Chatbots in Healthcare – The Effects of Affective and Cognitive Empathy on the User’s Satisfaction with, Trust in, and Loyalty to the Service
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2021-06-25
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en
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The present thesis aims to contribute to the important research field of empathy in text-based chatbots, which are increasingly used as service agents and therapeutical advisers in healthcare. In particular, the thesis examines the effects no empathy vs. empathy, as well as affective vs. cognitive empathy by a healthcare chatbot on the user’s satisfaction with, trust in, and loyalty to service, while comparing it to a regular human-to-human interaction. This is done by conducting quantitative research in the form of an experiment with a 2x3 between-subject design (N=197). While it could not be confirmed that general empathy in a chatbot automatically results in more user satisfaction, trust, or loyalty, the strongly differing effects of affective and cognitive empathy in chatbots and humans became clear. A chatbot provides a significantly more pleasant user experience with cognitive empathy. In contrast, a human healthcare adviser is more appreciated when affective empathy is shown. A reason for this could lie in the different expectations that are placed on a chatbot compared to a human. Chatbots are not necessarily expected to have the ability to feel emotions, making their attempt to show affective empathy seem fake and not genuine.
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Faculteit der Managementwetenschappen