Abstract
The tourism sector is service intensive and highly competitive. As a result, tourism establishments compete on quality of customer service, tourist experience and value for money in order to gain competitive advantage over competitors. Grading is a quality assurance process in which tourism establishments are classified using nomenclature such as stars, denoting luxury of services and facilities provided. The more stars an establishment is awarded, the more superior the luxury of services and facilities, customer service, tourist experience and value for money being provided. Therefore, graded tourism establishments are likely to have a competitive advantage over non-graded tourism establishments, resulting in an increase in their client base, profitability and ultimately business survival. This is because tourists are more likely to stay at a graded establishment, as they can be assured of predictable and guaranteed levels of quality. In addition, over R9 billion spent by the South African government in 2019 on travel and subsistence benefited only graded establishments, as South African government officials travelling for official purposes are required to book accommodation in graded establishments only. Given the benefits of being graded, the number of graded establishments remains low. What is also concerning is the low percentage of black-owned tourism establishments which are graded. This hinders transformation efforts within the tourism sector, given that tourism in South Africa continues to be characterised by disparities in access to benefits and opportunities, particularly for black people. The South African tourism sector remains largely white-owned with little transformation. Government programmes which have been established to subsidise the cost of grading have failed to substantially increase the number of graded establishments. In fact, this number is decreasing. Artificial intelligence (AI) is an analytical discovery which enables analyses of hidden patterns and information using various algorithms, including prediction, clustering and relationship mining. AI enables predictive models to be created based on regression, as well as classification based on discrete data. The focus of this research study was to identify variables that influence the grading of tourism establishments and utilise them to construct a computational intelligence framework for increasing the number of graded accommodation establishments. A Bayesian model was constructed to aid the development of the framework.
M.Com.