-
作者：Gupta, Diwakar; Mehrotra, Mili; Tang, Xiaoxu
作者单位：University of Texas System; University of Texas Austin; University of Illinois System; University of Illinois Urbana-Champaign; Wells Fargo Company
摘要：The Centers for Medicare and Medicaid Services (CMS) has introduced several Episode-based Payment Models. Episodes are combinations of pre-acute, acute, and post-acute services for particular medical conditions. During the year, CMS pays hospitals according to historical norms. At the end of the year, these payments are reconciled against a target price, resulting in either a gain or a loss for the hospital. The hospital may also realize gains or losses from its internal operations. It may inc...
-
作者：Xie, Yangyang; Xie, Lei; Lu, Meng; Yan, Houmin
作者单位：Chinese Academy of Sciences; University of Science & Technology of China, CAS; Shanghai University of Finance & Economics; City University of Hong Kong
摘要：In this study, as an alternative to the surplus utility, we propose a performance-price-ratio (PPR) utility and specialize the customer choice model with a PPR maximization criterion. With the PPR-based choice model, we investigate a pricing game between retailers in a competitive market. Through transferring the decision variable from price to performance-price ratio, the first-order condition of the game becomes a linear equation system, which enables us to develop a closed-form equilibrium ...
-
作者：Chen, Boxiao
作者单位：University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital
摘要：We consider an inventory control problem with lost-sales in a shifting demand environment. Over a planning horizon of T periods, demand distributions can change up to O( log T) times, but the firm does not know the demand distributions before or after each change, the time periods when changes occur, or the number of changes. Therefore, the firm needs to detect changes and learn the demand distributions only from historical sales data. We show that with censored demand, active exploration in t...
