Managing Service Systems with Overconfident Customers
研究了顾客对服务时间变异性低估（过度自信）时，服务系统的最优定价和队列长度信息提供策略，发现经典结论在不可观察队列中失效，且管理者应根据拥堵程度决定是否公开队列信息。
Problem definition: Extensive evidence shows that customers tend to underestimate the variability of service times. The theoretical foundation lies in overconfidence theory, which asserts that decision makers tend to make overly optimistic forecasts about uncertain events. We study how to decide optimal pricing and queue-length information provision policies to manage a service system where customers are overconfident in their beliefs about service times—customers underestimate the variability of service times. Methodology/results: We formulate the problem as a queueing-game-theoretic model to examine the implications of overconfidence. Our models and results generalize those in seminal queueing-economics papers. First, the classical equivalence result breaks down in an unobservable queue: the revenue-maximizing price is strictly higher than the welfare-maximizing price, and consumer surplus is always negative. However, in an observable queue, consumer surplus is always negative for sufficiently low and sufficiently high congestion, but it can be positive or negative for intermediate congestion depending on system features. Second, the revenue-maximizing price is always higher than in the classical model in an unobservable queue, whereas it can be higher or lower in an observable queue. Third, the manager should always reveal queue-length information to improve revenue for both sufficiently low and sufficiently high congestion but strategically decide for intermediate congestion. Finally, customers will not renege in both unobservable and observable queues, owing to the increasing failure rate of perceived service times. Managerial implications: This paper unravels the role of customer overconfidence in service systems and its important implications on the manager’s pricing decision and queue-length information provision policy as well as consumer surplus. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.0191 .