The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
E-government adoption in sub-Saharan Africa
Abstract
Abstract Over the past decade, there has been increased interest in understanding the underlying factors that influence the adoption of e-government services using a variety of technology acceptance models. One such model is the unified model of electronic government adoption (UMEGA), which has been validated as outperformed other models. The present study empirically tested UMEGA and an extended version of it using data from 282 respondents in a sub-Saharan African country, South Africa. The findings show that except for the association of effort expectancy with attitude, all other hypothesized associations of UMEGA were supported. Also, the extended version of the model performed better than the original version, with the total variance explained for attitudes modestly increasing and that for behavioral intention modestly improving also. We observed that performance expectancy, social influence, perceived risk and computer self-efficacy significantly influenced attitudes, while attitudes, facilitating conditions, trust of government and trust of the Internet had a direct significant influence on behavioral intention. For researchers, this study indicates the need to adequately refine e-government adoption models for use in different context. These findings from South Africa also provide an understanding of factors that the South African government can consider when developing strategies for improving the adoption of e-government services.
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
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
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012) · MIS Quarterly · doi:10.2307/41410412 · Cited by 15,756
Using pls path modeling in new technology research: updated guidelines
Henseler, J., Hubona, G., & Ray, P. A. (2016) · Industrial Management & Data Systems · doi:10.1108/imds-09-2015-0382 · Cited by 7,173
An empirical validation of a unified model of electronic government adoption (UMEGA)
Dwivedi, Y. K., Rana, N. P., Janssen, M., Lal, B., Williams, M. D., & Clement, M. (2017) · Government Information Quarterly · doi:10.1016/j.giq.2017.03.001 · Cited by 622
e-Government Adoption Model (GAM): Differing service maturity levels
Shareef, M. A., Kumar, V., Kumar, U., & Dwivedi, Y. K. (2011) · Government Information Quarterly · doi:10.1016/j.giq.2010.05.006 · Cited by 581
Šumak, B., & Šorgo, A. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.07.037 · Cited by 295
User acceptance of e-government services: examining an e-tax filing and payment system in Thailand
Bhuasiri, W., Zo, H., Lee, H., & Ciganek, A. P. (2016) · Information Technology for Development · doi:10.1080/02681102.2016.1173001 · Cited by 117
Alshare, K. A., & Lane, P. L. (2011) · Communications of the Association for Information Systems · doi:10.17705/1cais.02834 · Cited by 102
Cited by
Neneh, B. N. (2022) · Studies in Higher Education · doi:10.1080/03075079.2020.1770716 · Cited by 363
Chen, L., & Aklikokou, A. K. (2020) · International Journal of Public Administration · doi:10.1080/01900692.2019.1660989 · Cited by 317
Mensah, I. K. (2019) · Sage Open · doi:10.1177/2158244019855823 · Cited by 104
Malaysian urban poor adoption of e-government applications and their satisfaction
Shuib, L., Yadegaridehkordi, E., & Ainin, S. (2019) · Cogent Social Sciences · doi:10.1080/23311886.2019.1565293 · Cited by 36
Metadata
- Authors
- Verkijika, S. F., & De Wet, L.
- Venue
- Electronic Commerce Research and Applications
- Publisher
- Elsevier BV
- Published
- 2018-07
- Volume
- 30
- Pages
- 83-93
- ISSN
- 1567-4223 (ISSN-L)
- OpenAlex
- W2807302174
- Cited by
- 159
- References
- 8
- FWCI
- 65.45
- Type
- journal article
- Language
- en
- Open access
- closed
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: E-government adoption in sub-Saharan Africa. https://app.cochat.ai/papers/10.1016/j.elerap.2018.05.012
- The paper
- Verkijika, S. F., & De Wet, L. (2018). E-government adoption in sub-Saharan Africa. Electronic Commerce Research and Applications. https://doi.org/10.1016/j.elerap.2018.05.012
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.