• Journal of the Korea Society for Simulation
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• v.27 no.2
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• pp.91-100
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• 2018

Recently, the traditional call center, which has an important role as the customer's primary contact point, has been transformed into the omni-channel contact center which supports an additional variety of access channels in addition to phone calls in order to improve customer accessibility and convenience. The omni-channel contact center has agents on each channel which are vital in determining the response rate and waiting time for the customer. In traditional call centers, agents can be assigned to a call based on the characteristics of the call, however in omni-channel contact centers, the characteristics of issues vary and come in through multiple channels, each with their own characteristics, making it difficult to assign the appropriate agent for the issue. Customers must also be processed at the same time, adding an additional layer of complexity to the issue. This paper analyzes and simulates an omni-channel contact center that accommodates email, chat, voice calls and video consultation, and investigates how to optimize the allocation of agents.

• Journal of Korea Multimedia Society
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• v.12 no.1
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• pp.31-40
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• 2009

Call centers have become the prevalent contact points between companies and their customers. By virtue of recent advances in communication technology, the number and size of call centers have grown dramatically. As a large portion of the operating costs are related to the labor costs, efficient design and workforce staffing are crucial for the economic success of call centers. Therefore it is very important to determine the adequate number of agents. In this context, the workforce staffing level can be modeled as mathematical optimization problem using queueing theory. In this paper, we deal with an approximate analysis of an N-design call center with two finite queues and two types of reneging customers by using the state decomposition method. We also represent some numerical examples and show the impact of the system parameters on the performance measures of the call center.