Recently, a collaborative research study titled "Information Freshness in Service Queues With Strategic Customers" by Xu Jin , a faculty member from the Department of Supply Chain Management and Systems Engineering at the School of Management, Huazhong University of Science and Technology along with Professor Duan Lingjie from the Singapore University of Technology and Design, Professor Shou Biying from The Chinese University of Hong Kong , Shenzhen, and Professor Huang Jianwei from The Chinese University of Hong Kong, Shenzhen, was published in Production and Operations Management, a leading international journal in the field of management.
This paper aims to examine a scenario in which a service provider updates its queue length information to customers at a specific frequency. Customers decide whether to join the queue based on the most recent update. The objective is to determine the optimal updating frequency that benefits both the service provider and customers. Using a two-dimensional continuous-time Markov process, The study models the actual and announced queue length processes. By proving the identical distributions of these two processes under a Poisson updating scheme, the study derives closed-form solutions for customers utility functions. The findings demonstrate that customers adopt a generalized mixed-threshold strategy at equilibrium, and their certainty about whether to join the queue or balk does not always increase with fresher information. Furthermore, we reveal that due to customers different sensitivities to information freshness, system performance metrics such as throughput and total customer utility exhibit non-monotonic behavior in response to the updating frequency. Consequently, providing fresher information does not necessarily lead to improved system performance. To address this, the study proposes algorithms to determine the optimal updating frequency for each system performance metric and identify the conditions under which different updating frequencies are optimal. It demonstrates that any positive updating frequency can achieve customer utility no worse than the no-information system. Additionally, in systems with high customer arrival rates, updating with a positive updating frequency can improve throughput. Furthermore, the study proves conditions under which a positive and finite updating frequency can yield higher throughput and total customer utility compared to real-time information systems.
Xu Jin is a Lecturer in the Department of Supply Chain Management and Systems Engineering at the School of Management, Huazhong University of Science and Technology. His primary research interests include queuing systems, stochastic processes, and intelligent planning & scheduling. He has led multiple research projects, including: the National Natural Science Foundation of China (NSFC), Youth Program, Hubei Provincial Natural Science Foundation, General Program and the China postdoctoral science foundation general program.
Full text can be retrieved from:
https://journals.sagepub.com/doi/abs/10.1177/10591478241281913
