Scheduling Arrivals to Queues: A Single-Server Model with No-Shows

Refael Hassin () and Sharon Mendel ()
Additional contact information
Refael Hassin: School of Mathematical Sciences, Tel Aviv University, Tel Aviv 69978, Israel
Sharon Mendel: School of Mathematical Sciences, Tel Aviv University, Tel Aviv 69978, Israel

Management Science, 2008, vol. 54, issue 3, 565-572

Abstract: Queueing systems with scheduled arrivals, i.e., appointment systems, are typical for frontal service systems, e.g., health clinics. An aspect of customer behavior that influences the overall efficiency of such systems is the phenomenon of no-shows. The consequences of no-shows cannot be underestimated; e.g., British surveys reveal that in the United Kingdom alone more than 12 million general practitioner (GP) appointments are missed every year, costing the British health service an estimated £250 million annually. In this study we answer the following key questions: How should the schedule be computed when there are no-shows? Is it sufficiently accurate to use a schedule designed for the same expected number of customers without no-shows? How important is it to invest in efforts that reduce no-shows--i.e., given that we apply a schedule that takes no-shows into consideration, is the existence of no-shows still costly to the server and customers?

Keywords: appointment scheduling; health care; no-show; queue; single server (search for similar items in EconPapers)
Date: 2008
References: View complete reference list from CitEc
Citations: View citations in EconPapers (64)

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.1070.0802 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:54:y:2008:i:3:p:565-572

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().