Using strategic idleness to improve customer service experience in service networks

The most common measure of waiting time is the overall expected waiting time for service. However, in service networks the perception of waiting may also depend on how it is distributed among different stations. Therefore, reducing the probability of a long wait at any station may be important in im...

Full description

Saved in:
Bibliographic Details
Main Authors: Baron, Opher, Berman, Oded, Krass, Dmitry, Wang, Jianfu
Other Authors: Nanyang Business School
Format: Article
Language:English
Published: 2015
Subjects:
Online Access:https://hdl.handle.net/10356/106738
http://hdl.handle.net/10220/25077
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-106738
record_format dspace
spelling sg-ntu-dr.10356-1067382023-05-19T06:44:41Z Using strategic idleness to improve customer service experience in service networks Baron, Opher Berman, Oded Krass, Dmitry Wang, Jianfu Nanyang Business School DRNTU::Business::Operations management The most common measure of waiting time is the overall expected waiting time for service. However, in service networks the perception of waiting may also depend on how it is distributed among different stations. Therefore, reducing the probability of a long wait at any station may be important in improving customers' perception of service quality. In a single-station queue it is known that the policy that minimizes the waiting time and the probability of long waits is nonidling. However, this is not necessarily the case for queueing networks with several stations. We present a family of threshold-based policies (TBPs) that strategically idle some stations. We demonstrate the advantage of strategically idling by applying TBP in a network with two single-server queues in tandem. We provide closed form results for the special case where the first station has infinite capacity and develop efficient algorithms when this is not the case. We compare TBPs with the nonidling and Kanban policies, and we discuss when a TBP is advantageous. Using simulation, we demonstrate that the analytical insights for the two-station case hold for a three-station serial queue as well. Accepted version 2015-02-24T05:30:07Z 2019-12-06T22:17:19Z 2015-02-24T05:30:07Z 2019-12-06T22:17:19Z 2014 2014 Journal Article Baron, O., Berman, O., Krass, D., & Wang, J. (2014). Using strategic idleness to improve customer service experience in service networks. Operations research, 62(1), 123-140. https://hdl.handle.net/10356/106738 http://hdl.handle.net/10220/25077 10.1287/opre.2013.1236 en Operations research © 2014 Institute for Operations Research and the Management Sciences (INFORMS). This is the author created version of a work that has been peer reviewed and accepted for publication by Operations Research, Institute for Operations Research and the Mangement Sciences (INFORMS). It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1287/opre.2013.1236]. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Business::Operations management
spellingShingle DRNTU::Business::Operations management
Baron, Opher
Berman, Oded
Krass, Dmitry
Wang, Jianfu
Using strategic idleness to improve customer service experience in service networks
description The most common measure of waiting time is the overall expected waiting time for service. However, in service networks the perception of waiting may also depend on how it is distributed among different stations. Therefore, reducing the probability of a long wait at any station may be important in improving customers' perception of service quality. In a single-station queue it is known that the policy that minimizes the waiting time and the probability of long waits is nonidling. However, this is not necessarily the case for queueing networks with several stations. We present a family of threshold-based policies (TBPs) that strategically idle some stations. We demonstrate the advantage of strategically idling by applying TBP in a network with two single-server queues in tandem. We provide closed form results for the special case where the first station has infinite capacity and develop efficient algorithms when this is not the case. We compare TBPs with the nonidling and Kanban policies, and we discuss when a TBP is advantageous. Using simulation, we demonstrate that the analytical insights for the two-station case hold for a three-station serial queue as well.
author2 Nanyang Business School
author_facet Nanyang Business School
Baron, Opher
Berman, Oded
Krass, Dmitry
Wang, Jianfu
format Article
author Baron, Opher
Berman, Oded
Krass, Dmitry
Wang, Jianfu
author_sort Baron, Opher
title Using strategic idleness to improve customer service experience in service networks
title_short Using strategic idleness to improve customer service experience in service networks
title_full Using strategic idleness to improve customer service experience in service networks
title_fullStr Using strategic idleness to improve customer service experience in service networks
title_full_unstemmed Using strategic idleness to improve customer service experience in service networks
title_sort using strategic idleness to improve customer service experience in service networks
publishDate 2015
url https://hdl.handle.net/10356/106738
http://hdl.handle.net/10220/25077
_version_ 1770566627947970560