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<p>With the rapid development of artificial intelligence technology, AI assistants are gradually penetrating daily life and work. However, the internal mechanism of their user acceptance still needs to be further explored. Therefore, this study is based on the Technology Acceptance Model (TAM), introducing three external variables, Aesthetic Pleasure (AP), Information Quality (IQ), and AI Skills (AIS), to construct an extended model to explore the acceptance of AI assistants by Chinese users and its influencing factors. The results showed that aesthetic pleasure, information quality, and AI skills significantly affect perceived usefulness and ease of use by analyzing questionnaire survey data from 363 Chinese users and using structural equation modeling (CB-SEM) to validate hypotheses. AI skills, perceived usefulness, and perceived ease of use significantly affect behavioral intention. Notably, aesthetic pleasure and information quality do not affect behavioral intention. This study provides theoretical support for the design of AI assistants, helping designers and developers understand users’ needs and preferences to better design AI assistants.</p>

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Survey on Chinese users’ acceptance of AI assistants: expanding technology acceptance model

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年9月29日

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  • Wei Wang,
  • Yifan Lu

摘要

With the rapid development of artificial intelligence technology, AI assistants are gradually penetrating daily life and work. However, the internal mechanism of their user acceptance still needs to be further explored. Therefore, this study is based on the Technology Acceptance Model (TAM), introducing three external variables, Aesthetic Pleasure (AP), Information Quality (IQ), and AI Skills (AIS), to construct an extended model to explore the acceptance of AI assistants by Chinese users and its influencing factors. The results showed that aesthetic pleasure, information quality, and AI skills significantly affect perceived usefulness and ease of use by analyzing questionnaire survey data from 363 Chinese users and using structural equation modeling (CB-SEM) to validate hypotheses. AI skills, perceived usefulness, and perceived ease of use significantly affect behavioral intention. Notably, aesthetic pleasure and information quality do not affect behavioral intention. This study provides theoretical support for the design of AI assistants, helping designers and developers understand users’ needs and preferences to better design AI assistants.