Chatting vs clicking: how does AI interaction style affect travel decisions? a comparative study of generative AI and GUI-based platform

Purpose The purpose of this study is to examine travelers’ attitudes and intentions toward Artificial Intelligence (AI)-based travel planning assistants through an integrated task-technology fit, Technology Acceptance Model and Innovation Diffusion Theory framework, comparing generative AI and graphical user interfaces (GUI) platforms. Design/methodology/approach The survey data were collected from 355 generative AI and 268 GUI platform users. SEM tested relationships among constructs, and multi-group analysis compared the two groups. Findings The results of this study revealed that all variables except perceived ease of use and complexity positively influenced attitudes, which enhanced efficacy and intention to use. Perceived usefulness and compatibility showed consistent effects across both groups. Originality/value This study contributes to the literature by validating task-technology fit, Technology Acceptance Model and Innovation Diffusion Theory integration in tourism and first comparing two AI-TPA types, offering implications for design and promotion.