用户对人工智能绘画应用程序的持续意图:扩展期望确认模型
Xiaofan Yu1, Yi Yang2, Shuang Li1
1Postdoctoral Research Station, Central Academy of Fine Arts, Beijing, China.
PloS one
|May 15, 2024
概括
这项研究探讨了用户对人工智能绘画应用程序的意图,发现确认,满意度和社会影响是关键驱动因素. 习惯可以减少社会影响对持续使用AI绘画工具的影响.
科学领域:
- 人与计算机的交互
- 人工智能应用程序 人工智能应用程序
- 数字艺术技术 数字艺术技术
背景情况:
- 人工智能 (AI) 绘画是一种快速发展的技术.
- 了解用户采用和持续使用AI绘画应用程序对于开发至关重要.
研究的目的:
- 实证地调查用户对AI绘画应用程序的持续意图.
- 扩展现有的技术接受模型 (ECM,TAM,UTAUT) 和 AI 绘画背景的流理论.
主要方法:
- 提出了一个综合多种理论的综合研究模型.
- 通过调查问卷收集了443名拥有AI绘画经验的用户的数据.
- 使用结构方程建模测试的假设.
主要成果:
- 确认显著预测了满意度和社会影响.
- 个人创新能力影响了确认.
- 满意度,流体验和社会影响力积极预测意图;社会影响力有最大的影响.
- 感知到的有用性,享受和业绩预期并没有显著影响意图.
- 习惯负面地调节了社会影响和持续的意图之间的关系.
结论:
- 用户确认,满意度和社会影响对于持续使用AI绘画应用程序至关重要.
- 个人创新能力影响了最初的确认.
- 习惯可以减少社会影响对持续使用的影响.
- 结果为AI绘画利用和开发策略提供了洞察力.
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