The digital transformation of housing: A demography-sensitive scenario-based model of smart home acceptance for aging in place

Abstract

This study explores older adults' acceptance of IoT-based smart home systems using an extended Technology Acceptance Model (TAM) that incorporates trust alongside perceived ease of use (PEOU), perceived usefulness (PU), attitude toward use (ATU), and behavioral intention (BI). Data were collected from 166 older adults via visually enriched, scenario-based surveys tailored to enhance engagement and contextual comprehension. Structural Equation Modeling (SEM) and Multi-group SEM (MG-SEM) techniques were applied to examine both the general model structure and demographic moderating effects. Results reveal that trust is the most influential predictor of both PU and ATU, underscoring its central role in gerontechnological smart home acceptance decisions among older adults. PU significantly predicts ATU, which in turn strongly influences BI. While PEOU has no direct effect on ATU, it exerts a meaningful indirect effect on BI through PU and ATU. These patterns support the relevance of indirect usability pathways in technology acceptance. MG-SEM analyses highlight significant differences across demographic groups. Rural users show heightened sensitivity to ease of PEOU, whereas urban users display stronger trust-based pathways toward PU and BI. Younger elderly individuals are more influenced by ATU in forming BI, while older users associate PU and trust indicators with emotional and cognitive reassurance. Education and living environment also moderate several paths, confirming the need to consider contextual diversity in technology acceptance. This study contributes by extending TAM with trust, using scenario-based survey design, and integrating MG-SEM analyses to capture demographic and contextual variations. Findings emphasize the importance of personalized digital aging strategies and trust-based mechanisms for shaping older adults' technology acceptance.