Journal article
Factors that predict the acceptance and adoption of smart home technology by seniors in Australia: a structural equation model with longitudinal data
Informatics for Health and Social Care, Vol.48(1), pp.80-94
26/04/2022
PMID: 35473463
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Source: InCites
Abstract
Smart Home Technology presents an exciting opportunity to support seniors living independently in their homes. Despite widespread interest in Smart Homes, seniors’ readiness to adopt Smart Home Technology is low. To determine the factors underpinning Australian seniors’ acceptance and adoption of Smart Home Technology using an extended UTAUT model that includes Trust, Resistance to Change and Technology Anxiety. A longitudinal study was conducted to validate the proposed model prior to and after the implementation of a pilot Smart Home Modification program for seniors. Structural Equation Modeling has been applied to test the proposed hypotheses using a sample of 60 seniors in regional Australia. Perceived Usefulness is an important predictor of Smart Home Technology adoption by seniors. Trust was found to indirectly predict adoption of Smart Home Technology via Perceived Usefulness. This study showed that Perceived Usefulness and Trust are critical factors for the acceptance and use of SHT by seniors, validating the extension of UTAUT with a Trust factor. This makes a unique theoretical contribution to the literature with implications for aged care providers and policymakers to consider seniors’ perceived usefulness and trust in the design, development, and implementation of Smart Home solutions.
Details
- Title
- Factors that predict the acceptance and adoption of smart home technology by seniors in Australia: a structural equation model with longitudinal data
- Creators
- Golam Sorwar - Southern Cross UniversityChristina Aggar - Southern Cross UniversityOlivia Penman - Southern Cross UniversityCarolyn Seton - Southern Cross UniversityAnastasia Ward - Southern Cross University
- Publication Details
- Informatics for Health and Social Care, Vol.48(1), pp.80-94
- Publisher
- Taylor & Francis
- Identifiers
- 991013015498402368
- Copyright
- © 2022 Taylor & Francis Group, LLC.
- Academic Unit
- Information Technology; Faculty of Science and Engineering; Nursing; Faculty of Health
- Language
- English
- Resource Type
- Journal article