A simulation model for managing customer waiting time in restaurants: scenarios and beyond
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Dosyalar
Tarih
2020
Yazarlar
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Yayıncı
Emerald Group Publishing Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Purpose The purpose of this paper is to investigate the effects of capacity decisions regarding the number of servers/chefs and tables on identifying a change in the number of wait-related anxious customers, customer losses and customers served to meet the waiting time standards of an actual upscale restaurant. Design/methodology/approach The authors applied a simulation model to present the consequences of restaurant capacity decisions based on waiting time standards. Arena Simulation Software, licensed by Rockwell Automation, was used for modeling and identifying distributions of the data set provided by the restaurant. An experiment was designed for an upscale restaurant with existing five servers/chefs and 50 tables by changing these resources to measure the changes in customers' wait-related anxiety and other service performance indicators. Findings The results showed that an additional server/chef on weekends decreases the daily average number of anxious customers by nearly 33% and increases the daily average number of customers served by nearly 3% and has a little positive effect of decreasing customer losses. Table insertion for high- and low-requested seating areas had an only positive effect on decreasing customer losses. Originality/value In this study, the service capacity is dependent on waiting time, and it is addressed to study the relationship with customers' wait-related anxiety, which is a subjective metric. This study developed a point of view for identifying anxious customers whose waiting times are much longer than their cooking and delivery duration expectations regarding their meal preferences in the cooking stage and waiting experiences in the service entry.
Açıklama
Anahtar Kelimeler
Service delivery, Customer anxiety, Customer service, Simulation, Service Quality, Management, Delivery, Impact, Delays, Stage, Field
