When artificial intelligence meets performances The performances model of tourism destinations powered by artificial intelligence Politeknik Negeri Bandung Abstract The massive adoption of artificial intelligence (AI) has occurred after the COVID-19 pandemic, currently, AI is still being used. However, research analysing the impact of using AI on tourism destinations is still limited. Therefore, this study aims to find the effect of AI adoption on managerial performance and destination performance by integrating the human-organization-technology fit (HOT-fit) model and the technology-organization-environment (TOE) model. The data were gathered through a survey of 105 tourist destination managers who used AI and evaluated through the structural equation model-partial least squares (SEM-PLS) and essential performance map analysis (IPMA). By using SEM-PLS and IPMA, the findings of this study reveal that human, organisational, technological and environmental factors are essential factors influencing managerial and destination performance. This study encourages tourist destination managers to improve performances by utilising AI effectively, ensuring compatibility between humans, organisations, technology and the environment. The application of AI integrated with the HOT-fit and TOE models will help tourist destinations be more responsive to environmental and technological changes that improve destination performance. This study offers a new perspective into the theory and applications of the HOT-fit and TOE models in explaining managerial performance and destination performance in the context of AI in the tourism industry. Keywords: Artificial intelligence, Human-organization-technology fit model, Technology-organization-environment model, Managerial performance, Destination performance Topic: Artificial Intelligence (AI) |
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