To read this content please select one of the options below:

Delay announcements for call centers with hyperexponential patience modeling

Miao Yu (School of Management, Shenyang Jianzhu University, Shenyang City, China)
Jun Gong (College of Information Science and Engineering, Northeastern University, Shenyang City, China)
Jiafu Tang (Northeastern University, Shenyang City, China)
Fanwen Kong (School of Management, Shenyang Jianzhu University, Shenyang City, China)

Industrial Management & Data Systems

ISSN: 0263-5577

Article publication date: 10 July 2017




The purpose of this paper is to provide delay announcements for call centers with hyperexponential patience modeling. The paper aims to employ a state-dependent Markovian approximation for informing arriving customers about anticipated delay in a real call center.


Motivated by real call center data, the patience distribution is modeled by the hyperexponential distribution and is analyzed by its realistic significance, with and without delay information. Appropriate M/M/s/r+H2 queueing model is structured, including a voice response system that is employed in practice, and a state-dependent Markovian approximation is applied for computing abandonment. Based on this approximation, a method is proposed for estimating virtual delays, and it is investigated about the problem of announcing virtual delays to customers upon their arrival.


There are two parts of findings from the results obtained from the case study and a numerical study of simulation comparisons. First, using an H2 distribution for the abandonment distribution is driven by an empirical study which shows its good fit to real-life call center data. Second, simulation experiments indicate that the model and approximation are reasonable, and the state-dependent Markovian approximation works very well for call centers with larger pooling. It is concluded that our approach can be applied in a voice response system of real call centers.


Many results pertain to announcing delay information, customer reactions and links to estimating hyperexponential distribution based on real data that have not been established in previous studies; however, this paper analytically characterizes these performance measures for delay announcements.



This project is supported by the National Nature Science Foundation under Grant No. 71271052.


Yu, M., Gong, J., Tang, J. and Kong, F. (2017), "Delay announcements for call centers with hyperexponential patience modeling", Industrial Management & Data Systems, Vol. 117 No. 6, pp. 1037-1057.



Emerald Publishing Limited

Copyright © 2017, Emerald Publishing Limited

Related articles