Chatbot Anthropomorphism and Its Influence on Trust and Satisfaction via Perceived Value

Abstract

This study explores how chatbot user's perceptions about it’s competence, ease of use, and usefulness contribute to the value they assign to the interaction and how this value shapes trust and, ultimately, satisfaction. It also considers whether anthropomorphic design features, that make a chatbot seem more human, can strengthen the link between value and trust. A survey of university students (n = 233), all with previous chatbot experience, was analyzed using Partial Least Squares Structural Equation Modeling. The findings suggest that the three antecedents meaningfully influence perceived value, which then predicts both trust and satisfaction. Notably, anthropomorphism enhances the effect of perceived value on trust. The model shows acceptable explanatory strength for all endogenous constructs. By blending the Technology Acceptance Model with psychological insights and design elements such as anthropomorphism, the study contributes to a more layered understanding of chatbot evaluation. The research extends both Self-Determination Theory and Social Response Theory into chatbot contexts. Practically, the results imply that building chatbots that are not only functional and easy to use but also subtly human-like can improve user trust and satisfaction over time.