Factors affecting the elderly’s behavioral intention toward smart home systems: A cross-sectional study from China’s eastern coast

As China's population continues to age rapidly, smart elderly care has become a crucial strategy for addressing this societal challenge. Smart home systems have the potential to significantly enhance the quality of life, safety, and autonomy of the elderly. However, the adoption rate of these systems in this demographic remains relatively low, requiring an exploration of the key factors influencing the behavioral intention to use such systems. This study developed a comprehensive model based on the Technology Acceptance Model and the Unified Theory of Acceptance and Use of Technology. Through empirical analysis using partial least squares structural equation modeling, this study systematically examined the pathways through which various factors affected the behavioral intentions of the elderly. The findings revealed that perceived usefulness, facilitating conditions, compatibility, and perceived cost had significant direct effects on behavioral intention. Additionally, social influence, perceived trust, facilitating conditions, and compatibility indirectly influenced behavioral intention through perceived usefulness and perceived ease of use. Although perceived trust did not directly affect behavioral intention, it exerted an indirect influence through perceived usefulness. This comprehensive model provides theoretical insights into the behavioral intentions of the elderly toward smart home systems and offers practical guidance for developers, designers, and policymakers in the development, design, and promotion of these systems.

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Publication Details

Journal
PLoS ONE
Published
2024-12-13
DOI
https://doi.org/10.1371/journal.pone.0311280
Citations
4
Primary Topic
Technology Adoption and User Behaviour
Type
article
Field-Weighted Citation Impact
4.20

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article

Factors affecting the elderly’s behavioral intention toward smart home systems: A cross-sectional study from China’s eastern coast

Qianling Jiang, Ya Hua, Norazmawati Md. Sani, Yuan Wang et al.
4 citations
PLoS ONE
Technology Adoption and User Behaviour
4.20
article

Factors affecting the elderly’s behavioral intention toward smart home systems: A cross-sectional study from China’s eastern coast

Qianling Jiang, Ya Hua, Norazmawati Md. Sani, Yuan Wang, Long Zhao
article en
4 citations

Abstract

As China's population continues to age rapidly, smart elderly care has become a crucial strategy for addressing this societal challenge. Smart home systems have the potential to significantly enhance the quality of life, safety, and autonomy of the elderly. However, the adoption rate of these systems in this demographic remains relatively low, requiring an exploration of the key factors influencing the behavioral intention to use such systems. This study developed a comprehensive model based on the Technology Acceptance Model and the Unified Theory of Acceptance and Use of Technology. Through empirical analysis using partial least squares structural equation modeling, this study systematically examined the pathways through which various factors affected the behavioral intentions of the elderly. The findings revealed that perceived usefulness, facilitating conditions, compatibility, and perceived cost had significant direct effects on behavioral intention. Additionally, social influence, perceived trust, facilitating conditions, and compatibility indirectly influenced behavioral intention through perceived usefulness and perceived ease of use. Although perceived trust did not directly affect behavioral intention, it exerted an indirect influence through perceived usefulness. This comprehensive model provides theoretical insights into the behavioral intentions of the elderly toward smart home systems and offers practical guidance for developers, designers, and policymakers in the development, design, and promotion of these systems.

PLoS ONEVol. 19(12)
Jiangnan University (CN), Universiti Sains Malaysia (MY), Qufu Normal University (CN)
Qufu Normal University
Life below water
Openalex Percentile: Top 5%
Technology Adoption and User Behaviour
4.20
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