Show simple item record

dc.contributor.advisorSaayman, A.
dc.contributor.authorMinnaar, Reneé
dc.date.accessioned2018-02-06T14:19:51Z
dc.date.available2018-02-06T14:19:51Z
dc.date.issued2017
dc.identifier.urihttp://hdl.handle.net/10394/26261
dc.descriptionPhD (Tourism Management), North-West University, Potchefstroom Campus, 2017en_US
dc.description.abstractWorldwide, skills shortages in the labour market have become more pronounced over the past several years. This has led to a vast gap in talent which has devastating impacts in especially the service industries, such as the accommodation industry, which are widely known to be more heavily reliant on human interaction that other industries. The accommodation industry is also an under-skilled industry, with employment structures that are ill equipped to deal with the diverse skills needed to be successfully employed and to climb the succession ladder in this industry. South Africa is becoming a popular tourist destination. The industry is growing and tourism is therefore becoming a major contributor to economic growth and employment of employees with varying skill levels in the country. This study aims to forecast the demand for various job levels and the qualifications required to meet this growing demand in the accommodation industry in South Africa – a key component of the tourism offering. The research question addressed in this study was “What is the demand for labour with different levels of education in the accommodation sector of South Africa over the next 5 years?” This study uses a combination of qualitative and quantitative research methods. Due to variations in demand and supply of employees in the hospitality industry, data is scarce and mostly qualitative in nature. For the quantitative part of the research, data from Statistics South Africa (Stats SA), Culture Arts Tourism Hospitality and Sport Sector Education and Training Authority (CATHSSETA), as well as labour and other sectoral data from Quantec are used. Quantitative forecasting results are based on time series forecasting methods, the bottom-up coefficient approach and the top-down approach to manpower planning. The time-series forecasts and the bottom-up approach deliver comparable results, while the top-down approach gives inflated labour demand figures. Three scenarios based on these forecasts were presented to role players of the financial and human resources departments of the largest and most influential accommodation groups in South Africa for qualitative adjustment. After the adjustments made by the experts, the results of this study indicate that the demand for highly skilled labour for the managerial category is higher than the other highly skilled categories, and that these occupations require a minimum of a diploma or degree. For the skilled labour category, the demand is highest in the service and sales workers category, for which certificates and diplomas are seen as minimum requirements. The important contributions of this study towards the industry, are that educational institutions are able to better prepare graduates for the accommodation industry, ensuring that the graduates meet the demands of the industry in terms of qualifications and skills. In terms of policy recommendations, the accommodation industry could develop industry specific policies to deal with the challenges around the negative image of the accommodation industry in terms of long hours, unskilled work, and low wages. In terms of research recommendations, the bottom-up approach and the time-series methods provide comparable results and can be utilised for labour forecasting in other industries alsoen_US
dc.language.isoenen_US
dc.publisherNorth-West University (South Africa) , Potchefstroom Campusen_US
dc.subjectLabour demanden_US
dc.subjectAccommodation industryen_US
dc.subjectForecastingen_US
dc.titleCombining quantitative and qualitative methods in forecasting qualified labour demand in the South African accommodation industryen_US
dc.typeThesisen_US
dc.description.thesistypeDoctoralen_US
dc.contributor.researchID10225595 - Saayman, Andrea (Supervisor)


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record