The DOI matches its Crossref record; 78 of the 78 references it cites were found in a registry or an index.
A unified perspective on the factors influencing consumer acceptance of internet of things technology
Open accessAbstract
Purpose: – With recent advances in internet technologies, internet of things (IoT) technology is having an increasing impact on our daily lives, and beginning to offer interesting and advantageous new services. The current research aims to develop and test an integrative model of factors determining consumers' acceptance of IoT technology. Design/methodology/approach: – Based on technology acceptance model (TAM), the authors proposed an IoT acceptance model that consists of three technology factors (perceived usefulness, perceived ease of use, and trust); one social context factor (social influence); and two individual user characteristics (perceived enjoyment and perceived behavioral control). Data from 368 Chinese consumers were used to test the research model through the use of structural equation modeling. Findings: – The results showed particularly strong support for the effects of perceived usefulness, perceived ease of use, social influence, perceived enjoyment, and perceived behavioral control. However, trust played an insignificant role in predicting the intention. In addition, perceived ease of use and trust were found to affect perceived usefulness. Compared with the individual TAM model, the integrated model provides more explanation on user behavioral intention toward IoT usage. Originality/value: – The integrated model explores the driving factors of individuals' willingness to use IoT technology from the perspectives of the technology itself, social context and individual user characteristic. It links the constructs of social influence, enjoyment, and perceived behavioral control to the TAM and successfully extends TAM in the IoT technology context.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Evaluating structural equation models with unobservable variables and measurement error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800104 · Cited by 109,190
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
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
Structural equation modeling in practice: A review and recommended two-step approach
Anderson, J. C., & Gerbing, D. W. (1988) · Psychological Bulletin · doi:10.1037/0033-2909.103.3.411 · Cited by 41,941
Rogers, E. M., Singhal, A., & Quinlan, M. M. (2019) · An Integrated Approach to Communication Theory and Research · doi:10.4324/9780203710753-35 · Cited by 37,322
On the Evaluation of Structural Equation Models
Bagozzi, R. P., & Yi, Y. (1988) · Journal of the Academy of Marketing Science · doi:10.1007/bf02723327 · Cited by 26,163
User Acceptance of Computer Technology: A Comparison of Two Theoretical Models
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989) · Management Science · doi:10.1287/mnsc.35.8.982 · Cited by 25,709
A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies
Venkatesh, V., & Davis, F. D. (2000) · Management Science · doi:10.1287/mnsc.46.2.186.11926 · Cited by 23,066
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012) · MIS Quarterly · doi:10.2307/41410412 · Cited by 15,756
Cited by
Understanding the Blockchain technology adoption in supply chains-Indian context
Kamble, S., Gunasekaran, A., & Arha, H. (2019) · International Journal of Production Research · doi:10.1080/00207543.2018.1518610 · Cited by 960
Mariani, M. M., Perez‐Vega, R., & Wirtz, J. (2022) · Psychology & Marketing · doi:10.1002/mar.21619 · Cited by 631
Mariani, M. M., Machado, I., Magrelli, V., & Dwivedi, Y. K. (2023) · Technovation · doi:10.1016/j.technovation.2022.102623 · Cited by 578
Internet of Things and Big Data as enablers for business digitalization strategies
Sestino, A., Prete, M. I., Piper, L., & Guido, G. (2020) · Technovation · doi:10.1016/j.technovation.2020.102173 · Cited by 559
Challenges, Opportunities and Future Directions of Smart Manufacturing: A State of Art Review
Phuyal, S., Bista, D., & Bista, R. (2020) · Sustainable Futures · doi:10.1016/j.sftr.2020.100023 · Cited by 396
Metadata
- Authors
- Gao, L., & Bai, X.
- Venue
- Asia Pacific Journal of Marketing and Logistics
- Publisher
- Emerald
- Published
- 2014-04-08
- Volume
- 26
- Issue
- 2
- Pages
- 211-231
- ISSN
- 1355-5855 (ISSN-L)
- OpenAlex
- W1995620486
- Cited by
- 501
- References
- 78
- FWCI
- 21.42
- Type
- journal article
- Language
- en
- Open access
- green
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A unified perspective on the factors influencing consumer acceptance of internet of things technology. https://app.cochat.ai/papers/10.1108/apjml-06-2013-0061
- The paper
- Gao, L., & Bai, X. (2014). A unified perspective on the factors influencing consumer acceptance of internet of things technology. Asia Pacific Journal of Marketing and Logistics. https://doi.org/10.1108/apjml-06-2013-0061
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.