Adoption of e-government by the Bulgarian citizens - current state and general trends at the end of the COVID-19 pandemic
This paper contributes to the e-government adoption research by analyzing the results of our Bulgarian national representative survey conducted between June and August 2021, based on restricted survey participants had not accessed any Bulgarian e-government service in the past 12 months prior to the survey. (n = 385). An exploratory factor analysis (EFA) was conducted with Varimax rotation and a critical factor assignment value of 0.5. The obtained results define as the largest group of respondents (37%) for whom the leading factor is the quality of the e-government services, and the other factors have significantly less importance for them. For the second largest group (24%), the most significant reason for not using e-government services is a lack of digital identity. The third most important factor is related to the perception of e-government services as risky.
2. Citizens' information behavior in relation to electronic-government services: a systematic review. Hertzum, Morten. 6, 2022, Journal of Documentation, Vol. 78, pp. 1437-1456.
3. Perceived usefulness, personal experiences, risk perception and trust as determinants of adoption of e-government services in The Netherlands. Horst, M., Kuttschreuter, M. and Gutteling, J.M. 4, 2007, Computers in Human Behavior, Vol. 23, pp. 1838–1852.
4. The online users’ perceptions toward electronic government services. Camilleri, M.A. 2, 2019, Journal of Information, Communication and Ethics in Society, Vol. 18, pp. 221–235.
5. The Effect of Gender, Age, and Education on the Adoption of Mobile Government Services. Mensah, I.K., Zeng, G. and Luo, C. 3, 2020, International Journal on Semantic Web and Information Systems, Vol. 16, pp. 35–52. ISSN: 1552-6283.
6. Evaluation of Public Services Considering the Expectations of Users—A Systematic Literature Review. de Menezes V.G. et al.; Pedrosa G.V.; da Silva M.P.P.; Figueiredo R.M.C. 4, s.l. : MDPI, 2022, Information (Switzerland), Vol. 13. ISSN: 20782489.
7. William Black, Barry Babin, Rolph Anderson, Joseph Hair. Multivariate Data Analysis. 8. s.l. : Cengage Learning EMEA, 2018. ISBN-10 : 1473756545.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
By submitting a paper for publishing the authors hereby comply with the following provisions: 1. The authors retain the copyrights and only give the journal the right for first publication while licensing the work under Creative Commons Attribution License, which grants permissions to others to share the contribution citing this journal as first publication of the text. 2. The authors may enter separate, additional contractual relations for non-exclusive distribution of the published version of the work in this journal (e.g. to upload it in an institutional depository, or to be published in a book), given that they cite the first publication in this journal. 3. The authors are allowed and are encouraged to publish their works online (e.g. to upload it in an institutional depository, personal websites, social networks, etc.) before, during, and after the submission of the paper here, because this may lead to productive exchange, as well as earlier and larger referencing of the published works (see The Effect of Open Access).