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

tions to Hayward’s approximation, generalized peakedness, asymptotic expansions for the Erlang
loss function, the normal-distribution method, and bounds for the blocking probability. For the
case of no extra waiting space, a renewal arrival process and an exponential service-time distribution
(the GI/M/s/O model), a heavy-traffic local limit theorem by A.A. Borovkov implies that
the blocking depends on the arrival process only through the first two moments of the renewal
interval as the offered load increases. Moreover, in this situation, Hayward’s approximation is
asymptotically correct.
Keywords: Probability, Queueing theory, Telecommunication traffic, Service systems, Blocking,
Blocking probability, Congestion measures, Servers, Waiting spaces, G/GI/s/r model, Heavy
traffic limit theorems, Conditioning heuristic, Hayward’s approximation, Peakedness, Asymptotic
expansions, Erlang loss function, Normal distribution method, Exponential service time
distribution, GI/M/s/O model, Arrival process
15. Mabert, V.A. Short interval forecasting of emergency phone call (911) work loads, Journal of
Operations Management, 5 (3), 1985, 259–271.
Abstract. There has been a growing emphasis over the last 5–10 years on improving productivity
in the service sector of the US economy. Effective scheduling of the workforce in these
organizations requires good estimates of demand, which may show substantial variations between
days for certain times of the year. An examination is made of the use of 6 different forecasting
methods for predicting daily emergency call workloads for the Indianapolis Police Department’s
communications area: 1. one-year lag, 2. zero/one regression, 3. multiplicative/additive, 4.
zero/one with adjustment, 5. multiplicative/additive with adjustment, and 6. autoregressive,
integrated moving average intervention. The research suggests that there are clearly significant
differences in performance for the 6 models analyzed. Simple modeling approaches can perform
well in the complex environments found in many service organizations. Special tailoring of the
forecasting model is required for many service firms. Historical data patterns for these organizations
tend to be more involved than just trend and seasonal elements.
Keywords: Studies, Police, Mathematical models, Implementations, Forecasting techniques,
Emergencies, Departments, Communications, Case studies
(Appears also in Section II.)
16. Hoffman, K.L. and C.M. Harris. Estimation of a caller retrial rate for a telephone information
system, European Journal of Operational Research, 27 (2), 1986, 207–214.
Abstract. As part of a continuing study of the usage of its Taxpayer Service Telephone Network,
the US Internal Revenue Service wished to determine more accurate methods for demand
measurement. It has long been recognized that the total number of calls coming into such a busy
telephone system overestimates the actual number of distinct callers. The service had previously
estimated its real demand by adding ( 1
3 ) of both the number of blocked or overflow calls and
the number of abandonments to the total actually answered. The thrust of this current study
then was to develop an accurate statistical method for providing a more objective formula for
this true demand, which turns out to be equivalent to estimating the probability of retrial by
blocked and abandoned callers.
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