Exploring user perceptions of customer-centricity in chatbot interactions: a multi-method study in the healthcare sector

The advent and integration of technology have reshaped the interaction between customers and service providers across the customer journey. In the healthcare sector, chatbots are increasingly being adopted by service providers. Despite their growing usage, the perceived effectiveness of these tools depends on how users evaluate their customer-centricity. This paper investigates the user perceptions of customer-centricity in chatbot interactions. The study focuses on the healthcare sector.

An exploratory sequential multi-method approach was adopted, combining Grounded Theory and Total Interpretive Structural Modelling for this study.

The findings identify that perceived customer-centricity and customer satisfaction are driven by factors like digital empathy, trust, anthropomorphism, perceived usefulness, perceived control and perceived ease of use. The findings will help healthcare providers in designing more human-centric and emotionally intelligent chatbot systems.

The study contributes to the understanding of AI-mediated healthcare interactions by highlighting different aspects of chatbot experiences and their structural influence on customer-centricity.