This study aims to explore the antecedent factors affecting consumers’ intention to continue using artificial intelligence (AI) chatbots in pharmaceutical e-commerce. This study aims to provide a comprehensive understanding of how technical characteristics and user satisfaction influence continuance intention, offering insights for enhancing AI chatbot systems and customer service strategies.
This study adopts both online and offline data collection methods and uses structural equation modelling with AMOS 26.0 to investigate the factors influencing consumers’ continuance intention to use AI chatbots in the pharmaceutical e-commerce context. The research model integrates technical characteristics of AI chatbots, service expectation confirmation, emotional satisfaction, cognitive satisfaction and e-health literacy.
The results of this study indicate that perceived flexibility, accuracy, reliability and convenience of AI chatbots positively influence service expectation confirmation, while anthropomorphism does not have a significant impact. Both emotional and cognitive satisfaction positively influence consumers’ continuance intention. This study highlights the importance of optimizing AI chatbot systems to improve service efficiency and consumer satisfaction.
This study uniquely integrates the pharmaceutical e-commerce context into AI chatbots research, addressing an existing gap in context-specific studies. This study introduces a dual-dimensional satisfaction framework encompassing cognitive and emotional satisfaction, offering theoretical support for more holistic satisfaction enhancement strategies. The findings of this study also provide practical implications for companies seeking to establish and sustain long-term, stable customer relationships through advanced AI chatbot systems.
