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Factors impacting restaurant efficiency: a data envelopment analysis

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PurposeRestaurants are characterised by predictable, seasonal factors and unpredictable, individual customer demand, which make it difficult for restaurateurs to attain efficiency. A combination of these two factors, macro-predictability and micro-uncertainty, produces economic risks, which make it difficult for restaurants to attain operational efficiency. The purpose of this study is to identify factors impacting restaurant efficiency in South Africa.Design/methodology/approachBy using primary and secondary sources, data were collected from 16 different types of restaurants in South Africa, for the period 2012-2016, on a variety of parameters. A two-stage empirical analysis was carried out, which involved the estimation of operational efficiencies during the first stage by using data envelopment analysis (DEA) and determination of factors impacting restaurant performance in South Africa during the second stage by using two-way random-effects generalised least squares and Tobit regression models.FindingsThe results clearly show that the ability of restaurants to succeed will not be determined by their size but by their type, location and revenue per available seat. While the study finds various factors impacting on operational efficiency, the survival of restaurants in South Africa seem to be determined by cost efficiency, which brings in better market performance through lowering cost of sales.Practical implicationsThe results have implications for restaurant managers in that if they want to improve cost efficiency, they must manage restaurant capacity and customer demand in a way that maximises revenue. To stimulate demand during periods of low demand, management could consider strategies that attract more customers or encourage upselling, whereas during periods of high demand, management may consider raising prices or reducing meal durations. The results indicate that DEA is a useful tool to identify factors impacting restaurant efficiency and could enhance the service data and revenue management with regards to restaurant efficiency in South Africa.Originality/valueTo the best of the author’s knowledge, this paper is the first that attempts to identify factors impacting restaurant efficiency in South Africa by using DEA. The findings could enhance the service data and revenue management with regards to restaurant efficiency in South Africa.
Title: Factors impacting restaurant efficiency: a data envelopment analysis
Description:
PurposeRestaurants are characterised by predictable, seasonal factors and unpredictable, individual customer demand, which make it difficult for restaurateurs to attain efficiency.
A combination of these two factors, macro-predictability and micro-uncertainty, produces economic risks, which make it difficult for restaurants to attain operational efficiency.
The purpose of this study is to identify factors impacting restaurant efficiency in South Africa.
Design/methodology/approachBy using primary and secondary sources, data were collected from 16 different types of restaurants in South Africa, for the period 2012-2016, on a variety of parameters.
A two-stage empirical analysis was carried out, which involved the estimation of operational efficiencies during the first stage by using data envelopment analysis (DEA) and determination of factors impacting restaurant performance in South Africa during the second stage by using two-way random-effects generalised least squares and Tobit regression models.
FindingsThe results clearly show that the ability of restaurants to succeed will not be determined by their size but by their type, location and revenue per available seat.
While the study finds various factors impacting on operational efficiency, the survival of restaurants in South Africa seem to be determined by cost efficiency, which brings in better market performance through lowering cost of sales.
Practical implicationsThe results have implications for restaurant managers in that if they want to improve cost efficiency, they must manage restaurant capacity and customer demand in a way that maximises revenue.
To stimulate demand during periods of low demand, management could consider strategies that attract more customers or encourage upselling, whereas during periods of high demand, management may consider raising prices or reducing meal durations.
The results indicate that DEA is a useful tool to identify factors impacting restaurant efficiency and could enhance the service data and revenue management with regards to restaurant efficiency in South Africa.
Originality/valueTo the best of the author’s knowledge, this paper is the first that attempts to identify factors impacting restaurant efficiency in South Africa by using DEA.
The findings could enhance the service data and revenue management with regards to restaurant efficiency in South Africa.

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