Readiness of the hospitality industry to adopt on-line marketing technology in Mpumalanga
Abstract
The study examines the readiness of the hospitality industry in Mpumalanga, South Africa to adopt online marketing technologies by considering what online marketing technologies are currently adopted in the industry, what online marketing technologies are available and whether there is a readiness to adopt online marketing technologies by determining what factors enable or disable owners to accept online marketing technologies. It determines how online, Internet, digital, virtual, and e-marketing technologies and trends are conceptualised within literature, identifies factors which can contribute in predicting online marketing technology adoption readiness, identifies the drivers and barriers (both physical and psychological) to businesses to adopt online marketing technologies and constructs an online marketing technology adoption readiness framework from available literature. Non-probability sampling in the form of purposive sampling within the population was used to gather a sample of this population. A purposive sample of 103 respondents was selected for the quantitative research (questionnaires) and 7 for the qualitative research (semi-structured interview) based on the definition of the hospitality industry. Homogenous purposive non-probability sampling was used as it was anticipated that knowledgeable experts, i.e. owners, senior managers, directors and IT managers within the hospitality industry, i.e. guest houses, guest farms, lodges, and hotels, in the Cosmos area of Mpumalanga would provide reliable results. It was determined that 33% of respondents make use of the OMT enablers considered for this study and 50% of respondents make use of the OMTs. It is concluded that most of the digital technologies and OMTs are available to the respondents’ exposure, as well as the necessary infrastructure and that neither customer pressure, technology maturity, industry standardisation, nor geographical location are reasons that businesses will not invest in digital technologies or OMT’s. From the qualitative study respondents indicated that if customers do not make use of the technology, the hospitality businesses won’t either. Some barriers to technology adoption matched those from the literature study. A correlation study and linear regression was conducted between all listed constructs in the proposed OMT adoption readiness framework. To validate the proposed framework, a multiple regression was conducted to determine how the constructs collectively contribute in predicting OMT adoption readiness. The limitations and implications for further research are that results cannot be generalised to the broader hospitality industry in Mpumalanga or South Africa, owing to the use of a non-probability purposive sample. It is recommended that future studies focus on larger probability sample in order to be more representative of the population. The proposed OMT adoption readiness framework may still yield different results if tested on a larger probability sample under different conditions. It is, therefore, recommended that the originally proposed and amended frameworks be further tested and validated in order to use it as a prediction tool for OMT adoption readiness. The amended framework’s constructs can only be used to predict 24.52% of the variance in the OMT adoption readiness construct. Although this study finds that the respondents are 72% ready to adopt online technology, the amended framework could only predict 17% of that. It is, therefore, recommended that further research focus on the missing constructs which could help in predicting online technology readiness. It is clear that needs differ between small and very large hospitality businesses. It is recommended to test and interpret correlations between various constructs and conduct a factor analysis to potentially reduce the number of constructs which could help to predict OMT adoption readiness
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