Grounded in Relationship Marketing Theory, this study examines how artificial intelligence-powered chatbot communication quality (CCQ), including credibility, accuracy, and competence, influences consumer purchase intention through brand-related factors (brand loyalty, brand preference) and consumer–brand relationship variables (affective commitment, trust) in a developing market context. The study further evaluates the mediating roles of brand elements and consumer–brand relationships in this process.
The data were collected from 278 participants who had previous experience with chatbots. The collected survey data and the proposed research model were analyzed using partial least squares structural equation modeling, covariance-based structural equation modeling and a complementary structural equation modeling artificial neural network approach to assess both explanatory relationships and predictive robustness.
The results revealed the positive effect of CCQ on brand elements, specifically brand loyalty and brand preference, as well as on affective commitment and trust, two elements of the consumer–brand relationship. Moreover, brand elements and the consumer–brand relationship were found to positively influence consumers' purchase intentions. The study revealed the full mediating roles of brand elements and the consumer–brand relationship in the relationship between CCQ and purchase intention.
The study contributes to the literature and managerial practice by clarifying how artificial intelligence-powered chatbot communication quality shapes consumer responses in developing market contexts.
This study offers an integrated and theory-grounded framework that extends chatbot marketing research by demonstrating the central role of brand and relationship mechanisms in explaining consumer purchase intention in a developing market context.
