Liu Jing, Wang Xingang, Zhang Jiaqi
College of Mechanical and Electrical Engineering, Guangdong University of Petrochemical Technology, Maoming 525000, China.
Department of Industrial Art, Graduate School of System Design, Tokyo Metropolitan University, Tokyo 1910065, Japan.
Behav Sci (Basel). 2025 May 18;15(5):697. doi: 10.3390/bs15050697.
The emergence of AI companion robots is transforming the landscape of elderly care, offering numerous conveniences to senior citizens when their children are not around. This trend is particularly pertinent in ageing societies such as China. Against this backdrop, the present study aims to explore the acceptance of AI companion robots among the elderly from a user-centric perspective. By leveraging insights from existing studies in the literature, we identified three individual characteristic variables-technology optimism, innovativeness, and familiarity-to extend the Artificial Intelligence Device Use Acceptance (AIDUA) model. Subsequently, we developed a conceptual model which was empirically tested through structural equation modelling (SEM) analysis. Our dataset comprised responses from 452 elderly individuals in China. The results revealed that technology optimism and innovativeness were positively associated with performance expectancy and effort expectancy, whereas familiarity inversely predicted perceived risk. Furthermore, emotion was found to be positively influenced by performance expectancy and effort expectancy but negatively impacted by perceived risk. This research extends the AIDUA model within the context of AI companion robots by integrating individual characteristic variables. These findings offer valuable insights for the design and development of companion robots and enrich the domain of Human-Robot Interaction (HRI).
人工智能陪伴机器人的出现正在改变老年护理的格局，在子女不在身边时为老年人提供了诸多便利。这一趋势在中国等老龄化社会尤为显著。在此背景下，本研究旨在从以用户为中心的角度探讨老年人对人工智能陪伴机器人的接受度。通过借鉴文献中现有研究的见解，我们确定了三个个体特征变量——技术乐观主义、创新性和熟悉度，以扩展人工智能设备使用接受度（AIDUA）模型。随后，我们开发了一个概念模型，并通过结构方程建模（SEM）分析进行了实证检验。我们的数据集包含来自中国452位老年人的回复。结果显示，技术乐观主义和创新性与绩效期望和努力期望呈正相关，而熟悉度则反向预测感知风险。此外，情感被发现受到绩效期望和努力期望的积极影响，但受到感知风险的消极影响。本研究通过整合个体特征变量，在人工智能陪伴机器人的背景下扩展了AIDUA模型。这些发现为陪伴机器人的设计和开发提供了有价值的见解，并丰富了人机交互（HRI）领域。
