互联网 + 智慧养老服务使用意愿的形成机制研究——基于TAM-VAM整合模型与安徽省老年群体的实证分析

The Formation Mechanism of Usage Intention toward Internet-Enabled Smart Elderly Care Services—An Empirical Study Based on an Integrated TAM-VAM Model and Older Adults in Anhui Province

摘要: 在我国人口老龄化加速与“互联网 + 养老”政策持续推进的背景下，智慧养老服务成为提升养老服务质量的重要途径，但老年群体的实际使用意愿仍然偏低。现有研究多基于技术接受模型(TAM)，对感知风险等负向因素及感知价值的中介作用关注不足，且区域实证研究相对有限。基于此，本文融合技术接受模型(TAM)与感知价值理论(VAM)，构建包含感知风险、感知有用性、感知易用性、感知价值与使用意愿的理论模型，并以安徽省智慧养老服务使用人群为研究对象，通过问卷调查获得962份有效样本，采用验证性因子分析(CFA)、结构方程模型(SEM)和K-means聚类分析进行实证检验。结果表明，感知风险对感知价值和使用意愿具有显著负向影响，感知有用性和感知易用性对感知价值产生显著正向作用，感知价值显著促进使用意愿，并在相关变量与使用意愿之间发挥部分中介作用。进一步将样本划分为“积极接纳型”“易用优先型”“风险顾虑型”和“观望犹豫型”四类用户群体。研究结论为智慧养老服务的精准推广与优化提供了实证依据。

Abstract: Against the backdrop of accelerated population aging in China and the continuous advancement of the “Internet Plus Elderly Care” policy, smart elderly care services have become an important approach to improving the quality of elderly care, yet older adults’ actual willingness to use such services remains relatively low. Existing studies are mainly based on the Technology Acceptance Model (TAM) and pay limited attention to the effects of negative factors such as perceived risk and the mediating role of perceived value, while region-specific empirical evidence is still insufficient. To address these gaps, this study integrates the Technology Acceptance Model (TAM) and the Value-based Adoption Model (VAM) to construct a theoretical framework incorporating perceived risk, perceived usefulness, perceived ease of use, perceived value, and usage intention. Using survey data from users of smart elderly care services in Anhui Province (962 valid questionnaires), confirmatory factor analysis (CFA), structural equation modeling (SEM), and K-means clustering were employed for empirical testing. The results indicate that perceived risk has a significant negative effect on both perceived value and usage intention, while perceived usefulness and perceived ease of use have significant positive effects on perceived value. Perceived value significantly promotes usage intention and partially mediates the relationships between other variables and usage intention. Furthermore, four user segments—active adopters, ease-of-use-oriented users, risk-concerned users, and hesitant observers—are identified. These findings provide empirical evidence for the targeted promotion and optimization of smart elderly care services.