Previous Seminar

Understanding Demand Uncertainty

By Prof. Jeff HONG

Department of Economics & Finance / Management Sciences
City University of Hong Kong

Date
15 June 2017 (Finished)
Time
12:30pm-2:00pm
Venue
Room 8-210, 8/F, Lau Ming Wai Aademic Building (AC3), City University of Hong Kong
Language
English
 

Abstract
Poisson processes are often used to model arrival (demand) processes in many business and engineering fields. In this talk, I will show you the results from a sequence of studies that we have done trying to understand the uncertainty behaviors in demand processes. The examples include phone calls to call centers, chats to online chatting groups, confirmed cases of infectious diseases, arrivals to hospitals, appointments to a network of clinics, sales of soft drinks, trading volume of stocks, etc. The results basically show that Poisson processes tend to under-estimate the uncertainty in the demands. Moreover, the uncertainty follows a clear scaling relationship between the mean and the standard deviation in both temporal and spatial dimensions. I will connect our findings to what is known as Taylor's scaling law in the areas of biology and physics, and what is known as allometric scaling in biology and sociology. I will then introduce a space-filling fractal network model that we developed in explaining the observed phenomenon, but will also discuss the limitations of the model.

Biography
Professor Jeff Hong received his PhD in Industrial Engineering and Management Sciences from Northwestern University in 2004, MSc in Applied Mathematics from the University of Cincinnati in 2001, and BEng in Automative Engineering and BEng in Industrial Engineering from Tsinghua University in 1999. Prior to joining the City University of Hong Kong, he was Professor, Associate Director of Logistics and Supply Chain Management Institute, and Director of Financial Engineering Laboratory in Department of Industrial Engineering and Logistics Management at the Hong Kong University of Science and Technology. Professor Hong’s research interests include management sciences, operations research, financial engineering and risk management, and business analytics. He published extensively on leading academic journals such as Operations Researchand Management Science. He was the winner of the 2009 Operations Best Paper Award from the Institute of Industrial Engineers, the 2012 Outstanding Simulation Publication Award from the INFORMS Simulation Society, and the inaugural Outstanding Research Award from the Operational Research Society of China in 2014. He is currently an Associate Editor of Operations Research, Naval Research Logistics and ACM Transactions on Modeling and Computer Simulation.

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