基于UTAUT模型的老年人智能养老机器人采纳意愿及影响因素研究

Research on the Adoption Intention and Influencing Factors of Smart Elderly Care Robots Based on the UTAUT Model

摘要: 为探究老年人对智能养老机器人的采纳意愿及其关键影响因素，本研究在整合型技术接受与使用模型(UTAUT)基础上纳入风险感知变量，构建老年人采纳意愿研究模型。课题组于2025年10月至12月，采用随机抽样方法对广州、佛山、东莞三地的476名老年人进行问卷调查，后运用SPSS与Smart PLS 4.1软件进行描述性统计、信效度检验以及基于偏最小二乘法的结构方程模型分析。结果发现：绩效期望(β = 0.237, P < 0.001)、努力期望(β = 0.212, P < 0.001)、社会影响(β = 0.275, P < 0.001)和促成因素(β = 0.187, P < 0.001)均对采纳意愿产生直接且显著的正向影响，其中社会影响的总效应最大；风险感知的直接影响不显著(β = −0.021, P = 0.553)。此外，努力期望通过绩效期望对采纳意愿产生间接影响。模型对采纳意愿的解释力(R²)达到64.5%。研究结论表明：社会影响、绩效期望和努力期望是提升老年人采纳意愿的关键驱动因素。基于此，文章建议产品与服务供给方应从善用社会示范效应、优化产品实用功能、简化操作交互流程以及构建完善的支持体系等多方面协同发力，以有效提升老年群体对智能养老机器人的接受度和使用意愿。

Abstract: To explore the adoption intention of elderly people towards smart elderly care robots and their key influencing factors, this study incorporated risk perception variables based on the Integrated Technology Acceptance and Use Model (UTAUT) to construct a research model on the adoption intention of elderly people. The research group conducted a questionnaire survey on 476 elderly people in Guangzhou, Foshan, and Dongguan from October to December 2025 using a random sampling method. Descriptive statistics, reliability and validity tests, and structural equation modeling analysis based on partial least squares were conducted using SPSS and Smart PLS 4.1 software. The results showed that performance expectations (β = 0.237, P < 0.001), effort expectations (β = 0.212, P < 0.001), social influence (β = 0.275, P < 0.001), and facilitating factors (β = 0.187, P < 0.001) all had a direct and significant positive impact on adoption intention, with social influence having the greatest overall effect; The direct impact of risk perception is not significant (β = −0.021, P = 0.553). In addition, effort expectations can indirectly influence adoption intentions through performance expectations. The explanatory power (R²) of the model for adoption intention reached 64.5%. The research findings indicate that social influence, performance expectations, and effort expectations are key driving factors in enhancing the adoption intention of elderly people. Based on this, the article suggests that product and service providers should collaborate from multiple aspects, such as making good use of social demonstration effects, optimizing product practical functions, simplifying operational interaction processes, and building a sound support system, to effectively enhance the acceptance and willingness of elderly people to use smart elderly care robots.