Int J Performability Eng ›› 2022, Vol. 18 ›› Issue (5): 338-349.doi: 10.23940/ijpe.22.05.p4.338349

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Modeling Consumer Adoption Intention of an AI-Powered Health Chatbot in Taiwan: An Empirical Perspective

Chin-Yuan Huanga,*, Ming-Chin Yanga, I-Ming Chenb,c, and Wen-Chang Hsud   

  1. aInstitute of Health Policy and Management, National Taiwan University, Taipei, Taiwan;
    bDepartment of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan;
    cDepartment of Psychiatry, National Taiwan University Medical College, Taipei, Taiwan;
    dDepartment of Gastrointestinal Surgery, Taipei City Hospital Renai Branch, Taipei, Taiwan
  • Submitted on ; Revised on ; Accepted on
  • Contact: * E-mail address:

Abstract: The research of mobile health application interventions has attracted much interest from practitioners and scholars. There is a relative paucity of research investigating the factors influencing consumers to use a health chatbot for weight and health management. This study utilized the extended unified theory of acceptance and use of technology (UTAUT2) model as the theoretical basis and extended it with personal innovativeness and network externality to investigate the predominant factors affecting one’s intention to use a health chatbot. Materials and Methods: An online survey was carried out for people aged≥20 years throughout Taiwan from 23 November to 30 December, 2019. Structural equation modeling (SEM) was used to test the hypotheses. Results: In total, 415 responses were analyzed. Our proposed model explained 87.1% of the variance in behavioral intention. Among eight factors, five of the factors were found to be the significant predictors of intention to use a health chatbot. Gender and experience were seen to exert a moderating effect on some of the relationships hypothesized in our research model, whereas education, chronic conditions, BMI, and age did not play a significant role. This study provides academics, health professionals, and practitioners with insights into the factors influencing the acceptance and use of a health chatbot. In the future, researchers could extend the model to investigate the effects of user intention on actual use behavior.

Key words: mobile health, UTAUT2 model, chatbot, network externality, personal innovativeness