Understanding Consumer Intention to Adopt AI Chatbots in Saudi Tourism: A conceptual Framework

HRMARS - Purpose: This research investigates the determinants influencing travelers’ intention to adopt and use AI-driven chatbots in tourism planning and decision-making. Despite the growing integration of artificial intelligence (AI) in the tourism and hospitality industry, scholarly research on chatbot applications remains limited. This study aims to bridge this theoretical and empirical gap by examining how personal innovativeness moderates the relationships between perceived behavioral control, attitude, initial trust, and subjective norm toward the intention to use AI chatbots for travel planning. Methodology - Design-based approach: The study integrates the Diffusion of Innovation (DOI) theory and the Theory of Planned Behaviour (TPB), incorporating key constructs indirectly linked to the Technology Acceptance Model (TAM). A quantitative, cross-sectional design will be employed, and data will be collected through purposive sampling targeting individuals with digital travel experience. Fourteen hypotheses will be tested using structural equation modeling (SEM) to validate the proposed framework. Findings: The anticipated findings are expected to demonstrate that perceived behavioral control, attitude, initial trust, and subjective norm significantly influence the intention to use AI chatbots, with personal innovativeness serving as a crucial moderating factor. These results will contribute to extending existing technology adoption theories to the tourism context. Research limitations- implications: The study may be limited by its reliance on self-reported data, potential sampling bias, and the cross-sectional design, which restricts causal inference. Future research should consider longitudinal approaches, larger and more diverse samples, and inclusion of variables such as perceived enjoyment or anthropomorphism of AI chatbots to enhance model robustness. Practical implications: Findings from this study will guide tourism practitioners and stakeholders in developing effective strategies to promote AI-driven chatbot adoption. Enhancing user trust, personalization, and perceived usefulness will be key to improving digital travel experiences and operational efficiency within the tourism sector. Originality-value: This study is among the first to develop and empirically test an integrated model combining DOI,TPB, and TAM to explain the adoption of AI chatbots in tourism. It contributes novel theoretical insights and practical guidance for leveraging smart technologies to enhance the digital travel experience.