From conversation to green intention: how perceived AI chatbot empathy shapes sustainable travel

Abstract

Recent developments in artificial intelligence (AI) have expanded the role of conversational agents in hospitality and travel service encounters. However, it remains unclear how the conversational characteristics of AI become psychologically meaningful and relate to travelers’ sustainable decision-making. Drawing on Cognitive Appraisal Theory (CAT), this study examines the associations between Chatbot Conversational Quality (CCQ) and Green Travel Intention (GTI) through the sequential roles of Perceived Chatbot Empathy (PCE) and Green Travel Motivation (GTM), while considering Eco-Friendly Customer Innovativeness (EFCI) as a boundary condition. Survey data from 400 travelers show that CCQ is associated with PCE, which in turn is associated with stronger GTM and, subsequently, higher GTI. EFCI strengthens the PCE-GTM relationship but does not significantly moderate GTM-GTI, suggesting greater relevance during motivation formation than motivation-to-intention translation. The findings show how conversational AI interactions can acquire socio-emotional meaning in hospitality contexts and highlight customer heterogeneity in sustainability-related decisions.