{"title":"Evaluation of Appointment Scheduling Rules: A Multi-Performance Measures Approach","authors":"S. Creemers, P. Colen, M. Lambrecht","doi":"10.2139/ssrn.2086264","DOIUrl":null,"url":null,"abstract":"Appointment scheduling rules are used to determine when a customer is to receive service. Many appointment scheduling rules exist and are being used in practice (e.g., in healthcare and legal services). Which appointment scheduling rule is best, however, is still an open question. In order to answer this question, we develop an analytical model that allows to assess the performance (in terms of customer waiting time, server idle time and server overtime) of appointment scheduling rules in a wide variety of settings. More specifically, the model takes into account: (1) customer unpunctuality, (2) no-shows, (3) service interruptions and (4) delay of the service process. In addition, we allow the use of general distributions to capture system processes. We adopt an \u000eefficient algorithm (with respect to computational and memory requirements) to assess the performance of 314 scheduling rules and use data envelopment analysis to compare results.","PeriodicalId":344620,"journal":{"name":"Entrepreneurship & Marketing eJournal","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Entrepreneurship & Marketing eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2086264","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Appointment scheduling rules are used to determine when a customer is to receive service. Many appointment scheduling rules exist and are being used in practice (e.g., in healthcare and legal services). Which appointment scheduling rule is best, however, is still an open question. In order to answer this question, we develop an analytical model that allows to assess the performance (in terms of customer waiting time, server idle time and server overtime) of appointment scheduling rules in a wide variety of settings. More specifically, the model takes into account: (1) customer unpunctuality, (2) no-shows, (3) service interruptions and (4) delay of the service process. In addition, we allow the use of general distributions to capture system processes. We adopt an efficient algorithm (with respect to computational and memory requirements) to assess the performance of 314 scheduling rules and use data envelopment analysis to compare results.