In an online retail setting, we study the interplay between social learning-induced network effects and product proliferation-induced substitution effects within a product category in which customer-generated online reviews are available. We show that, when product launches are asynchronous,...

We develop a distribution-free model to evaluate the performance of process flexibility structures when only the mean and partial expectation of the demand are known. We characterize the worst-case demand distribution under general concave objective functions, and applying it to derive tight...

We report on a survey of global manufacturing sourcing decisions that were made by multi-national companies operating in China. Based on responses from Chinese managers, the survey explored explicit sourcing and technology company decisions. The analysis provided insights into what these firms...

We study the classical multi-period capacitated stochastic inventory control problems in a data-driven setting. Instead of assuming full knowledge of the demand distributions, we assume that the demand distributions can only be accessed through drawing random samples. Such data-driven models are...

We study a hybrid strategy that uses both process flexibility and finished goods inventory for supply chain risk mitigation. The interplay between process flexibility and inventory is modeled as a two-stage robust optimization problem. In the first stage, the firm allocates inventory before...

Motivated by applications in inventory control and real-time bidding, we consider un-discounted reinforcement learning (RL) in Markov decision processes (MDPs) under temporal drifts. In this setting, both the reward and state transition distributions are allowed to evolve over time, as long as...

We consider an online assortment optimization problem where we have n substitutable products with fixed reusable capacities c1,...,cn. In each period t, a user with some preferences (potentially adversarially chosen) arrives to the seller's platform who offers a subset of products St, from the...

The prevalence of e-commerce has made detailed customers’ personal information readily accessible to retailers, and this information has been widely used in pricing decisions. When involving personalized information, how to protect the privacy of such information becomes a critical issue in...

Motivated by our collaboration with Anheuser-Busch InBev (AB InBev), a consumer packaged goods (CPG) company, we consider the problem of forecasting sales under the coronavirus disease 2019 (COVID-19) pandemic. Our approach combines non-parametric regression, game theory, and pandemic modeling...

We propose a new approach for the vehicle routing problem with stochastic customer demands revealed before vehicles are dispatched. We combine ideas from vehicle routing and manufacturing process flexibility to propose overlapped routing strategies with customer sharing. We characterize the...