AI-driven competitive advantage model in tourism: integrating model of HOTE model and performances model (HOTE-P adoption model)

Purpose This study aims to discover the competitive advantage of tourist destinations that adopted artificial intelligence (AI) by integrating the human–organisation–technology–environment (HOTE) model and performance model. Design/methodology/approach The data were collected via a survey of 136 tourist destination managers who used AI and analysed using the structural equation modelling-partial least squares and importance performance map analysis. Findings This study’s findings demonstrate that human, organisational, technological and environmental factors are crucial determinants in AI adoption, influencing managerial performance, destination performance and social performance. These three performance aspects confirmed their influence on competitive advantage. Practical implications Practically, this study encourages the tourism industry to increase the adoption of AI in tourism destination management, thereby improving performance and competitive advantage. Through this study, destination marketing managers, governments and others concerned with the tourism industry’s future development can create effective ways to increase the adoption of AI in this industry. Originality/value To the best of the authors’ knowledge, this study is the first to empirically use the HOTE model and performance model in analysing the competitive advantage of tourist destinations.