The impact of AI chatbot service quality on consumer purchase intention: the cognitive and affective mediating mechanisms

Abstract

The increasing prevalence of artificial intelligence chatbots in e-commerce raises questions about how the service quality dimensions of AI chatbots may influence consumer purchase intentions. Drawing on Expectation-Confirmation Theory, the Information Systems Success Model, and the Technology Acceptance Model, this study proposes a conceptual framework to examine these relationships. Survey data were collected from 493 Chinese consumers with prior experience using AI chatbots. The study examined perceived personalization, social presence, information quality, and human-AI service continuity as possible antecedents of purchase intention. Perceived usefulness and satisfaction were treated as mediating variables. Partial least squares structural equation modeling was used for the analysis with 5,000 bootstrapped resamples. Perceived personalization, social presence, information quality, and human-AI service continuity were associated with perceived usefulness. Additionally, perceived personalization, information quality, and human-AI service continuity were positively associated with satisfaction. Conversely, social presence did not show a significant direct effect on satisfaction. Both perceived usefulness and satisfaction are linked to purchase intention, with satisfaction having a stronger direct connection. The mediation analysis revealed that perceived usefulness and satisfaction mediate the relationship between AI chatbot service quality and purchase intention. The only exception was the indirect effect of social presence through satisfaction, which was not statistically significant. This study seeks to contribute to understanding how the service quality of AI chatbots influences consumers’ purchase intentions through perceived usefulness and satisfaction. The results indicate that information quality is the most significant among the service quality dimensions in AI-mediated interactions. The lack of a significant direct impact of social presence on satisfaction suggests that, in utilitarian-oriented e-commerce environments, consumers are more likely to prioritize functional service features over social–emotional factors when assessing AI chatbot services. These findings may inform e-commerce practitioners seeking to improve AI-driven customer service by emphasizing information accuracy and completeness, enhancing personalization, and fostering seamless human-AI service continuity to drive purchase conversions.