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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 – The airline industry is structurally challenged by its very nature, because of high overhead and capital costs. This is further exacerbated by macro-predictability and micro-uncertainty, thereby making it difficult for airlines in South Africa to attain operational efficiency. The purpose of this study is to identify drivers of operational efficiency and their impacts on airline performances in South Africa. Design/methodology/approach – An extensive data collection using primary and secondary sources enabled the researchers to gather data on all the airlines operating in South Africa, for the period of 2012-2016, on a variety of parameters. A two-stage empirical analysis was carried out, which involved estimation of operational efficiencies during the first stage by using data envelopment analysis (DEA) and determination of performance drivers during the second stage by using a two-way random-effects generalised least squares regression and also a Tobit model. Findings – From the study, it is clear that two structural drivers, namely, ‘‘aircraft size’’ and ‘‘seat load factor’’, and two executional drivers, namely, ‘‘low cost business model’’ and ‘‘revenue hours per aircraft’’, significantly impacted (p < 0.05) positively on airline efficiencies in South Africa. To improve efficiency, management should first concentrate on the drivers that can be changed in the short-term (executional drivers) and later focus on the drivers that require long-term planning (structural drivers). However, among the structural drivers, only ‘‘aircraft families’’ had a negative impact on airline efficiencies, whilst among executional drivers, only ‘‘block hours’’ negatively impacted on airline efficiencies. Research limitations/implications – Despite the importance of this study, it is not free of limitations. Firstly, because of the small size of the industry, fewer airlines and lack of detailed data, the study could not consider other important factors such as optimal routing and network structure. Secondly, although non-aeronautical revenues have become increasingly important in airline management, they were not included in this study. Further studies may investigate the impact of these factors on airline efficiency. Practical implications – The results have potential policy implications. Firstly, as the domestic airline market in South Africa is too small to operate with a smaller aircraft efficiently, airlines that intend to make use of smaller aircraft should first identify niche markets where they can have a route monopoly, such as SA Airlink. Secondly, as block time negatively affected airline efficiency, airlines can undertake schedule adjustments to reduce block time and thus improve technical efficiency. Originality/value – This paper is a first attempt to identify drivers of operational efficiency in the airline industry in South Africa. The results indicate that DEA is a useful tool to identify factors impacting airline efficiency and could improve airline performances in South Africa.en_US
dc.relation.ispartofTourism Reviewen_US
dc.subjectSouth Africa.en_US
dc.subjectData envelopment analysis.en_US
dc.subjectAirline efficiency.en_US
dc.subjectPerformance drivers.en_US
dc.titleThe airline industry in South Africa: drivers of operational efficiency and impacts.en_US
dc.typejournal articleen_US
dc.contributor.affiliationSchool of Hospitality and Tourism Managementen_US
item.openairetypejournal article-
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