Consumer Service Agent and Patient Adoption Intention: Recommendations From Chatbot or Human

Chatbots have been used in consumer-facing applications, and their effectiveness in e-commerce has been widely analyzed. However, their role in online healthcare communities has not been fully explored. Unlike recommending products on e-commerce platforms, customer service agents (CSAs) in online healthcare communities aim to recommend suitable doctors, which is closely related to patient health. This study aimed to understand the differences in patients’ intention to adopt recommendations provided by different types of CSA. The results showed that patients with high-severity diseases were more likely to accept recommendations from humans. When CSAs used concrete language, patients were more likely to adopt chatbot recommendations with the mediating effect of confirmation. Regardless of the language style used by CSAs, patients with high-severity diseases were more likely to adopt recommendations from humans, with the mediating effect of perceived trust. These findings can provide managers with insights into how and why CSAs’ characteristics enhance patient adoption intentions.