| dc.description.abstract | Generative AI chatbot is a highly disruptive innovation with significant commercial potential. The rise of generative chatbots has introduced new expectations and challenges regarding human-computer interaction. Consequently, generative AI has become a popular topic for discussion and research. However, there is still a lack of quantitative research on user attitudes and perceptions toward generative AI chatbots. This study conducts empirical research to explore the impact of anthropomorphic design in generative AI chatbots on users′ willingness to interact. Based on Force Field Theory, the study examines the driving factors such as the anthropomorphic characteristics of generative AI chatbot (empathy, adaptability, perceived warmth) and the restraining factors (communication delay, perceived coldness) on perceived communication quality (accuracy, credibility, competence), user likability, and willingness to interact. It also investigates the moderating effect of privacy concerns in this context. The research methodology is divided into two parts. The first part aims to understand the public′s experience with generative AI, while the second part uses situational experiments to understand the impact of chatbot communication styles for marketing and entertainment purposes on user attitudes. Both parts employ questionnaire surveys, with the collected data analyzed using structural equation modeling. The results indicate that empathy, adaptability, and perceived warmth positively influence consumers′ perceived communication quality with chatbots, whereas communication delay and perceived coldness have negative effects. Overall, higher perceived communication quality leads to increased user likability and greater willingness to interact with the chatbot. Although privacy concerns did not moderate the proposed model, the findings revealed a certain degree of privacy paradox.
This study provides new insights into the anthropomorphic characteristics of generative AI chatbots and their effects on users. It offers practical guidance for businesses using generative AI chatbots for branding and customer service, and provides theoretical and practical recommendations for future researchers and developers. | en_US |