My research focuses on new approaches to revenue management and dynamic pricing. In my job market paper, I study the intertemporal pricing policy and dynamic allocation problem in the market with limited data and demand information. The goal is to understand how firms should react to the market with the lack of demand information and how to design pricing mechanisms to adjust to customers’ forward-looking behavior in such environment.
My research goal is to expand the framework of revenue management. I have worked on the problems affecting many different market situations. In my current projects, I look at the industries with vertically differentiated products and the markets with changing environments. Besides the rational customer behavior, I also study the bounded rationality and explore the behavioral aspects in the customer decision-making process. My research lies on the interface of operations management, marketing and machine learning. I have adopted and applied interdisciplinary approaches to my research by combining robust optimization, game theory, mechanism design, optimal control and statistical learning.