Authors:

A.O. Gurtuev, B.K. Buzdov

Institute of Computer Science and Problems of Regional Management – Branch of Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences, Nalchik, Russia

Abstract:

In highly competitive environments, restaurants must balance revenue and service quality under stochastic demand. Analyzing customer arrival patterns becomes critical, since traditional metrics obscure periods of idleness and overload. The article examines the role of the temporal structure of demand distribution in shaping restaurant revenue under capacity constraints. The methodological foundation lies in queueing theory and the process-based approach to service management. The study employs simulation modelling; the model incorporates the total dining room capacity, stochastic service times, queues, and customer churn. The empirical base consists of industry-specific analytical reports used to profile different types of restaurants. The temporal distribution of potential demand is proved to be a more informative determinant of economic performance than aggregate demand. High temporal concentration of demand renders certain types of restaurants unprofitable despite substantial overall demand. In contrast, multimodal arrival profiles enable more efficient capacity utilization and increase the conversion of potential demand into actual sales. The obtained results expand on standard approaches to demand analysis in the service sector and demonstrate the need to consider the temporal structure of customer arrivals in strategic decision-making. The model serves as a practical tool for scenario analysis and can be adapted to a wide range of service markets with limited capacity and time-sensitive demand.

Keywords: strategic management; service industry; restaurant management; queuing system; customer arrival patterns; simulation modelling.

For citation: Gurtuev A.O., Buzdov B.K. (2026). Customer flow management in enhancing restaurant business efficiency. Upravlenets / The Manager, vol. 17, no. 4, pp. 93–111. DOI: 10.29141/2218-5003-2026-17-4-7. EDN: FGBGGE.

Article info: received March 17, 2026; received in revised form April 27, 2026; accepted May 14, 2026