We consider a dynamic pricing problem where the firm tries to maximize the profit upon selling a product over the course of T periods. We do not assume decision maker’s foreknowledge on the demand. Traditionally, the cost is fixed and the problem may be formulated as a multi armed bandit problem,

In this paper, we study the dynamic pricing and availability decisions of a firm that repeatedly introduces new generations of a product over time. Customers are strategic and are affected by two types of scarcity effects----direct scarcity effect and relative scarcity effect. Firm-induced scarcity

Over the past few decades, global metapopulation epidemic simulations built with worldwide air-transportation data have been the main tool for studying how epidemics spread from the origin to other parts of the world (e.g. for pandemic influenza, SARS and Ebola). However, it remains unclear how

This work is motivated by the appointment booking of specialist services at the ambulatory care center (ACC) in a major public hospital in Hong Kong. We study scheduling policies in a healthcare system in which patients' waiting times for medical consultations are governed by the Hong Kong Hospital

We consider the problem of allocating daily hospital service capacity among several types of elective surgical procedures. Our focus is on the interaction between two major constraining hospital resources: operating room and recovery bed capacity. In our model, each type of surgical procedure has

We study stochastic optimization problems with decisions truncated by random variables. The technical difficulty is that the optimization problems may not be convex programs due to the truncation. We develop a transformation technique to convert the original non-convex problems to equivalent convex

Opponents of pollution regulation claim that regulations choke businesses, hurt welfare and destroy economic growth. Do pollution regulations in fact hurt producers and the economy? To address this question, we develop an integrated production-pollution-abatement model, and study two popular

Using network survey and objective productivity data collected from the Esquel Group, a large textile company headquartered in Hong Kong, we find that the density of worker social connections within a production line positively and quadratically affects the line-average productivity. However, we

This paper provides an examination of the notion of “distance” and ordering between the whole distributions of earnings for men and women, and some related counterfactuals.We investigate aggregative measures and their statistical implementation and evaluation. We provide a synthesis of the decision

Deep learning is a form of machine learning for nonlinear high dimensional pattern matching and prediction. By taking a Bayesian probabilistic perspective, we provide a number of advantages, with more efficient algorithms for optimization and hyper-parameter tuning, and an explanation of predictive