Commercial AI solutions provide analysts and managers with data-driven business intelligence for a wide range of decisions, such as demand forecasting and pricing. However, human analysts may have their own insights and experiences about the decision-making that is at odds with the algorithmic...

We study the problem when a firm sets prices for products based on the transaction data, i.e., which product past customers chose from an assortment and what were the historical prices that they observed. Our approach does not impose a model on the distribution of the customers’ valuations and...

Thanks to the abundant user-generated content on the review websites, customers can easily make a casual inference on the service speed through observing and learning from others' service experiences. We study a service system where customers make their join-or-balk decisions based on a sample...

We apply Multi-Agent Deep Reinforcement Learning (MADRL) to inventory management problems with multiple echelons and evaluate MADRL's performance to minimize the overall costs of a supply chain. We also examine whether the upfront-only information-sharing mechanism used in MADRL helps alleviate...

To address financial shortage for public service provision, a government may delegate service provision to a private firm subject to regulation in service price or wait time, or jointly finance, own, and run a service system with the firm. However, the conflict between the government's and...

We study the problem of inequitable access to public restrooms by women and the LGBTQ community. Individuals choose to enter a restroom based on their gender identity and the expected or observed wait time. We analytically show the benefits of having unisex restrooms from three angles: (1)...