Understanding older adults’ continuance intention toward smart locks: a socio-technical study based on the Expectation-Confirmation Model of Information Systems and Task-Technology Fit Model

Background As aging populations continue to grow, smart home technologies—such as smart locks—have become increasingly essential to support older adults’ independent living. Long-term use remains a challenge, however, with most studies focusing on initial adoption rather than sustained engagement. Methods In this study, we examined the key factors related to older adults’ continuance intention toward smart locks, applying a socio-technical framework that integrated the Expectation-Confirmation Model of Information Systems (ECM-IS), the Task-Technology Fit (TTF) model, and external variables, including privacy and security, trust, and habit. We analyzed survey data from 422 Chinese participants aged 55 and older using Partial Least Squares Structural Equation Modeling (PLS-SEM) and Importance-Performance Matrix Analysis (IPMA). Results The model explained 71.6% of the variance in continuance intention ( R 2 = 0.716) and showed strong predictive relevance (Q 2 = 0.623). Trust and perceived usefulness were positively related to continuance intention, followed by satisfaction. Task-technology fit and confirmation were significantly associated with perceived usefulness and satisfaction. Habit and privacy and security were not significant with respect to continuance intention. Conclusions These findings provide theoretical and practical insight for designing age-inclusive, trust-enhancing smart locks that better support older adults’ needs in post-adoption contexts.

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Publication Details

Journal
PeerJ Computer Science
Published
2026-02-19
DOI
https://doi.org/10.7717/peerj-cs.3621
Primary Topic
Technology Use by Older Adults
Type
article
Field-Weighted Citation Impact
0.00
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article

Understanding older adults’ continuance intention toward smart locks: a socio-technical study based on the Expectation-Confirmation Model of Information Systems and Task-Technology Fit Model

Ya Hua, Lu Pei, Yuan Wang, Norazmawati Md Sani et al.
PeerJ Computer Science
Technology Use by Older Adults
article

Understanding older adults’ continuance intention toward smart locks: a socio-technical study based on the Expectation-Confirmation Model of Information Systems and Task-Technology Fit Model

Ya Hua, Lu Pei, Yuan Wang, Norazmawati Md Sani, Jing Cai, Lixin Wang
article en

Abstract

Background As aging populations continue to grow, smart home technologies—such as smart locks—have become increasingly essential to support older adults’ independent living. Long-term use remains a challenge, however, with most studies focusing on initial adoption rather than sustained engagement. Methods In this study, we examined the key factors related to older adults’ continuance intention toward smart locks, applying a socio-technical framework that integrated the Expectation-Confirmation Model of Information Systems (ECM-IS), the Task-Technology Fit (TTF) model, and external variables, including privacy and security, trust, and habit. We analyzed survey data from 422 Chinese participants aged 55 and older using Partial Least Squares Structural Equation Modeling (PLS-SEM) and Importance-Performance Matrix Analysis (IPMA). Results The model explained 71.6% of the variance in continuance intention ( R 2 = 0.716) and showed strong predictive relevance (Q 2 = 0.623). Trust and perceived usefulness were positively related to continuance intention, followed by satisfaction. Task-technology fit and confirmation were significantly associated with perceived usefulness and satisfaction. Habit and privacy and security were not significant with respect to continuance intention. Conclusions These findings provide theoretical and practical insight for designing age-inclusive, trust-enhancing smart locks that better support older adults’ needs in post-adoption contexts.

PeerJ Computer ScienceVol. 12
Universiti Sains Malaysia (MY), Qufu Normal University (CN)
Openalex Percentile: Top 59%
Technology Use by Older Adults
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