| dc.description.abstract | Conversational artificial intelligence agents or chatbots have transformational potential to automate service delivery. This potential has resulted in increasing interest in customer service applications while studies of chatbots in healthcare have been more limited. Chatbots can immediately advise users on medical issues in the form of a ‘pocket doctor’, therefore raising significant questions about the dynamics of these interactions in relation to traditional healthcare services. The research presented in this thesis integrates various theoretical perspectives to advance our knowledge of how users interact with healthcare chatbots. The aim is to examine how users perceive the promise of healthcare chatbots and how this promise can be translated into sustained engagement and positive outcomes. The empirical part is based on three survey studies with chatbot users in China. This thesis aims to make several contributions to information systems research. First, it extends our understanding of the transition process from human-led healthcare services to AI technologies and how user resistance will influence switching behaviours and continuous use intentions. Second, the research sheds light on the unique proposition of healthcare chatbots to provide emotional support in empowering users in health management and chatbots’ potential to establish a human-like social presence in medical advice interactions. It concludes that these aspects matter more than simply providing information to users and affect user perceptions of the outcomes of their interaction. Third, the research identifies two pathways through which user interest in chatbots can be sustained: establishing a feeling of empowerment from a psychological point of view and confirming satisfactory service quality outcomes. From a practical point of view, apart from offering personalised services and well-explained service boundaries, the thesis further suggests that developers should follow a participatory design principle that involves users, developers, and doctors in the development process, with a particular focus on improving the information quality, content richness, and the ability to convey emotional support. The results also highlight the importance of developing empathetic conversational AI interactions by improving the sociability of conversational agents. | en_US |
