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

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Authors: Yuan Wang, Norazmawati Md Sani, Jing Cai, Lu Pei, Lixin Wang, Ya Hua
Cited by: 1
References: 93

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.

Fields of Study & Subjects

Technology Use by Older Adults Context-Aware Activity Recognition Systems Innovative Human-Technology Interaction

Publication details

Journal / source
PeerJ Computer Science
Publisher
PeerJ
Volume
12
Pages
e3621–e3621
Publication date
19 February 2026
Language
EN