does not know the demand distribution a priori and …

Problem definition: This paper addresses the question whether or not self-learning
algorithms can learn to collude instead of compete against each other, without violating …

Transfer learning for contextual multi-armed bandits Page 1 The Annals of Statistics 2024,
Vol. 52, No. 1, 207–232 https://doi.org/10.1214/23-AOS2341 © Institute of Mathematical …

In feature-based dynamic pricing, a seller sets appropriate prices for a sequence of products
(described by feature vectors) on the fly by learning from the binary outcomes of previous …

We consider the periodic review dynamic pricing and inventory control problem with fixed
ordering cost. Demand is random and price dependent, and unsatisfied demand is …

In today's data-rich environment, context-based dynamic pricing has gained much attention.
To model the demand as a function of price and context, the existing literature either adopts …

In several e-commerce scenarios, pricing long-tail products effectively is a central task for
the companies, and there is broad agreement that Artificial Intelligence (AI) will play a …

Dynamic pricing is a fast-moving research area in machine learning and operations
management. A lot of work has been done for this problem with known noise. In this paper …