A study on the adoption of IoT smart home service: using Value-based Adoption Model
Abstract
This study aims to comprehensively examine the adoption of smart home service. A new model combining VAM (Value-based Adoption Model) and TAM (Technical Acceptance Model) was developed and analysed with a set of variables from Unified Theory of Acceptance and Use of Technology and Elaboration Likelihood Model. Perceived value was affected by both perceived benefit and perceived sacrifice. In particular, perceived benefit was found to have a strong positive effect on perceived value. In contrast, privacy risk and innovation resistance were found to limit perceived value. This study holds considerable significance as it proposes a new approach to IoT (Internet of Things)-based smart home service adoption using VAM and TAM. Through these two models, the study determined that it is imperative for businesses to constitute and secure appropriate infrastructure for residents to use IoT-based smart home service. Developing content related to security is also crucial.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
An inverse correlation exists between perceived risks and perceived value when predicting technology use intention.
“A growing body of research supports the notion that an inverse correlation exists between perceived risks and perceived value when predicting technology use intention [28,29,30,36,43]”
From ChatGPT in Learning: Assessing Students’ Use Intentions through the Lens of Perceived Value and the Influence of AI Literacy (2024) · cites this paper as [36]
The citation lists haven’t been fetched yet
References 56 · Cited by 328
- Authors
- Kim, Y., Park, Y., & Choi, J.
- Affiliations
- Soongsil University (KR)
- Graduate School of Business, Soongsil University, Seoul, Republic of Korea
- Corresponding author
- Choi, Jeongil
- Venue
- Total Quality Management & Business Excellence
- Publisher
- Informa UK Limited
- Published
- 2017-04-12
- Volume
- 28
- Issue
- 9-10
- Pages
- 1149-1165
- ISSN
- 1478-3363 (ISSN-L)
- 1478-3371
- OpenAlex
- W2606252612
- Cited by
- 328
- References
- 56
- Citations by year
- 2026: 20 · 2025: 49 · 2024: 40 · 2023: 55 · 2022: 54 · 2021: 45 · 2020: 29 · 2019: 22 · 2018: 11 · 2017: 2
- FWCI
- 28.18
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Total Quality Management & Business Excellence (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Physical Sciences › Engineering › Electrical and Electronic Engineering › IoT-based Smart Home Systems
- Life Sciences › Agricultural and Biological Sciences › General Agricultural and Biological Sciences › Agricultural Innovations and Practices
- Keywords
- smart home services, Internet of Things, technology adoption, value-based adoption model, technology acceptance model, perceived value, perceived benefits, perceived sacrifice, privacy risks, resistance to innovation, Unified Theory of Acceptance and Use of Technology, elaboration likelihood model, security infrastructure
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
