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Guerrero Diaz, Brandy (2025) Exploring Customer Trust and Satisfaction in AI Chatbot Interactions on Amazon Marketplace Case in Ireland. Masters thesis, Dublin, National College of Ireland.
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Abstract
Background: This research examined customer trust and satisfaction in AI chatbot interactions within Amazon Marketplace Ireland, aiming to extend understanding of both functional and emotional dimensions of user experience. Specially, the research explored how attribute such as competence, empathy, fairness, and transparency shape trust and satisfaction, and whether trust serves as a mediator between chatbot attribute and overall customer satisfaction.
Methods: A cross-sectional online survey was conducted with Amazon Marketplace Ireland users (final analytic sample n=42, after excluding non-users of chatbot system). Multi-item scales measured constructs of trust and satisfaction, while single-item measures captured privacy concerns and fairness perceptions. Descriptive statistics, correlation analysis, and regressions based in mediation model were employed to test hypotheses.
Results: Findings revealed that fairness perceptions significantly predicted customer trust, while empathy and transparency played a weaker but notable role. Trust was positively associated with satisfaction and partially mediated the relationship between chatbot attributes and satisfaction. However, the relatively small sample size limited statistical power, especially in categories such as complaint and returns.
Conclusion: The study highlights that customer trust is fragile yet essential in chatbot interactions, with competence and fairness emerging as key drivers in the Irish Amazon Marketplace context. These insights contribute to the growing literature on AI customer service by showing how platforms dynamics shape trust and satisfaction, offering implications for both theory and practice in relational marketing.
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