The Value of Dynamic Pricing in Large Queueing Systems
成果类型:
Article
署名作者:
Kim, Jeunghyun; Randhawa, Ramandeep S.
署名单位:
University of Southern California
刊物名称:
OPERATIONS RESEARCH
ISSN/ISSBN:
0030-364X
DOI:
10.1287/opre.2017.1668
发表日期:
2018
页码:
409-425
关键词:
lead-time quotation
revenue management
network
size
摘要:
We study the value of dynamic pricing to maximize revenues in queueing systems with price-and delay-sensitive customers. The system queue length is visible so that upon arrival, customers decide to join the system based on the congestion and the price at that time. We analyze this problem in the asymptotic regime of large customer market size and capacity. We find that dynamic pricing performs significantly better than static pricing at mitigating the effect of uncertainty. Asymptotically, the revenue in such systems consists of a positive deterministic component and a negative stochastic component, the latter representing the impact of variability. Static pricing leads to the n(1/2)-scale effect of variability, i.e., the expected steady-state queue length is Kn(1/2) for some K > 0, where n represents the system size. However, dynamic pricing can lower this effect of variability to the n(1/3)-scale. We further show that a simple policy of using only two prices can achieve most of the benefits of dynamic pricing. We also discuss how our results can apply to other dynamic control problems in queueing systems.