Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMhlanga, Oswald.en_US
dc.descriptionPlease note that only UMP researchers are shown in the metadata. To access the co-authors, please view the full text.en_US
dc.description.abstractPurpose – 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 from42 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.en_US
dc.relation.ispartofInternational Journal of Culture, Tourism and Hospitality Research.en_US
dc.subjectSouth Africa.en_US
dc.subjectRevenue management.en_US
dc.subjectStochastic cost frontier.en_US
dc.subjectRestaurant capacity.en_US
dc.subjectRestaurant efficiency.en_US
dc.titleDrivers of restaurant efficiency in South Africa : a stochastic frontier approach.en_US
dc.typejournal articleen_US
dc.contributor.affiliationSchool of Hospitality and Tourism Managementen_US
item.openairetypejournal article-
item.fulltextWith Fulltext-
Appears in Collections:Journal articles
Files in This Item:
File Description SizeFormat 
  Until 2050-01-01
Published version.162.26 kBAdobe PDFView/Open    Request a copy
Show simple item record

Page view(s)

checked on Jan 8, 2021


checked on Jan 8, 2021

Google ScholarTM



Items in UMP Scholarship are protected by copyright, with all rights reserved, unless otherwise indicated.