An investigation into the acceptance of intelligent care systems: an extended technology acceptance model (TAM)

With the aging population trend becoming increasingly pronounced, the health issues of elderly individuals living alone have become a focal point of societal concern. This study aims to investigate guardians of the elderly's acceptance of intelligent care systems for the elderly. This system integrates millimeter-wave radar and image recognition technologies to monitor the health status of seniors in real time and automatically alert their children in emergency situations. To evaluate the market acceptance of this emerging technology, we employed a Covariance-Based Structural Equation Modeling (CB-SEM) approach and constructed an acceptance model for the intelligent care system. Survey data were collected from 386 respondents in China. The results indicate that users of this system are more concerned with task completion rather than ease of use. Enhancements in information trust significantly promote perceived usefulness (PU), perceived ease of use (PEOU), and behavioral intention to use (BI). Individuals with higher risk perception sensitivity exhibit greater perceptions of the system's usefulness and ease of use. Aesthetics emerged as a significant factor influencing PU, PEOU, and BI, second only to information trust. When the system is perceived as well-designed, it is also deemed acceptable. An aesthetically pleasing system is not only considered useful but also easier to use. Interestingly, opinions from social circles did not directly impact BI or PEOU. they only influenced perceived usefulness. Moreover, higher privacy security requirements correlate with lower perceptions of the system's usefulness. Overall, improvements in perceived usefulness, information trust, and aesthetics significantly enhance user acceptance of the system. These findings provide theoretical support for developing more appealing intelligent care systems for the elderly and contribute new perspectives on understanding the key factors driving the adoption of such systems. Additionally, they enrich and refine the knowledge base within the TAM framework.