User acceptance of smart home services: An extension of the theory of planned behavior
Abstract
Purpose: The purpose of this paper is to develop a comprehensive research model that can explain potential customers’ behavioral intentions to adopt and use smart home services. Design/methodology/approach: This study proposes and validates a new theoretical model that extends the theory of planned behavior. Partial least squares analysis is employed to test the research model and corresponding hypotheses on data collected from 216 survey samples. Findings: Mobility, security/privacy risk, and trust in the service provider are important factors affecting the adoption of smart home services. Practical implications: To increase potential users’ adoption rate, service providers should focus on developing mobility-related services that enable people to access smart home services while on the move using mobile devices via control and monitoring functions. Originality/value: This study is the first empirical attempt to examine user acceptance of smart home services, as most of the prior literature has concerned technical features.
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?
The decision and behaviour of consumers are affected mainly by knowledge, trust, and awareness.
“The decision and behaviour of consumers are a ected mainly by knowledge, trust, and awareness [30].”
From Are You Environmentally Conscious Enough to Differentiate between Greenwashed and Sustainable Items? A Global Consumers Perspective (2020) · cites this paper as [30]
Cites
The theory of planned behavior
Ajzen, I. (1991) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(91)90020-t · Cited by 90,587 · see citing works
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003) · Journal of Applied Psychology · doi:10.1037/0021-9010.88.5.879 · Cited by 82,194 · see citing works
Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003) · Information Systems Research · doi:10.1287/isre.14.2.189.16018 · Cited by 6,479 · see citing works
(2003) · International Journal of Electronic Commerce · doi:10.1080/10864415.2003.11044275 · Cited by 5,715 · see citing works
Wetzels, M., Odekerken-Schröder, G., & van Oppen, C. (2009) · MIS Quarterly · doi:10.2307/20650284 · Cited by 4,944 · see citing works
Humans and automation: Use, misuse, disuse, abuse
Parasuraman, R., & Riley, V. (1997) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872097778543886 · Cited by 4,554 · see citing works
Assessing IT Usage: The Role of Prior Experience
Taylor, S., & Todd, P. (1995) · MIS Quarterly · doi:10.2307/249633 · Cited by 2,891 · see citing works
Perceived risk: Further considerations for the marketing discipline
Stone, R. N., & Grønhaug, K. (1993) · European Journal of Marketing · doi:10.1108/03090569310026637 · Cited by 1,348 · see citing works
Gamal Aboelmaged, M. (2010) · Industrial Management & Data Systems · doi:10.1108/02635571011030042 · Cited by 240 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Sohn, K., & Kwon, O. (2020) · Telematics and Informatics · doi:10.1016/j.tele.2019.101324 · Cited by 646 · see citing works
Lăzăroiu, G., Neguriţă, O., Grecu, I., Grecu, G., & Mitran, P. C. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.00890 · Cited by 432 · see citing works
Adoption of artificial intelligence (AI) for talent acquisition in IT/ITeS organizations
Pillai, R., & Sivathanu, B. (2020) · Benchmarking: An International Journal · doi:10.1108/bij-04-2020-0186 · Cited by 422 · see citing works
Technology acceptance research: Meta-analysis
Marikyan, D., Papagiannidis, S., & Stewart, G. (2026) · Journal of Information Science · doi:10.1177/01655515231191177 · Cited by 140 · see citing works
Urbański, M., & ul Haque, A. (2020) · Sustainability · doi:10.3390/su12051786 · Cited by 122 · see citing works
Privacy is the Boring Bit: User Perceptions and Behaviour in the Internet-of-Things
Williams, M., Nurse, J. R. C., & Creese, S. (2017) · 2017 15th Annual Conference on Privacy, Security and Trust (PST) · doi:10.1109/pst.2017.00029 · Cited by 53 · see citing works
- Authors
- Yang, H., Lee, H., & Zo, H.
- Affiliations
- Samsung (South Korea) (KR)
- Dankook University (KR)
- Korea Advanced Institute of Science and Technology (KR)
- Venue
- Industrial Management & Data Systems
- Publisher
- Emerald
- Published
- 2017-02-06
- Volume
- 117
- Issue
- 1
- Pages
- 68-89
- ISSN
- 0263-5577 (ISSN-L)
- OpenAlex
- W2577608393
- Cited by
- 325
- References
- 9
- Citations by year
- 2026: 14 · 2025: 34 · 2024: 34 · 2023: 50 · 2022: 58 · 2021: 57 · 2020: 38 · 2019: 19 · 2018: 17 · 2017: 4
- FWCI
- 34.29
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Industrial Management & Data Systems (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
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Keywords
- smart home services, user acceptance, theory of planned behavior, technology adoption, behavioral intention, mobility, trust in service providers
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
