CALL CENTERS (CENTRES) - Faculty of Industrial Engineering and ...
CALL CENTERS (CENTRES) - Faculty of Industrial Engineering and ...
CALL CENTERS (CENTRES) - Faculty of Industrial Engineering and ...
You also want an ePaper? Increase the reach of your titles
YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.
Keywords: Exponential (Markovian) queues, Ab<strong>and</strong>onments, Equilibrium analysis, Invisible<br />
queues, Performance-dependent behavior, Tele-services, Tele-queues, Call centers<br />
(Appears also in Section III.)<br />
117. Aksin, O. Zeynep <strong>and</strong> Patrick T. Harker. Capacity sizing in the presence <strong>of</strong> a common shared<br />
resource: Dimensioning an inbound call center, European Journal <strong>of</strong> Operational Research, 147<br />
(3), 2003, 464–483.<br />
Abstract. This paper studies a capacity sizing problem for service systems where capacity is<br />
determined by multiple types <strong>of</strong> resources that are required simultaneously in order to provide<br />
service. In addition to the simultaneous use <strong>of</strong> resources, the systems are characterized by the<br />
presence <strong>of</strong> a common resource that is shared across multiple types <strong>of</strong> customers. The paper<br />
focuses on inbound call centers as an important example <strong>of</strong> such systems. The capacity sizing<br />
problem in this context is one where the optimal number <strong>of</strong> servers that need to be allocated to<br />
different call types is determined. Optimality is defined as the number <strong>of</strong> servers that maximize<br />
revenues net <strong>of</strong> staffing costs. For the case where customers do not wait, it is shown that a<br />
greedy allocation procedure yields the optimal server allocation. Heuristics are proposed for<br />
the case with waiting customers that can exhibit impatience. The numerical analysis illustrates<br />
that for systems experiencing heavy loads <strong>and</strong> serving a diverse set <strong>of</strong> customers, the proposed<br />
heuristics outperform current methods that ignore the role <strong>of</strong> a shared resource in these types<br />
<strong>of</strong> dimensioning problems.<br />
Keywords: Queueing, Staff dimensioning, Resource sharing, Call center design<br />
118. Bhulai, S. <strong>and</strong> G. Koole. A queueing model for call blending in call centers, IEEE Transactions<br />
on Automatic Control, 48 (8), 2003, 1434–1438.<br />
Abstract. Call centers that apply call blending obtain high productivity <strong>and</strong> high service levels<br />
by dynamically mixing inbound <strong>and</strong> outbound traffic. We show that agents should be assigned<br />
to outbound calls if the number <strong>of</strong> available agents exceeds a certain threshold. This control<br />
policy is optimal for equal service time distributions <strong>and</strong> a very good approximation otherwise.<br />
Keywords: Call centres, Decision theory, Dynamic programming, Markov processes, Queueing<br />
theory, Stochastic processes<br />
119. Chevalier, P. <strong>and</strong> N. Tabordon. Overflow analysis <strong>and</strong> cross-trained servers, International Journal<br />
<strong>of</strong> Production Economics, 85 (1), 2003, 47–60.<br />
Abstract. In this paper, we evaluate the performance <strong>of</strong> a call center composed <strong>of</strong> specialized<br />
<strong>and</strong> cross-trained operators (i.e., operators trained to answer different classes <strong>of</strong> calls). The<br />
paper focuses on the approximation <strong>of</strong> the loss probability <strong>of</strong> a call center where the different<br />
classes <strong>of</strong> calls arrive according to a Poisson distribution <strong>and</strong> service time distribution is exponential.<br />
We make the simplifying assumption that calls not immediately answered are lost. Our<br />
closed form approximation is based on an approximation for hierarchical overflow systems in<br />
telecommunication developed by Hayward <strong>and</strong> later extended by Fredericks (1980).<br />
Keywords: Statistical decision theory, Operations research, Personnel management, Executive<br />
44