C all centers are an increasingly important part of today's business world, employing millions of agents across the globe and serving as a primary customer-facing channel for firms in many different industries. Call centers have been a fertile area for operations management researchers in several domains, including forecasting, capacity planning, queueing, and personnel scheduling. In addition, as telecommunications and information technology have advanced over the past several years, the operational challenges faced by call center managers have become more complicated. Issues associated with human resources management, sales, and marketing have also become increasingly relevant to call center operations and associated academic research.In this paper, we provide a survey of the recent literature on call center operations management. Along with traditional research areas, we pay special attention to new management challenges that have been caused by emerging technologies, to behavioral issues associated with both call center agents and customers, and to the interface between call center operations and sales and marketing. We identify a handful of broad themes for future investigation while also pointing out several very specific research opportunities.

International audienceIn 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 delay that has originally been announced to them. The balking and reneging from such a system are a function of the delay announcement. Modeling the call center as an M/M/s + M queue with endogenized customer reactions to announcements, we analytically characterize performance measures for this model. The analysis allows us to explore the role announcing different percentiles of the waiting time distribution, i.e., announcement coverage, plays on subsequent performance in terms of balking and reneging. Through a numerical study, we explore when informing customers about delays is beneficial and what the optimal coverage should be in these announcements. We show how managers of a call center with delay announcements can control the trade-off between balking and reneging through their choice of announcements to be made

This paper considers a call center outsourcing contract analysis and choice problem faced by a contractor and a service provider. The service provider receives an uncertain call volume over multiple periods and is considering outsourcing all or part of these calls to a contractor. Each call brings in a fixed revenue to the service provider. Answering calls requires having service capacity; thus implicit in the outsourcing decision is a capacity decision. Insufficient capacity implies that calls cannot be answered, which in turn means there will be a revenue loss. Faced with a choice between a volume-based and a capacity-based contract offered by a contractor that has pricing power, the service provider determines optimal capacity levels. The optimal price and capacity of the contractor together with the optimal capacity of the service provider determine optimal profits of each party under the two contracts being considered. This paper characterizes optimal capacity levels and partially characterizes optimal pricing decisions under each contract. The impact of demand variability and the economic parameters on contract choice are explored through numerical examples. It is shown that no contract type is universally preferred and that operating environments as well as cost-revenue structures have an important effect.call center, outsourcing, subcontracting, contract choice, capacity investment, pricing

W e model the decision-making process of callers in call centers as an optimal stopping problem. After each waiting period, a caller decides whether to abandon a call or continue to wait. The utility of a caller is modeled as a function of her waiting cost and reward for service. We use a random-coefficients model to capture the heterogeneity of the callers and estimate the cost and reward parameters of the callers using the data from individual calls made to an Israeli call center. We also conduct a series of counterfactual analyses that explore the effects of changes in service discipline on resulting waiting times and abandonment rates. Our analysis reveals that modeling endogenous caller behavior can be important when major changes (such as a change in service discipline) are implemented and that using a model with an exogenously specified abandonment distribution may be misleading.

This paper models a call center as a Markovian queue with multiple servers, where customer balking, impatience, and retrials are modeled explicitly. The resulting queue is analyzed both in a stationary and non-stationary setting. For the stationary setting a fluid approximation is proposed, which overcomes the computational burden of the continuous time markov chain analysis, and which is shown to provide an accurate representation of the system for large call centers with high system load. An insensitivity property of the retrial rate to key system parameters is established. The fluid approximation is shown to work equally well for the nonstationary setting with time varying arrival rates. Using the fluid approximation, the paper explores the retrial phenomenon for a real call center. The model is used to estimate the real arrival rates based on demand data where retrials cannot be distinguished from first time calls. This is a common problem encountered in call centers. Through numerical examples, it is shown that disregarding the retrial phenomenon in call centers can lead to huge distortions in subsequent forecasting and staffing analysis.

We 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. A Cox regression analysis reveals that in this call center, callers' abandonment behavior is affected by the announcement messages heard. To account for this, we formulate a structural estimation model of callers' (endogenous) abandonment decisions. In this model, callers are forward-looking utility maximizers and make their abandonment decisions by solving an optimal stopping problem. Each caller receives a reward from service and incurs a linear cost of waiting. The reward and per-period waiting cost constitute the structural parameters that we estimate from the data of callers' abandonment decisions as well as the announcement messages heard. The call center performance is modeled by a Markovian approximation. The main methodological contribution is the definition of an equilibrium in steady state as one where callers' expectation of their waiting time, which affects their (rational) abandonment behavior, matches their actual waiting time in the call center, and its characterization as the solution of a set of non-linear equations. A counterfactual analysis shows that callers react to longer delay announcements by abandoning earlier, that less patient callers as characterized by their reward and cost parameters react more to delay announcements, and that congestion in the call center at the time of the call affects caller reactions to delay announcements.

Cross-selling attempts, based on estimated purchase probabilities, are not guaranteed to succeed and such failed attempts may annoy customers. There is a general belief that crossselling may backfire if not implemented cautiously, however there is not a good understanding of the nature and impact of this negative reaction or appropriate policies to counter-balance it. This paper focuses on this issue and develops a modeling framework that makes use of a Markov decision model to account for negative customer reactions to failed sales attempts, and the effect of past contacts in managing cross-selling initiatives. Three models are analyzed, where purchase probabilities are affected from customer maturity or the number of failed attempts since the last purchase, or both. The analysis shows that customer reactions to cross-sell attempts make the purchase probabilities endogenous to the firm's cross-selling decisions; hence the optimal cross-selling policy becomes a function of customer state. The results highlight the role the cost of excessive cross-selling (direct as well as in the form of customer reactions) plays in optimal policies. Cross-sell data from a retail bank illustrates in what context the modeling framework can be applied and underlines the importance of customizing cross-sell policies to individual customers.

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 customers upon their arrival. For the simplest model without reneging, we give a method to estimate virtual delays that is used within the announcement step. For the second model, we first build the call center model incorporating reneging. The model takes into account the change in customer behavior that may occur when delay information is communicated to them. In particular, it is assumed that customer reneging is replaced by balking that depends on the state of the system in this case. We develop a method based on Markov chains in order to estimate virtual delays of new arrivals for this model. Finally, some practical issues concerning delay announcement are discussed.