Although tourists can now book trips directly using generative artificial intelligence (GenAI), it remains unclear whether the real-time travel information it provides is comprehensive and sufficiently trustworthy enough to make booking decisions. The present research addresses this gap by integrating media richness, trust transfer, and the value-based adoption model (VAM) to investigate the impact of varying levels of travel information richness (text-only, text-image, and text-image-audio) on the booking behaviors of tourists using GenAI such as ChatGPT. With data from 578 participants, we tested the proposed structural and configurational models using a multi-analytical approach. Our findings revealed that the three media richness levels yield both analogous and distinctive effects on tourist perceptions regarding benefits, costs, trust formation, and intentions in ChatGPT online travel booking. Specifically, the text-image group demonstrated the strongest links from media richness to trust in ChatGPT, perceived benefit to value, and ultimately value to increased booking intention. Our findings from configurational modeling confirm a significant opportunity to harness the power of AI-empowered platforms for online travel booking.
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