IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v45y1999i2p192-207.html
   My bibliography  Save this article

Improving Service by Informing Customers About Anticipated Delays

Author

Listed:
  • Ward Whitt

    (AT&T Labs, Shannon Laboratory, 180 Park Avenue, Florham Park, New Jersey 07932-0971)

Abstract

This paper investigates the effect upon performance in a service system, such as a telephone call center, of giving waiting customers state information. In particular, the paper studies two M/M/s/r queueing models with balking and reneging. For simplicity, it is assumed that each customer is willing to wait a fixed time before beginning service. However, customers differ, so the delay tolerances for successive customers are random. In particular, it is assumed that the delay tolerance of each customer is zero with probability \beta , and is exponentially distributed with mean \alpha -1 conditional on the delay tolerance being positive. Let N be the number of customers found by an arrival. In Model 1, no state information is provided, so that if N \ge s, the customer balks with probability \beta ; if the customer enters the system, he reneges after an exponentially distributed time with mean \alpha -1 if he has not begun service by that time. In Model 2, if N = s + k \ge s, then the customer is told the system state k and the remaining service times of all customers in the system, so that he balks with probability \beta + (1 - \beta )(1 - q k ), where q k = P(T > S k ), T is exponentially distributed with mean \alpha -1 , S k is the sum of k + 1 independent exponential random variables each with mean (s\mu ) -1 , and \mu -1 is the mean service time. In Model 2, all reneging is replaced by balking. The number of customers in the system for Model 1 is shown to be larger than that for Model 2 in the likelihood-ratio stochastic ordering. Thus, customers are more likely to be blocked in Model 1 and are more likely to be served without waiting in Model 2. Algorithms are also developed for computing important performance measures in these, and more general, birth-and-death models.

Suggested Citation

  • Ward Whitt, 1999. "Improving Service by Informing Customers About Anticipated Delays," Management Science, INFORMS, vol. 45(2), pages 192-207, February.
  • Handle: RePEc:inm:ormnsc:v:45:y:1999:i:2:p:192-207
    DOI: 10.1287/mnsc.45.2.192
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.45.2.192
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mnsc.45.2.192?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Ward Whitt, 1999. "Predicting Queueing Delays," Management Science, INFORMS, vol. 45(6), pages 870-888, June.
    2. Linda Green & Peter Kolesar, 1991. "The Pointwise Stationary Approximation for Queues with Nonstationary Arrivals," Management Science, INFORMS, vol. 37(1), pages 84-97, January.
    3. Jimmie L. Davis & William A. Massey & Ward Whitt, 1995. "Sensitivity to the Service-Time Distribution in the Nonstationary Erlang Loss Model," Management Science, INFORMS, vol. 41(6), pages 1107-1116, June.
    4. William A. Massey & Ward Whitt, 1996. "Stationary-Process Approximations for the Nonstationary Erlang Loss Model," Operations Research, INFORMS, vol. 44(6), pages 976-983, December.
    5. Ward Whitt, 1991. "The Pointwise Stationary Approximation for Mt/Mt/s Queues Is Asymptotically Correct As the Rates Increase," Management Science, INFORMS, vol. 37(3), pages 307-314, March.
    6. Joseph Abate & Ward Whitt, 1995. "Numerical Inversion of Laplace Transforms of Probability Distributions," INFORMS Journal on Computing, INFORMS, vol. 7(1), pages 36-43, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. James Dong & Ward Whitt, 2015. "Using a birth‐and‐death process to estimate the steady‐state distribution of a periodic queue," Naval Research Logistics (NRL), John Wiley & Sons, vol. 62(8), pages 664-685, December.
    2. Izady, N. & Worthington, D., 2011. "Approximate analysis of non-stationary loss queues and networks of loss queues with general service time distributions," European Journal of Operational Research, Elsevier, vol. 213(3), pages 498-508, September.
    3. Achal Bassamboo & J. Michael Harrison & Assaf Zeevi, 2006. "Design and Control of a Large Call Center: Asymptotic Analysis of an LP-Based Method," Operations Research, INFORMS, vol. 54(3), pages 419-435, June.
    4. Niyirora, Jerome & Zhuang, Jun, 2017. "Fluid approximations and control of queues in emergency departments," European Journal of Operational Research, Elsevier, vol. 261(3), pages 1110-1124.
    5. Itai Gurvich & Ohad Perry, 2012. "Overflow Networks: Approximations and Implications to Call Center Outsourcing," Operations Research, INFORMS, vol. 60(4), pages 996-1009, August.
    6. Achal Bassamboo & J. Michael Harrison & Assaf Zeevi, 2009. "Pointwise Stationary Fluid Models for Stochastic Processing Networks," Manufacturing & Service Operations Management, INFORMS, vol. 11(1), pages 70-89, August.
    7. Ward Whitt, 2006. "Staffing a Call Center with Uncertain Arrival Rate and Absenteeism," Production and Operations Management, Production and Operations Management Society, vol. 15(1), pages 88-102, March.
    8. Chen, Xiaoming & Zhou, Xuesong & List, George F., 2011. "Using time-varying tolls to optimize truck arrivals at ports," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 965-982.
    9. Samantha L. Zimmerman & Alexander R. Rutherford & Alexa Waall & Monica Norena & Peter Dodek, 2023. "A queuing model for ventilator capacity management during the COVID-19 pandemic," Health Care Management Science, Springer, vol. 26(2), pages 200-216, June.
    10. Chen, Gang & Govindan, Kannan & Golias, Mihalis M., 2013. "Reducing truck emissions at container terminals in a low carbon economy: Proposal of a queueing-based bi-objective model for optimizing truck arrival pattern," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 55(C), pages 3-22.
    11. Defraeye, Mieke & Van Nieuwenhuyse, Inneke, 2016. "Staffing and scheduling under nonstationary demand for service: A literature review," Omega, Elsevier, vol. 58(C), pages 4-25.
    12. Linda V. Green & Peter J. Kolesar, 1998. "A Note on Approximating Peak Congestion in Mt/G/\infty Queues with Sinusoidal Arrivals," Management Science, INFORMS, vol. 44(11-Part-2), pages 137-144, November.
    13. R. Bekker & A. Bruin, 2010. "Time-dependent analysis for refused admissions in clinical wards," Annals of Operations Research, Springer, vol. 178(1), pages 45-65, July.
    14. René Bekker & Paulien Koeleman, 2011. "Scheduling admissions and reducing variability in bed demand," Health Care Management Science, Springer, vol. 14(3), pages 237-249, September.
    15. Yue Zhang & Martin L. Puterman & Matthew Nelson & Derek Atkins, 2012. "A Simulation Optimization Approach to Long-Term Care Capacity Planning," Operations Research, INFORMS, vol. 60(2), pages 249-261, April.
    16. Schwarz, Justus Arne & Selinka, Gregor & Stolletz, Raik, 2016. "Performance analysis of time-dependent queueing systems: Survey and classification," Omega, Elsevier, vol. 63(C), pages 170-189.
    17. Zeynep Akşin & Baris Ata & Seyed Morteza Emadi & Che-Lin Su, 2017. "Impact of Delay Announcements in Call Centers: An Empirical Approach," Operations Research, INFORMS, vol. 65(1), pages 242-265, February.
    18. Robert M. Saltzman & Vijay Mehrotra, 2001. "A Call Center Uses Simulation to Drive Strategic Change," Interfaces, INFORMS, vol. 31(3), pages 87-101, June.
    19. J. G. Dai & Pengyi Shi, 2017. "A Two-Time-Scale Approach to Time-Varying Queues in Hospital Inpatient Flow Management," Operations Research, INFORMS, vol. 65(2), pages 514-536, April.
    20. Moshe Haviv & Ramandeep S. Randhawa, 2014. "Pricing in Queues Without Demand Information," Manufacturing & Service Operations Management, INFORMS, vol. 16(3), pages 401-411, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:45:y:1999:i:2:p:192-207. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.