Beyond intention: gendered and tourist-type perceptions of post-GenAI-usage satisfaction
Kai Xin Tay, Khaslinda Akasyah Mujin, Jennifer Kim Lian Chan · International Journal of Tourism Cities · 2026
The present study examined generative artificial intelligence (GenAI) adoption intention’s impact on post-GenAI-usage tourist satisfaction (TS) in tourist cities, where tourists used GenAI for planning, navigation, and itinerary management. The stimulus–organism–response framework (S–O–R) was employed to investigate how the perceived usefulness (PU) and perceived trust-based risk (PTR) of post-GenAI-usage acted as cognitive stimuli, shaping tourists’ affective emotions (EMOs) towards GenAI (organism) to subsequently influence overall TS as the behavioural response. A structural equation modelling-based analysis of 858 tourists in Malaysia revealed that PU directly enhanced both EMOs and TS, while PTR only negatively influenced tourists’ EMOs post‑GenAI-usage, but did not directly affect TS. These results confirmed that in the S–O–R sequence, where EMO partially mediated the correlation between both stimuli (PU) and TS, tourist type (TT), be it domestic tourists (DTs) or international tourists (ITs), moderated these S–O–R framework pathways, whereas gender did not. This study contributes to urban tourism research by extending the S–O–R framework to explain how GenAI reshapes tourists’ EMOs towards the trip, thereby transforming TS outcomes in tourist cities, while also identifying TT as a key moderating factor. For tourism practitioners, AI developers, and policymakers, the findings underscore the need to prioritise GenAI’s functional utility over trust‑building alone, to tailor interfaces for DTs and ITs, and to embed GenAI tools into urban destination ecosystems to enhance real‑time visitor experiences.