Dongyuan Zhan is a Professor at School of Management, University of Science and Technology of China. He worked as an Assistant and Associate Professor at UCL School of Management. He studies service operations, platform design with an emphasis on strategic behavior of servers or agents whose payoff may include behavioral concerns. His papers have won the Second Place of CSAMSE Best Paper Award, and won twice NET Institute Summer Research Grants. He is Associate Editor of Decision Sciences Journal, and on the Editorial Review Board of POMS. He holds a Ph.D. degree from University of Southern California, and an MS and a BS degree from Tsinghua University.<\/p>\n"}],"event_agenda":false,"event_photo_gallery":false,"event_presentations":false,"event_custom_heading":[{"event_custom_title":"Abstract","event_custom_details":"
Motivated by omnichannel service systems in which online customers can place orders remotely while walk-in customers must queue on site, we study a two-stage tandem queue with a cashier queue followed by an order-processing queue. Walk-in customers enter the first queue before proceeding to the second, whereas online customers bypass the first queue and join the second queue directly. Customers strategically decide whether to join upon arrival and, after joining, whether to abandon while waiting. Because online customers can overtake walk-in customers waiting in the cashier queue, the model generates overtaking-induced abandonment incentives that are absent from standard tandem-queue settings.<\/p>\n
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In the base model, online customers do not observe the order-processing queue, and we compare two information structures depending on whether walk-in customers observe that queue through an in-store dashboard. In the dashboard scenario, we show that walk-in customers follow a two-dimensional threshold strategy and may abandon while waiting in the cashier queue. In the no-dashboard scenario, we prove that walk-in customers never abandon after joining and that their equilibrium joining behavior has a threshold structure. For online customers, equilibrium existence in the dashboard scenario is nonstandard because their expected utility may be discontinuous in the joining probability; we establish existence using a quasi-increasing fixed-point argument. Building on these equilibrium characterizations, we study how online adoption level affects system performance. We show that both throughput and social welfare can decrease as online adoption level increases, implying that service providers should not blindly promote online ordering. We further compare the two information structures and show that a revenue-maximizing provider should conceal the order-processing queue length when the online adoption level is low and disclose it otherwise, whereas a social planner prefers concealment only for an intermediate range of online shares. Notably, there exists an intermediate region where many omnichannel brands currently operate, in which disclosure improves both throughput and social welfare. We also show that these insights remain robust when online customers observe the order-processing queue.<\/p>\n"}],"event_enquiry_details":{"event_enq_full_name":"","event_enq_department":"","event_enq_email":"","event_enq_telephone":"","event_enq_website":""}}]