Many service systems provide customers with information about the system so that customers can make an informed decision about whether to join or not. Many of these systems provide information in the form of an update. Thus, the information about the system is updated periodically in increments of size $\Delta$. It is known that these updates can cause oscillations in the resulting dynamics. However, it is an open problem to explicitly characterize the size of these oscillations when they occur. In this paper, we solve this open problem and show how to exactly calculate the amplitude of these oscillations via a fixed point equation. We also calculate closed form approximations via Taylor expansions of the fixed point equation and show that these approximations are very accurate, especially when $\Delta$ is large. Our analysis provides new insight for systems that use updates as a way of disseminating information to customers.
翻译:许多服务系统向客户提供有关系统的信息,使客户能够就是否加入系统作出知情的决定。许多这些系统以更新的形式提供信息。因此,关于系统的信息定期更新,以美元为单位递增。众所周知,这些更新可能会导致由此产生的动态变化。然而,当这些波动发生时,明确描述这些波动的大小是一个公开的问题。在本文中,我们解决了这一未解决的问题,并展示了如何通过固定点方程式准确计算这些振荡的振幅。我们还通过泰勒扩大固定点方程式计算封闭式近似值,并显示这些近似非常准确,特别是在美元为大的情况下。我们的分析为使用更新作为向客户传播信息的一种方式的系统提供了新的洞察力。