Efficient Queueing via Partial Bayesian Persuasion: Nudging Just Enough Customers Amid
Prof. GUO Pengfei
Chair Professor of Supply Chain Management, Department of Decision Analytics and Operations, City University of Hong Kong
Date: 11 April 2025 (Friday)
Time: 10:30 – 12:00
Venue: E22-2010
Host: Prof. Zhaotong LIAN, Professor in Business Intelligence and Analytics
Abstract
We study the information design problem for a service provider whose service quality fluctuates between high and low levels, and only a portion of customers receive information about its service quality. This is common in digital marketing, where platforms send advertisements to a portion of customers. We model this as a Bayesian persuasion problem, where the service provider sends a binary quality signal to a portion of customers based on a committed information strategy after the service quality level is realized. Customers then update their beliefs using Bayes’ rule and decide whether or not to queue. We analyze two cases: one in which the persuasion coverage level is fixed, and the other in which it is a decision variable. We derive the optimal information design strategies for both profit maximization and welfare maximization. When the persuasion coverage level is fixed, the profit-maximizing provider often adopts a partial discloser strategy: sending a positive signal when service quality is high and randomizing between positive and negative signals otherwise. By contrast, the welfare-maximizing provider’s information strategy depends on market size: full disclosure in small-sized markets, where each signal fully reveals the service quality; partial disclosure in negative signal otherwise; and non-disclosure in large-sized markets, in which it sends the same signal regardless of the realized quality level. When the persuasion coverage level is a decision variable, we show that irrespective of the provider’s objective, partial persuasion always outperforms full persuasion when the market size is sufficiently large
Speaker
Professor Pengfei Guo is Chair Professor of Supply Chain Management of City University of Hong Kong. Prior to joining CityU, he was a faculty member at the Department of Logistics and Maritime Studies, Faculty of Business, the Hong Kong Polytechnic University. He received his PhD in Business Administration from Duke University. Before that, he obtained his BS from Xi’an Jiaotong University and MS degree from Shanghai Jiao Tong University. His research work has been published in the leading academic journals such as Management Science, Operations Research, Manufacturing & Service Operations Management, Production and Operations Management, etc. Prof. Guo has broad research interests, including service operations, queuing economics, healthcare policy, and supply chain management. He is an Associate Editor of Manufacturing & Service Operations Management and a Senior Editor of Production and Operations Management. He also served as the president of the POMS – Hong Kong Chapter during 2022-2024.
All are welcome!
