Huang, Chin YuanChin YuanHuangMING-CHIN YANGHuang, Chin YuChin YuHuang2022-01-072022-01-072021-05-0109731318https://scholars.lib.ntu.edu.tw/handle/123456789/591882The research of mobile health (mHealth) application interventions has attracted considerable attention among researchers. The convenience and ubiquity of smartphones makes them an ideal vehicle by which to use mHealth APPs for the self-monitoring of one's health throughout the day. This study utilized the tenets of the extended unified theory of acceptance and use of technology (UTAUT2) as our theoretical foundation. We also considered innovativeness and network externality in seeking to investigate the determinants of one's intention to adopt a chatbot for health and weight management. The health chatbot running on the LineTM APP platform features artificial intelligence (AI) technology to facilitate accurate analysis and health consultations in near real-time. In the analysis of 415 responses, the proposed model explained 87.1% of variance in behavioral intention. Habit was the independent variable with the strongest performance in predicting user intention, followed by performance expectancy, social influence, network externality, and innovativeness. Social influence affects user intention through performance expectancy. This study provides academics and APP developers with insight into the primary determinants of user attitudes toward the adoption of an AI-powered health chatbot.enArtificial intelligence | Chatbot | Innovativeness | MHealth | Network externality | UTAUT2journal article10.23940/ijpe.21.05.p2.4224322-s2.0-85106569670https://api.elsevier.com/content/abstract/scopus_id/85106569670