Abstract

Purpose: This study examines the influence of support quality in airline and distribution sector chatbot services on customer satisfaction and usage intention. As AI-powered chatbots become essential in these industries’ customer service landscape, understanding how different types of support affect user behavior is important. Research design, data and methodology: The research conceptualizes support quality in two dimensions: emotional support and informational support. A structural equation modeling (SEM) approach was employed to test four hypotheses. Data were collected through a survey of airline chatbot users in Korea, resulting in 368 valid responses. Confirmatory factor analysis and model fit indices were used to validate the measurement and structural models. Results: Both emotional and informational support showed statistically significant positive effects on customer satisfaction and continued usage intention. Informational support had a slightly stronger influence on continued usage. The explanatory power (R²) of support quality on customer satisfaction and continued usage intention was 37.7% and 48.3%, respectively. Conclusions: This study highlights the importance of enhancing both emotional and informational dimensions of chatbot service quality. Practical implications suggest that airlines and distribution firms should design chatbot systems capable of not only providing accurate information but also responding with empathy to strengthen long-term customer engagement.