Modelling The Mediation Effect Of Management Support On The Relationship Between AI Adoption Innovation Dimensions And AI Implementation In The UAE Tourism Sector

Abstract

Objective: This study aims to develop an empirical framework of the mediation effect of management support on the relationship between AI adoption innovation dimensions and the successful implementation of AI technologies within the UAE tourism sector

Research Method: Data to validate the theoretical framework was collected from 370 employees of the Dubai Tourism Authority using purposive sampling. The validation process employed SmartPLS software, utilizing PLS-SEM techniques to examine relationships between variables. PLS-SEM is particularly well-suited for validating theoretical models and ensuring analytical robustness in developing the empirical framework

Findings: The empirical framework indicates that Management Support significantly enhances AI adoption by amplifying the impact of Compatibility, Relative Advantage, and Trialability, while Low Complexity has an insignificant indirect effect. Additionally, the direct effects of these innovation dimensions on AI adoption vary in strength. This framework has several practical applications. From a strategic AI implementation perspective, organizations can prioritize AI innovations that demonstrate strong direct and indirect influences on adoption, particularly focusing on Compatibility and Relative Advantage

Originality: Through applying this framework, tourism businesses and policymakers can develop optimized AI adoption strategies, ultimately improving efficiency, customer experiences, and overall industry competitiveness