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13 JUN 2023 Seminar

The Whiplash Effect: Congestion Dissipation and Mitigation in a Circulatory Transportation System

Professor Ming Hu

Professor Ming Hu

The pandemic time witnessed a significant increase in port congestion, leading to shipping delays and rising costs for shippers. We build a fluid model to investigate how disruptions at one port can affect both the disrupted port and its counterpart in another country in a circulatory system where a stream of fleets transport goods back and forth between the two ports. Port disruption leads to two types of congestion: the inbound backlog, which occurs when ships are unable to enter the disrupted port, and the outbound backlog, which arises when goods are unable to be loaded onto ships for transport to other ports. We provide an analytical expression for the recovery time of the system of two ports (from when the disruption ends to when the system goes back to normal) and track the evolution of backlogs of goods and ships during the recovery process. We identify a whiplash effect in the outbound backlog level at both ports, which bears a resemblance to the commonly known “bullwhip effect”. Notably, the whiplash effect manifests in three primary features, namely oscillation, attenuation, and lag. Furthermore, we extend our analysis to a network of ports and show that the key findings and insights derived from the two-port model still hold in the multi-port bipartite system. This finding confirms that, despite its parsimony, the two-port system sufficiently captures the impact of port disruptions. We also extend the fluid model to a diffusion approximation model. Finally, we apply machine learning techniques to predict the time that vessels spend in the Shanghai port and show that our proposed model reduces prediction errors compared to the benchmark, demonstrating the potential and power of our model in helping to predict and mitigate the impact of disruptions in a circulatory transportation system, e.g., those in container shipping and air traveling industries.

Short Biography:
Ming Hu is the University of Toronto Distinguished Professor of Business Operations and Analytics, a professor of operations management at the Rotman School of Management, and an Amazon Scholar. He was named one of Poets & Quants Best 40 Under 40 business school professors in 2018. His research has been featured in mainstream media, such as the Financial Times. Most recently, his research has focused on operations management in the context of two-sided markets, sharing economy, social buying, crowdfunding, and crowdsourcing, with the goal of making full use of operational decisions to the benefit of society. He recently edited a Springer book titled Sharing Economy: Making Supply Meet Demand on operations management in the age of the sharing economy. He is the recipient of the Wickham Skinner Early-Career Research Accomplishments Award by the POM Society (2016) and the Best Operations Management Paper in Management Science Award by INFORMS (2017). He currently serves as the editor-in-chief of Naval Research Logistics, department editor of Service Science, associate editor of Operations Research, Management Science, and Manufacturing & Service Operations Management, and senior editor of Production and Operations Management. He is a former chair of the Revenue Management and Pricing (RMP) Section at the Institute for Operations Research and the Management Sciences. He received a master's degree in Applied Mathematics from Brown University in 2003 and a Ph.D. in Operations Research from Columbia University in 2009. For more details of his research, please visit



13 June 2023 (Tuesday)




Professor Ming Hu


HW 8-28

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