Doctoral student coauthors study on chatbot preference

Ms. Mei Xu, a student in the Doctor of Business Administration program, has recently had a co-authored paper published in the Journal of Global Information Management (JGIM), a peer-reviewed Quartile 2 journal.

Ms. Xu has been working as Research Assistant to Dr. Hongnai Zhang. One of Dr. Zhang’s colleagues at another university reached out to him about collecting data from U.S. consumers to strengthen research on consumer behavior in healthcare. Dr. Zhang saw this as an excellent opportunity for Ms. Xu to further develop her research skills, so he introduced her to his colleagues to assist with the data collection effort.

Ms. Xu performed exceptionally well, contributing significantly to the questionnaire design, survey administration, and data collection. Owing to her outstanding performance and professionalism throughout the process, she was invited to join the paper as a co-author.

The published study, Consumer Service Agent and Patient Adoption Intention: Recommendations From Chatbot or Human, provides insights on how patients decide whether to trust recommendations from a human agent or an AI chatbot when seeking care recommendations.

• The researchers found that patients with severe conditions were significantly more likely to trust and accept recommendations from human agents. Those with minor, common ailments on average were as likely to accept advice from a chatbot as from a human.
• For both human and AI agents, communicating specifically about the patient’s condition rather than in general terms increased trust.
• The study results suggest adopting a triage model: patients can interact with chatbots first. If the patient’s disease severity is low, the chatbot can provide the doctor recommendation. If disease severity is assessed as high, the system can route the interaction to a human customer service agent. Both human agents and AI chatbots should be trained to use concrete, specific language when communicating with patients.
• AI agents are not a replacement for human agents, but a tool to manage high-volume, low-stakes interactions while preserving human resources for more complex, high-stakes consultations.

Congratulations to Ms. Mei Xu on her publication!

Han, Z., Du, G., & Xu, M. (2025). Consumer Service Agent and Patient Adoption Intention: Recommendations From Chatbot or Human. Journal of Global Information Management (JGIM), 33(1), 1-37. https://doi.org/10.4018/JGIM.391506