The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
UTAUT2 Based Predictions of Factors Influencing the Technology Acceptance of Phablets by DNP
Open accessAbstract
The smart mobile devices have emerged during the past decade and have become one of the most dominant consumer electronic products. Therefore, exploring and understanding the factors which can influence the acceptance of novel mobile technology have become the essential task for the vendors and distributors of mobile devices. The Phablets, integrated smart devices combining the functionality and characteristics of both tablet PCs and smart phones, have gradually become possible alternatives for smart phones. Therefore, predicting factors which can influence the acceptance of Phablets have become indispensable for designing, manufacturing, and marketing of such mobile devices. However, such predictions are not easy. Meanwhile, very few researches tried to study related issues. Consequently, the authors aim to explore and predict the intentions to use and use behaviors of Phablets. The second generation of the Unified Theory of Acceptance and Use of Technology (UTAUT2) is introduced as a theoretic basis. The Decision Making Trial and Evaluation Laboratory (DEMATEL) based Network Process (DNP) will be used to construct the analytic framework. In light of the analytic results, the causal relationships being derived by the DEMATEL demonstrate the direct influence of the habit on other dimensions. Also, based on the influence weights being derived, the use intention, hedonic motivation, and performance expectancy are the most important dimensions. The analytic results can serve as a basis for concept developments, marketing strategy definitions, and new product designs of the future Phablets. The proposed analytic framework can also be used for predicting and analyzing consumers’ preferences toward future mobile devices.
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
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
Ryan, R. M., & Deci, E. L. (2000) · American Psychologist · doi:10.1037//0003-066x.55.1.68 · Cited by 54,599
Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence
Zeithaml, V. A. (1988) · Journal of Marketing · doi:10.1177/002224298805200302 · Cited by 18,292
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012) · MIS Quarterly · doi:10.2307/41410412 · Cited by 15,756
Moore, G. C., & Benbasat, I. (1991) · Information Systems Research · doi:10.1287/isre.2.3.192 · Cited by 9,150
Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control
Ajzen, I., & Madden, T. J. (1986) · Journal of Experimental Social Psychology · doi:10.1016/0022-1031(86)90045-4 · Cited by 5,718
Mathieson, K. (1991) · Information Systems Research · doi:10.1287/isre.2.3.173 · Cited by 4,216
Value-based Adoption of Mobile Internet: An empirical investigation
Kim, H.-W., Chan, H. C., & Gupta, S. (2007) · Decision Support Systems · doi:10.1016/j.dss.2005.05.009 · Cited by 2,084
The social influence model of technology adoption
Vannoy, S. A., & Palvia, P. (2010) · Communications of the ACM · doi:10.1145/1743546.1743585 · Cited by 210 · cited 1×
“Therefore, discovering and exploring the crucial factors which can influence the acceptance and continuous usage of the smart mobile devices have become indispensable for marketers and designers to enable such devices to reach better and to satisfy customers’ anticipation [1, 2].”
BackgroundMagni, M., Susan Taylor, M., & Venkatesh, V. (2010) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2010.03.004 · Cited by 173
Cited by
Venkatesh, V., & Morris, M. G. (2000) · MIS Quarterly · doi:10.2307/3250981 · Cited by 2,780
The Supply Chain Has No Clothes: Technology Adoption of Blockchain for Supply Chain Transparency
Francisco, K., & Swanson, D. (2018) · Logistics · doi:10.3390/logistics2010002 · Cited by 951
Nikolopoulou, K., Gialamas, V., & Lavidas, K. (2020) · Education and Information Technologies · doi:10.1007/s10639-020-10157-9 · Cited by 205
Acceptance of Mobile Health Applications: Examining Key Determinants and Moderators
Nunes, A., Limpo, T., & Castro, S. L. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.02791 · Cited by 114
Alhwaiti, M. (2023) · Applied Artificial Intelligence · doi:10.1080/08839514.2023.2175110 · Cited by 105
Metadata
- Authors
- Huang, C.-Y., & Kao, Y.-S.
- Venue
- Mathematical Problems in Engineering
- Publisher
- Wiley
- Published
- 2015
- Volume
- 2015
- Pages
- 1-23
- ISSN
- 1024-123X (ISSN-L)
- 1563-5147
- OpenAlex
- W1752577401
- Cited by
- 163
- References
- 10
- FWCI
- 11.58
- Type
- journal article
- Language
- en
- Open access
- hybrid
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: UTAUT2 Based Predictions of Factors Influencing the Technology Acceptance of Phablets by DNP. https://app.cochat.ai/papers/10.1155/2015/603747
- The paper
- Huang, C.-Y., & Kao, Y.-S. (2015). UTAUT2 Based Predictions of Factors Influencing the Technology Acceptance of Phablets by DNP. Mathematical Problems in Engineering. https://doi.org/10.1155/2015/603747
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.