Over the last couple of years, Bitcoin cryptocurrency and the Blockchain technology that forms the basis of Bitcoin have witnessed an unprecedented attention. Designed to facilitate a secure distributed platform without central regulation, Blockchain is heralded as a novel paradigm that will be as powerful as Big Data, Cloud Computing, and Machine Learning. Blockchain continues to evolve, but its applications have already matured to rival, and already in some cases, replace more traditional institutions as avenues of global activity.

The Fama-French three factor models are commonly used in the description of asset returns in finance. Statistically speaking, the Fama-French three factor models imply that the return of an asset can be accounted for directly by the Fama-French three factors, i.e. market, size and value factor, through a linear function. A natural question is: would some kind of transformed Fama-French three factors work better? If so, what kind of transformation should be imposed on each factor in order to make the transformed three factors better account for asset returns?

Motivated by the news that Car2go in San Diego replaced all of its electric vehicle fleet with gasoline-powered cars starting in May 2016, we examine the questions of whether it is optimal to use EVs in the car sharing market and what is the environmental impact of the optimal choice on the car mix. We develop a model consisting of a profit-maximizing CSC and a population of utility-maximizing customers and show that it is optimal for the CSC to use EVs only if the charging speed is high enough and both the number of charging stations and the range of EVs are large enough.

Financial market inefficiencies do not affect all firms homogenously. Financially constrained firms have limited or no access to financial markets and rely more heavily on internal resources to finance their operations. We show that financially constrained firms hold relatively higher inventory and have lower inventory turnover. Using two distinct approaches, we suggest the link is causal. We first investigate the effect of the 2008 financial crisis on the inventory performance of financially constrained versus unconstrained firms.

Blockchain is a form of distributed ledger technology. While it has grown in prominence, its full potential and possible downsides are not fully understood yet, especially with respect to Operations Management (OM). This article fills this gap. After briefly reviewing the technical foundations, we explore multiple business and policy aspects. We identify five key strengths, the corresponding five main weaknesses, and three research themes of applying Blockchain technology to OM. The key strengths are (1) visibility, (2) aggregation, (3) validation, (4) automation, and (5) resiliency.

Network operations often suffer from chronic asset imbalance over time and across locations. This paper addresses the issue in the intermodal industry. The problem is mainly driven by myopic policies, environmental uncertainty, and network interdependence. To address the problem, we develop a unified framework that integrates two core operations: container repositioning and load acceptance. The central piece is the scarcity pricing scheme, which internalizes the externalities each acceptance imposes over time and across locations.

Department of Management Sciences hosted the 10th POMS-HK International Jan 5 to 6, 2019. The conference, themed with “Operations Excellence for a Better World” welcomed over 400 participants from over 14 countries and regions, a record high for this annual event. Prof. Way Kuo, President of City University of Hong Kong, and Prof. George Shanthikumar, Immediate Past President of Production and Operations Management Society, delivered the welcome speech and opening remarks. The conference was featured with three fabulous keynote speeches by Prof. Jonh Birge, Prof Max Shen and Prof.

In the ranking-and-selection field, many current existing fully sequential procedures are developed under the indifference-zone (IZ) formulation which assumes an optimality gap between the best alternative and the others. In this paper, by modifying one classical fully sequential procedure, Paulson’s procedure, we devise a new type of fully sequential procedure which can provide the probably approximately correct (PAC) selection guarantee.

In 1992, FDA instituted the accelerated approval pathway (AP) to allow promising drugs to enter the market based on limited evidence, but requiring manufacturers to verify the drugs’ true clinical benefits through post-market studies. However, most post-market studies are not completed due to many incentive issues, and FDA must endure an onerous process to withdraw an unproven drug from the market when a post-market study is uncompleted.

Optimal routing solutions in deterministic models usually fail to deliver promised on-time services in the real world of uncertainty, causing potential loss of customers and revenue. In this study, we propose a new formulation for the data-driven Vehicle Routing Problem with Time Windows (VRPTW) under uncertain travel times that is compatible with the paradigm of distributionally robust optimization.