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Employees Behavioural Intentions Towards the Use of Artificial Intelligence on Sustainable Tourism
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Employees Behavioural Intentions Towards the Use of Artificial Intelligence on Sustainable Tourism
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Dissertation
Employees Behavioural Intentions Towards the Use of Artificial Intelligence on Sustainable Tourism
2024
Overview
The increased competition and need to provide sustainable tourism in tourism organisations has resulted in a rapid growth of the application of Artificial Intelligence. The study aimed to find employees' behavioural intentions about the usage of Artificial Intelligence in sustainable tourism. This study is essential in assessing in what way employees perceive the deployment of Artificial Intelligence in the work environment in South African cities. The research is based on the Unified Theory of Acceptance and Use of Technology, Diffusion of Innovation Theory, and the Theory of Planned Behaviour. The research's empirical goals aimed to assess the Unified Theory of Acceptance and Use of Technology perceptions on user and technology acceptability among employees in sustainable tourism businesses. Also, to determine the Diffusion of Innovation Theory on the structure of innovation use and discover acceptance patterns to foresee how individuals choose which innovations to implement. Finally, the Theory of Planned Behaviour investigated employee interest-based behaviour in terms of aim, activity, context, and time period while implementing Artificial Intelligence technologies. Data was collected from 353 participants whose tourism organisations have applied Artificial Intelligence. The Statistical Package for Social Science was utilised in the research to organise the information that was gathered. The findings of a descriptive analysis of behavioural intentions revealed that employees are optimistic about the application of Artificial Intelligence over future career growth and expect to utilise it more frequently at work. The relation of behavioural intentions and action was established utilising the Partial Least Squares Structural Equation Modelling technique. The Structural Equation Modelling evaluation found that behavioural intentions and use (β=0.906, p<0.001) have a substantial favourable effect on employees' adoption of Artificial Intelligence. The analysis yielded substantial outcomes that are dependable amid the theoretical foundations and examination on the topic. The findings point to a path for the deployment of Artificial Intelligence technologies in tourism businesses, with individuals as well as organisations focussing on achieving a balance between organisational training and enhanced skills. The study outcome serves as a guide for tourism organisations, to determine strategic decisions about the deployment of Artificial Intelligence technology in the workplace to achieve sustainability.
