Stochastic Models for the Design and Management of Customer Contact Centers

联络中心是一个资源的集合，提供服务提供商与其客户之间的接口。经典的联络中心是一个呼叫中心，包含一组通过电话与客户交谈的服务代表（Rep）。在呼叫中心，服务代表由相当复杂的信息和通信技术（ICT）设备支持，例如专用分支交换机（PBX）、交互式语音应答（IVR）单元、自动呼叫分配器（ACD）、个人计算机（PC）和各种数据库。随着电子商务的迅速发展，服务提供商与其客户之间的联系往往是通过电子邮件或互联网而不是通过电话进行的。 联络中心的设计和管理是重要的，值得研究，因为联络中心包括一个大的，不断增长的经济部分，因为他们是相当复杂的。经典的呼叫中心是复杂的，因为通常有许多类型的呼叫，需要不同的服务技能，如不同的语言知识和不同的特殊促销知识。ACD能够通过基于技能的路由作出反应，但仍有机会确定更好的路由算法和更有效的人员配置方法。这些困难主要是由于不能确定将来是否会收到各种服务要求，以及回应这些要求所需的时间和资源，由于与客户的联系不再需要通过电话，因此有必要考虑其他媒体。当服务代表执行几种不同类型的工作时，需要将工作分配给不同的任务，如果某些工作可以推迟，则可以提高效率。多媒体也会带来更复杂的接触体验。 例如，客户可能会在与服务代表交互的时间段和在互联网上浏览的时间段之间交替。 本项目旨在通过对联络中心的随机（概率）模型进行探索性研究来应对这些挑战，旨在揭示基本原理并开发性能分析工具，从而改善联络中心的设计和管理。将努力寻找联络中心资源共享的条件，在这种情况下，大型单一技能中心的效率可以在多技能中心以最小的灵活性实现。将在实时、短期和长期这三个重要时间尺度中的每一个尺度上研究人员配置问题。将努力了解不同来源的不确定性的影响：模型不确定性、参数不确定性和过程不确定性。

A contact center is a collection of resources providing an interface between a service provider and its customers. The classical contact center is a call center, containing a collection of service representatives (reps) who talk to customers over the telephone. In a call center, the service reps are supported by quite elaborate information-and-communication-technology (ICT) equipment, such as a private branch exchange (PBX), an interactive voice response (IVR) unit, an automatic call distributor (ACD), a personal computer (PC) and assorted databases. With the rapid growth of e-commerce, contact between the service provider and its customers is often made via e-mail or the Internet instead of by telephone. The design and management of contact centers is important, and worthy of research, because contact centers comprise a large, growing part of the economy and because they are quite complicated. Classic call centers are complicated because there are often many types of calls, requiring different service skills, such as knowledge of different languages and knowledge of different special promotions. The ACD is able to respond through skill-based routing, but there remains an opportunity to determine better routing algorithms and more effective methods for staffing. The difficulties are largely due to uncertainty about future arrivals of service requests of various kinds and the time and resources that will be required to respond to those requests.Given that contact with customers no longer need be by telephone, it is necessary to consider the other media. When service reps perform several different kinds of work, there is a need to allocate effort to the different tasks, which presents opportunities for improved efficiency if some of the work can be postponed. Multimedia also lead to more complicated contact experiences. For example, customers might alternate between periods of interaction with service reps and periods of browsing on the Internet. This project aims to respond to these challenges by conducting exploratory research on stochastic (probability) models of contact centers, aiming to uncover fundamental principles and develop performance-analysis tools that will make it possible to improve the design and management of contact centers. Effort will be made to find conditions for resource pooling in contact centers, where the efficiency of a large single-skill center is achieved in a multi-skilled center with minimal flexibility. Staffing will be studied in each of three important time scales: real-time, short-term and long-term. Effort will be made to understand the contribution of different sources of uncertainty: model uncertainty, parameter uncertainty and process uncertainty.