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Determinants of artificial intelligence-assisted diagnostic system adoption intention: A behavioral reasoning theory perspective

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  • Li, Weixia
  • Wang, Jianguo

Abstract

Artificial intelligence-assisted diagnostic systems (AIADS) signify a significant medical revolution, reducing environmental burdens and enabling AI-based medical services to catalyze sustainability-oriented positive change. Because users demonstrate almost contradictory attitudes or resistance to adopting medical information provided by AIADS, controversy persists regarding the use of the technology. Based on behavioral reasoning theory (BRT), this study adds empirical insights into the significant influence of users' values (openness to change) toward reasons (for and against) and their intentions to adopt AIADS from the perspective of behavioral reasoning. A scenario questionnaire survey of 604 Chinese users demonstrated that openness to change significantly impacts users' attitudes and reasons (for and against) adopting AIADS. A dual pathway explains the reasons for and against adopting AIADS. The findings contribute to BRT's application in AI-assisted medical service and provide implications to practitioners that will increase users' adoption of AIADS.

Suggested Citation

  • Li, Weixia & Wang, Jianguo, 2024. "Determinants of artificial intelligence-assisted diagnostic system adoption intention: A behavioral reasoning theory perspective," Technology in Society, Elsevier, vol. 78(C).
    • Handle: RePEc:eee:teinso:v:78:y:2024:i:c:s0160791x2400191x
    DOI: 10.1016/j.techsoc.2024.102643
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    1. Zhong, Xi & She, Jianquan & Wu, Xiaojie, 2024. "Tech for social good: Artificial intelligence and workplace safety," Technology in Society, Elsevier, vol. 79(C).

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