文摘
This thesis studies callers abandonment behavior in call centers. I propose a new method to estimate callers delay sensitivity from the data,and show how we can use this information to predict the impact of changes in the priority policy of a call center or the delay information conveyed to callers. In the first chapter,I model callers decision making process in call centers as an optimal stopping problem. The utility of a caller is modeled as a function of her waiting cost and reward for service. I estimate the cost and reward parameters of the callers using the data of individual calls made to an Israeli call center. I also conduct a series of counterfactual analyses that explore the effects of changes in service discipline on resulting waiting times and abandonment rates. In the second chapter,I undertake an empirical study of the impact of delay announcements on callers abandonment behavior and the performance of a call center with two priority classes. Given callers parameters estimated from the data,I predict callers behavior in settings with announcement patterns different from that in the data,and analyze the impact on the system performance. Using a Markovian approximation to simplify the queueing analysis,I develop a methodological framework to find the steady-state equilibrium by combining the estimation of callers reward and cost parameters,the model of callers abandonment behavior,and the queuing analysis that incorporates this behavior. The third chapter describes how the Stochastic Kriging approach can be used to find the impact of delay announcements in multi-class call centers. I use this approach to derive the waiting time distributions and the steady state probabilities as functions of the abandonment time distributions. This derivation was done in Chapter 2 using a Markovian approximation. However,the Markovian approximation presented in Chapter 2 is sensitive to the priority policy of that particular two-class call center. In addition,developing the same approximation for multi-class class call centers is cumbersome. In contrast,the Stochastic Kriging approach can be used to study call centers with any priority policy and a larger number of classes.
