The promised benefits of the Internet of Things (IoT) are predicated on the notion that better decisions will be enabled through a multitude of autonomous sensors (often deployed by different companies) providing real-time knowledge of the state of things. This knowledge will be imperfect, however,

Operational decision making in service systems often depends largely on the characterization of the random fluctuations involved. Exogenous arrivals represent a primary source of uncertainty and their stochastic behavior needs to be modeled carefully. In this talk, we will first argue that the

We derive a generalized likelihood ratio method to estimate any distribution sensitivity in a unified form. Then, the distribution sensitivities are used to in a gradient-based simulated maximum likelihood estimation (GSMLE) to estimate unknown parameters in a stochastic model without assuming that

News arrive randomly and the resulting sentiment, after quantification, behaves like a stochastic process. We propose a sentiment-driven stochastic volatility model to characterize the evolution of sentiment and its interplay with price and volatility process. Specifically, we propose a

Assortment rotation -- the retailing practice of changing the assortment of products offered to customers -- has recently been used as a competitive advantage for both brick-and-mortar and online retailers. We focus on product categories where consumers typically purchase multiple products during a

A prevalent yet little understood phenomenon of customer reward programs is the use of finite reward expiration term. We develop a theoretical framework to investigate the economic rationale behind this phenomenon, and the tradeoff between short and long expiration terms. In our model, a

Recently, there has been a rapid rise of on-demand ride-hailing platforms, such as Uber and Didi, which allow passengers with smartphones to submit trip requests and match them to drivers based on their locations and drivers' availability. With the rapid rise, there have been questions about how

Operational disruptions can impact a firm's risk, which manifests in a host of operational issues, including a higher holding cost for inventory, a higher financing cost for capacity expansion, and a higher perception of the firm's risk among its supply chain partners. While disruptions have been

Minimization with respect to a matrix X subject to orthogonality constraints X'X = I has wide applications in polynomial optimization, combinatorial optimization, eigenvalue problems, the total energy minimization in electronic structure calculation, sparse principal component analysis, community

We provide a theory that unifies the long tail and blockbuster phenomena. Specifically, we analyze a three-stage game where, first, a large number of potential firms make entry decisions, then those who stay in the market decide on the investment in its product, and lastly customers with