In this paper, we analyze a call center with impatient customers. We study how informing customers about their anticipated delays affects performance. Customers react by balking upon hearing the delay announcement and may subsequently renege, particularly if the realized waiting time exceeds the...

We consider ordinary and conditional first passage times in a general birth–death process. Under existence conditions, we derive closed-form expressions for the kth order moment of the defined random variables, k ≥ 1. We also give an explicit condition for a birth–death process to be...

We consider ordinary and conditional first passage times in a general birth–death process. Under existence conditions, we derive closed-form expressions for the kth order moment of the defined random variables, k ≥ 1. We also give an explicit condition for a birth–death process to be...

In this paper, we consider two basic multi-class call center models, with and without reneging. Customer classes have different priorities. The content of different types of calls is assumed to be similar allowing their service times to be identical. We study the problem of announcing delays to...

We investigate the benefits of migrating from a call center, where all agents are pooled and customers are treated indifferently by any agent, toward a call center where customers are grouped into clusters with dedicated teams of agents. Each cluster is referred to as a portfolio. Customers of...

We consider a call center with two classes of impatient customers: premium and regular classes. Modeling our call center as a multiclass GI/GI/s+M queue, we focus on developing scheduling policies that satisfy a target ratio constraint on the abandonment probabilities of premium customers to...

We focus on architectures with limited flexibility for multi-skill call centers. The context is that of call centers with asymmetric parameters: unbalanced workload, different service requirements, a predominant customer type, unbalanced abandonments and high costs of cross-training. The most...