A simulation model for managing customer waiting time in restaurants: scenarios and beyond (original) (raw)
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Analysis of Expected and Actual Waiting Time in Fast Food Restaurants
2012
People are willing to queue and pay to get food. Knowing peoples' opinions on queuing is of interest to restaurant stakeholders since it and related actions have a direct effect on revenue. While most previous studies focused on dine-in restaurants, we observed queuing for fast food restaurants. Specifically, we observed the actual waiting time of customers for a number of fast food restaurants, and compared the metrics with waiting times that customers expected. During lunch time peak hours, customers spent on average 5.4 minutes waiting before they could get their orders. The 5.4 minutes consisted of 2.42 minutes of queuing time and 2.98 minutes of service time. This total waiting time is only slightly below the actual expected waiting time of 5.42 minutes. How the fast food restaurants try to manage the perceived waiting time of customers was also discussed.
A Comparative Study of Restaurant Customers' Waiting Time in a Quasi-experimental Setting
Culinary Science & Hospitality Research
In recognition of the significance of waiting time in restaurant management, a quasi-experimental design was employed to measure the gap between actual and perceived waiting time in a real restaurant setting. In particular, this study focused on a comparison of Americans and Koreans to explore gender and culture differences in customer waiting behaviors. The results indicated that compared to American women, Korean women are more tolerant of waiting, and reported perceived waiting time as much longer than actual waiting time. However, there are no gender differences in both cultures. It is anticipated that managers will be able to adjust their operational strategies based on these results.
Application of queuing theory to a fast food outfit: a study of blue meadows restaurant
Independent Journal of Management & Production
The study evaluated the queuing system in Blue Meadows restaurant with a view to determining its operating characteristics and to improve customers’ satisfaction during waiting time using the lens of queuing theory. Data was obtained from a fast food restaurant in the University of Benin. The data collected was tested to show if it follows a Poisson and exponential distribution of arrival and service rate using chi square goodness of fit. A 95% confidence interval level was used to show the range of customers that come into the system at an hour time frame and the range of customers served at an hour time frame. Using the M/M/s model, the arrival rate, service rate, utilization rate, waiting time in the queue and the probability of customers likely balking from the restaurant was derived. The arrival rate (λ) at Blue Meadows restaurant was about 40 customers per hour, while the service rate was about 22 customers per hour per server. The number of servers present in the system was t...
Foodservice Research International, 2000
The purpose of this research was to evaluate the influence of waiting time on service quality and customer satisfaction. The surveys were distributed to customers in a cafeteria at a large northeastern university to measure service quality, customer satisfaction, expected reasonable waiting time, and perceived waiting time. Arrival rate and service times were collected to simulate actual waiting time. The results showed that when customers' expected reasonable waiting time was longer than perceived waiting time, the discrepancy between expected reasonable waiting time and perceived waiting time influenced service quality and customer satisfaction. The results also showed that negative correlations existed between simulated actual waiting time and customer perceptions of service quality.
The Effect of Perceived Waiting Time on Customer’s Satisfaction: A Focus on Fast Food Restaurant
International Journal of Supply Chain Management, 2018
Past research reveals that perceived waiting time was found to influence customer satisfaction and post-purchase behaviour. However, the present study aims to examine the effect of perceived waiting time on customer satisfaction in the context of fast food restaurant in Malaysia. In this study, simple random sampling method was employed and a total of 384 questionnaires were distributed. Consequently, 205 usable responses were successfully collected, representing 53% response rate. The data were analysed using SPSS software including descriptive analysis, reliability and validity test, factor analysis and correlation analysis. The result reveals that perceived waiting time significantly influence customer satisfaction towards fast food restaurants. Theoretically, this study confirmed the effects of perceived waiting time on customer satisfaction in the context of fast food restaurant. Practically, these findings are invaluable to fast food operators to improve the quality of their s...
The Effect of Perceived Waiting Time on Customer’s Satisfaction: A Focus on Fast Food Restaurant
2018
Past research reveals that perceived waiting time was found to influence customer satisfaction and post-purchase behaviour. However, the present study aims to examine the effect of perceived waiting time on customer satisfaction in the context of fast food restaurant in Malaysia. In this study, simple random sampling method was employed and a total of 384 questionnaires were distributed. Consequently, 205 usable responses were successfully collected, representing 53% response rate. The data were analysed using SPSS software including descriptive analysis, reliability and validity test, factor analysis and correlation analysis. The result reveals that perceived waiting time significantly influence customer satisfaction towards fast food restaurants. Theoretically, this study confirmed the effects of perceived waiting time on customer satisfaction in the context of fast food restaurant. Practically, these findings are invaluable to fast food operators to improve the quality of their s...
Case Study for Restaurant Queuing Model
ipedr.net
Restaurants would avoid losing their customers due to a long wait on the line. Some restaurants initially provide more waiting chairs than they actually need to put them in the safe side, and reducing the chairs as the time goes on safe space. However, waiting chairs alone would not solve a problem when customers withdraw and go to the competitor's door; the service time may need to be improved. This shows a need of a numerical model for the restaurant management to understand the situation better. This paper aims to show that queuing theory satisfies the model when tested with a real-case scenario. We obtained the data from a restaurant in Jakarta. We then derive the arrival rate, service rate, utilization rate, waiting time in queue and the probability of potential customers to balk based on the data using Little's Theorem and M/M/1 queuing model. The arrival rate at Sushi Tei during its busiest period of the day is 2.22 customers per minute (cpm) while the service rate is 2.24 cpm. The average number of customers in the restaurant is 122 and the utilization period is 0.991. We conclude the paper by discussing the benefits of performing queuing analysis to a busy restaurant.
Application of Queuing Model in a Restaurant (A Case Study of Kalinga Restaurant)
International Journal of Science and Research (IJSR)
In this work, to show that real life cases scenario when tested satisfied queuing theory, we obtain data from kalinga restaurant, Jodhpur. We then calculated the arrival rate, service rate, utilization rate, waiting time and the probability of potential customers to balk based on the collected data, Little's theorem and M/M/I queuing model. The arrival rate during busiest period of the day is 1.42 customer per minute. The average number of customers in the restaurant is 70 and utilisation rate of 0.9859. We conclude the work by given the concluding remarks.
SSRN Electronic Journal, 2000
Fundamental business principles are very critical to the growth and survival of the business. Waiting in line or queue causes inconvenience to customers and economic costs to firms. Queuing theory is a mathematical approach to the study of waiting in lines/queues. The study presents the results of a study that evaluates the effectiveness of a queuing model in identifying the restaurant queuing system efficiency parameters. It uses Little's Theorem to analyze data collected from Croc Foods Restaurant in Beitbridge over a three-week period. The study showed that on average 60 customers arrive every hour and the service rate is 84 customers per hour. Using the Queuing Theory calculator, the system utilization factor was 71.43%, the probability of zero customers waiting 0.2857, average number of customers waiting 1.782 and average waiting time 0.0298 hours. The study compared the single server model against multi-server model and concluded that M/M/1 model was not the best for Croc Foods restaurant.Using a questionnaire of 171 respondents, the study found out that about 43.3% of customers are not satisfied about the nature of waiting lines and about 69% customers have at least turned away at regular occasions due to the queues. The long term value of existing customers should not be overlooked; constant check for their changing needs and improvement in the time spent when serving them has been emphasized by the study.