Drivers of restaurant efficiency in South Africa: a stochastic frontier approach

Purpose Restaurants in South Africa have a notoriously high failure rate. This study aims to identify drivers of restaurant efficiency in South Africa. Design/methodology/approach A stochastic cost frontier function with three inputs (i.e. labour, food and beverage and materials) and one output as the total revenue is specified and used to estimate restaurant efficiency. An extensive data collection using primary and secondary sources enabled the researcher to gather data from 42 restaurants, for the year 2016, on a variety of parameters. Findings The findings show that on average restaurants were operating at 77%, with the most and least efficient restaurants operating at a 97 and a 43% efficiency level, respectively. From the study, it is clear that two structural drivers, namely, “location” and “operation type”, and two executional drivers, namely, “restaurant type” and “revenue per available seat hour”, significantly impacted ( p < 0.05) on restaurant efficiency in South Africa. Research limitations/implications Despite the importance of this study, it is not free of limitations. First, the research was based on efficiency drivers for restaurants situated in a specific South African province. Caution is therefore required when generalising the findings of this study to restaurants in other geographic areas, as a replication of this study in other geographic areas might reveal varying levels of efficiency. Second, the measurement of restaurant efficiency was limited to five efficiency drivers. Even though these efficiency drivers were included in other studies as well, there could be other relevant efficiency drivers that are likely to influence restaurant efficiency. Practical implications To improve efficiency, restaurateurs should first concentrate on the drivers that can be changed in the short term (executional drivers) and then later focus on the drivers that require long-term planning (structural drivers). Restaurateurs should understand the use of RevPASH strategies to manipulate demand during peak and off-peak periods. Furthermore, restaurants should be able to change the table mix to optimise table configuration. Changing a restaurant’s table configuration during peak times increases efficiency. Originality/value This paper is a first attempt to identify drivers of operational efficiency using a stochastic approach in the restaurant industry in South Africa. As restaurants in South Africa have a high failure rate, the results could assist restaurateurs in managing more successful entities.