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Real-time delay prediction in customer service systems.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
書名/作者:	Real-time delay prediction in customer service systems.
作者:	Ibrahim, Rouba.
面頁冊數:	282 p.
附註:	Source: Dissertation Abstracts International, Volume: 71-09, Section: B, page: 5767.
Contained By:	Dissertation Abstracts International71-09B.
標題:	Operations Research.
ISBN:	9781124180892
摘要、提要註:	It is common practice in service systems to have customers who cannot be served immediately upon arrival wait in queue until system resources become available to the customer. A customer's waiting experience typically affects his evaluation of the service provided. For service providers, making delay announcements is a relatively inexpensive way of reducing customer uncertainty about delays, thereby improving customer satisfaction with the service provided. Our work focuses on applying queuing theory and computer simulation to develop effective ways to accurately predict customer delay in customer service systems, in real time. Primarily, these real-time delay predictions are intended to help service providers make delay announcements. But, they may also be used by service providers to better manage their systems. For instance, recognizing that customer delay is longer than planned at a service facility, the service provider may elect to provide additional service at that facility in order to reduce customer delay. Our general approach is to consider large heavily-loaded queueing models that mimic the operations of a real-life service system such as call center or a hospital emergency department. We are particularly concerned with the practical appeal of our delay prediction procedures. That is why we incorporate important real-life phenomena such as customer abandonment, time-varying arrival rates, and a time-varying number of servers. We also consider general arrival, service, and abandonment-time distributions (exponential and non-exponential), which are commonly observed in practice. We use heavy traffic limits and computer simulation to quantify the accuracy of the alternative delay predictors proposed, and to compare them with delay predictors commonly used in practice.
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3420817

Real-time delay prediction in customer service systems.
Ibrahim, Rouba.

Real-time delay prediction in customer service systems. - 282 p.

Source: Dissertation Abstracts International, Volume: 71-09, Section: B, page: 5767.

Thesis (Ph.D.)--Columbia University, 2010.

It is common practice in service systems to have customers who cannot be served immediately upon arrival wait in queue until system resources become available to the customer. A customer's waiting experience typically affects his evaluation of the service provided. For service providers, making delay announcements is a relatively inexpensive way of reducing customer uncertainty about delays, thereby improving customer satisfaction with the service provided. Our work focuses on applying queuing theory and computer simulation to develop effective ways to accurately predict customer delay in customer service systems, in real time. Primarily, these real-time delay predictions are intended to help service providers make delay announcements. But, they may also be used by service providers to better manage their systems. For instance, recognizing that customer delay is longer than planned at a service facility, the service provider may elect to provide additional service at that facility in order to reduce customer delay. Our general approach is to consider large heavily-loaded queueing models that mimic the operations of a real-life service system such as call center or a hospital emergency department. We are particularly concerned with the practical appeal of our delay prediction procedures. That is why we incorporate important real-life phenomena such as customer abandonment, time-varying arrival rates, and a time-varying number of servers. We also consider general arrival, service, and abandonment-time distributions (exponential and non-exponential), which are commonly observed in practice. We use heavy traffic limits and computer simulation to quantify the accuracy of the alternative delay predictors proposed, and to compare them with delay predictors commonly used in practice.

ISBN: 9781124180892Subjects--Topical Terms:

423094
Operations Research.

Real-time delay prediction in customer service systems.
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245 1 0 $a Real-time delay prediction in customer service systems.
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520 $a It is common practice in service systems to have customers who cannot be served immediately upon arrival wait in queue until system resources become available to the customer. A customer's waiting experience typically affects his evaluation of the service provided. For service providers, making delay announcements is a relatively inexpensive way of reducing customer uncertainty about delays, thereby improving customer satisfaction with the service provided. Our work focuses on applying queuing theory and computer simulation to develop effective ways to accurately predict customer delay in customer service systems, in real time. Primarily, these real-time delay predictions are intended to help service providers make delay announcements. But, they may also be used by service providers to better manage their systems. For instance, recognizing that customer delay is longer than planned at a service facility, the service provider may elect to provide additional service at that facility in order to reduce customer delay. Our general approach is to consider large heavily-loaded queueing models that mimic the operations of a real-life service system such as call center or a hospital emergency department. We are particularly concerned with the practical appeal of our delay prediction procedures. That is why we incorporate important real-life phenomena such as customer abandonment, time-varying arrival rates, and a time-varying number of servers. We also consider general arrival, service, and abandonment-time distributions (exponential and non-exponential), which are commonly observed in practice. We use heavy traffic limits and computer simulation to quantify the accuracy of the alternative delay predictors proposed, and to compare them with delay predictors commonly used in practice.
520 $a Keywords: Real-time delay prediction; delay announcements, many-server queues; simulation; heavy-traffic; call centers; customer abandonment; time-varying arrival rates; nonstationary queues; time-varying number of servers
590 $a School code: 0054.
650 4 $a Operations Research. $3 423094
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