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Quantitative study reveals how generative AI improves travel outcomes by managing information overload and cognitive challenges.
This study examines how generative artificial intelligence (GenAI) optimizes travel planning by moderating information complexity and cognitive load. A quantitative approach with a formative–reflective modeling framework was applied to data from 1,242 respondents who experienced e-travel services. Results show that high information complexity increases cognitive load, negatively affecting travel outcomes, including personalization, logistical efficiency, financial management, and sustainable decision-making. GenAI mitigates these cognitive challenges, enhancing user satisfaction, trust, and adoption while supporting operational efficiency and AI-driven marketing insights. By integrating cognitive, technological, and behavioral perspectives, this study offers theoretical and practical contributions, guiding the design of AI-enabled travel systems and advancing knowledge on smart travel decision-making. These empirical findings expand existing knowledge by highlighting the potential of GenAI to transform traveler experiences and optimize tourism operations.
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Shehawy et al. (2026) studied this question.
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