How generative AI shapes eco-friendly accommodation choices

Purpose Despite the growing use of generative artificial intelligence (GenAI) in travel planning, limited research has examined how GenAI-related characteristics influence travelers’ eco-friendly accommodation choices. Guided by the “Stimulus–Organism–Response” framework, this study aims to examine how perceived interactivity, personalization, information accuracy, usefulness, currency and anthropomorphism shape trust in GenAI, environmental awareness and environmental attitude, which subsequently influence intention to choose eco-friendly accommodations. Design/methodology/approach Survey data from 371 Vietnamese leisure travelers with GenAI travel-planning experience were analyzed using partial least squares structural equation modeling and artificial neural networks (ANNs). Findings Perceived usefulness and currency influence trust, environmental awareness and environmental attitude, while other GenAI characteristics show more selective effects. All three psychological states positively influence eco-friendly accommodation intention. ANN identifies environmental attitude as the strongest predictor, followed by environmental awareness and trust. Need for cognition strengthens the awareness-intention relationship, while need for affect strengthens the attitude–intention relationship. Practical implications GenAI-supported travel systems should prioritize useful, current and credible sustainability information rather than rely primarily on personalization or human-like interaction. Sustainability communication can also be adapted to travelers’ cognitive and affective processing tendencies. Originality/value The study moves beyond GenAI adoption by showing that distinct GenAI characteristics influence sustainable accommodation choices through different psychological routes. It also identifies the conditions under which these internal states are more strongly translated into behavioral intention.