Analysing Customer Waiting Time Using Queuing Models

Abstract

Customer experiences are of very importance to restaurants to remain longer in the industry. Customers complain that they have to wait before they can be seated and placed their orders or food to be delivered and this is a negative factor to their experiences and there is a high likelihood that they will not come again. The customers then get frustrated and leave them with reviews making it impossible to attract other potential customers. This translates into a disrepute revenue stream and a bad image of the restaurant. As most establishments attempt to integrate good processes with quality service, shortening of wait times is usually among the highest priorities. The necessity to simplify the processes is even more significant in high volume periods. This becomes all the more relevant in cases of poor staffing. The paper concentrates particularly on the application of the queuing theory in reducing customer waiting time in dine-in restaurants and in particular the assessment of single and multi-server queuing models in Zus Coffee Cubic Botanical in Pantai Dalam Kuala Lumpur and 7-Eleven in Shizuoka. It is only concerned with the effectiveness of single-server and multi-server queuing models at peak and off-peak hour services. Dine-in and takeaway ordering processes of customer service are also covered and order services, which imply drive-thru and mobile application ordering, are not. The operational improvements and customer satisfaction goal of this study is to be supported by the findings. The analyses and the data processing are done in MATLAB.