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Allocating resources for a restaurant that serves regular and group-buying customers

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Abstract

Restaurants in China have recently begun offering group-buying (GB) options on the internet as a marketing and advertising tool to attract customers. GB coupon is available to parties of any size and the groups do not need to go together to the restaurants. Such restaurants serve two types of customers: GB customers with GB coupons and regular customers without coupons. One common practice for these restaurants is to set a maximum number of tables for each type of customer in advance and ask customers to wait in separate queues when all the tables for that customer type are occupied. As a result, restaurants are interested in finding optimal table allocation to serve the two types of customers to maximize profits. Since customers come follow a stochastic and discrete process, eat on a table that can be regarded as being served by a server in a queueing system, and wait in the queue when the restaurant is full, the dining process of customers and operating process of the restaurant is suitable to be described by queueing system. So, this study applies queueing theory to examine the table allocation problem. The effects of customer related parameters such as arrival rate and patience degree on the optimal allocation are discussed. The simulation model is extended to consider customers arriving in parties of different and serving tables of different sizes. We find that for a specific type of customer, if the arrival rate increases, the number of tables allocated for them increases. Patience degree has opposite influences on table allocation for the two types of customers: if regular customers are not patient, more tables should be allocated to them; while if GB customers are not patient, less tables should be allocated to them. If considering different customer party sizes and table sizes, as the arrival rate of regular customer increases, number of GB table decreases, number of tables for large (small) regular party first decreases (increases) and then increases (decreases).

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China (Grant Nos. 71390334, 71661167009), National Planning Office of Philosophy and Social Science (Grant No. 13ZDA022), the Fundamental of Research Funds for the Central Universities (2015jbzd01), China Scholarship Council (CSC) and Beijing Logistics Informatics Research Base.

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Authors and Affiliations

  1. School of Economics and Management, Beijing Jiaotong University, Haidian District, Beijing, 100044, China

    Tianhua Zhang, Juliang Zhang & Yihong Ru

  2. School of Mechanical Engineering, Purdue University, 585 Purdue Mall, West Lafayette, IN, 47907, USA

    Fu Zhao

  3. Division of Environmental and Ecological Engineering, Purdue University, 500 Central Drive, West Lafayette, IN, 47907, USA

    Fu Zhao & John W. Sutherland

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  1. Tianhua Zhang
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Correspondence to Fu Zhao.

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Zhang, T., Zhang, J., Zhao, F. et al. Allocating resources for a restaurant that serves regular and group-buying customers. Electron Commer Res 20, 883–913 (2020). https://doi.org/10.1007/s10660-018-9315-x

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