报告题目：Translating empirical state-dependent service times into queueing models
报 告 人：丁李康
报告时间：2023年12月19日（星期二），10:00-11:30
报告地点：明哲楼504
主办单位：东北财经大学现代供应链管理研究院
【报告人简介】
Likang Ding is a PhD candidate in the Department of Accounting & Business Analytics at the Alberta School of Business, University of Alberta. He received his bachelor's degree in Operations Management from the University of Alberta. His research interests include queueing theory, customer behavior, sports analytics and healthcare operations.
【摘要】
Recent empirical studies suggest that service times in queueing settings are state-dependent due to human behaviors. Analytical studies on state-dependent queueing models assume that the parameters are given. We investigate the translation of empirical state-dependent service times into queueing model formulations. To this end, we identify two common model types from the literature, service time and service rate models, based on state dependency in service. We relate the two model types to different groups of mechanisms and show that they may be formulated from the same service times using data from published work. In addition, we show that translating service times into service rate models may result in invalid service rates, thus providing evidence against this model type and the mechanisms associated with it. For service rate models, we find that mean service times are in general not the inverse of service rates, the directional change in service rates is not always the opposite of the directional change in mean service times, and the state measurement timing may alter mean service time patterns. We provide closed-form solutions to convert service times into service rates and vice versa, and find conditions under which monotonic mean service times imply monotonic service rates and vice versa. Our results provide a guideline for researchers to select and formulate an appropriate state-dependent queueing model from service time data, and expand the scope of previously published managerial insights.
