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CALL CENTERS (CENTRES) - Faculty of Industrial Engineering and ...

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108. Masi, Denise M. Bevilacqua, Martin Fisher <strong>and</strong> Carl M. Harris. Computation <strong>of</strong> steady-state<br />

probabilities for resource sharing call center queueing systems, Stochastic Models [online], 17 (2),<br />

2001 [viewed July 24, 2001].<br />

Abstract. Two routing rules for a queueing system <strong>of</strong> two stations are considered as alternative<br />

models for modeling a call-center network. These routing rules allow customers to switch queues<br />

under certain server <strong>and</strong> other resource availability conditions, either external to the system upon<br />

arrival to the network, or internal to the system after arrival to a primary call center. Under<br />

the assumption <strong>of</strong> Poisson arrivals <strong>and</strong> exponentially distributed service times, these systems are<br />

analyzed using matrix-geometric techniques, yielding a non-trivial set <strong>of</strong> ergodicity conditions<br />

<strong>and</strong> the steady-state joint probability distribution for the number <strong>of</strong> customers at each station.<br />

An extensive numerical analysis is conducted, yielding some physical insight into these systems<br />

<strong>and</strong> related generalizations.<br />

109. Shumsky, R. <strong>and</strong> E. Pinker. Gatekeepers <strong>and</strong> referrals in services. Working paper OP01-02,<br />

Simon School, University <strong>of</strong> Rochester, 2001.<br />

Abstract. We examine services in which customers encounter a gatekeeper who makes an initial<br />

diagnosis <strong>of</strong> the customer’s problem <strong>and</strong> then may refer the customer to a specialist. The gatekeeper<br />

may also attempt to solve the problem, but the probability <strong>of</strong> treatment success decreases<br />

as the problem’s complexity increases. Given the costs <strong>of</strong> treatment by the gatekeeper <strong>and</strong> the<br />

specialist, we find the firm’s optimal referral rate from a particular gatekeeper to the specialists.<br />

We then consider the principal-agent problem that arises when the gatekeeper, but not the firm,<br />

observes the gatekeeper’s treatment ability as well as the complexity <strong>of</strong> each customer’s problem.<br />

We examine the relative benefits <strong>of</strong> compensation systems designed to overcome the effects<br />

<strong>of</strong> this information asymmetry <strong>and</strong> identify when bonuses based solely on referral rates do not<br />

ensure first-best system performance. We also consider the value <strong>of</strong> such output-based contracts<br />

when gatekeepers are heterogeneous in ability, so that two gatekeepers face different probabilities<br />

<strong>of</strong> treatment success when given the same problem. Finally, we compare environments in which<br />

the gatekeeper is, <strong>and</strong> is not, faced with risk in the form <strong>of</strong> significant variance in compensation.<br />

110. Atlason, Julius, Marina A. Epelman <strong>and</strong> Shane G. Henderson. Combining simulation <strong>and</strong> cutting<br />

plane methods in service systems. Proceedings <strong>of</strong> the 2002 National Science Foundation<br />

Design, Service <strong>and</strong> Manufacturing Grantees Conference, 2002.<br />

Abstract. In this paper we describe a method that combines simulation <strong>and</strong> cutting plane<br />

methods to solve resource allocation <strong>and</strong> scheduling problems. We solve a relaxed linear (integer)<br />

program iteratively <strong>and</strong> pass the solution <strong>of</strong> each iteration to a simulation. The results<br />

<strong>of</strong> the simulation are used to generate constraints in the linear (integer) program. We provide<br />

conditions under which the solutions <strong>of</strong> the linear (integer) program converges to an optimal<br />

solution <strong>of</strong> the unrelaxed problem. The concavity <strong>of</strong> the underlying service level function is<br />

critical for the method <strong>and</strong> we present a linear programming method to numerically check the<br />

concavity <strong>of</strong> a function.<br />

111. Chen, Bert P.K. <strong>and</strong> Shane G. Henderson. Two issues in setting call centre staffing levels, Annals<br />

41

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