The Roles of Big Data for Supporting E-Government Application and Usage in Public Sector, Dubai
DOI:
https://doi.org/10.47604/ijts.2581Keywords:
Big Data Analytics, E-Government Application, Public SectorAbstract
Purpose: This research will establish the extent of the use of big data analytics in supporting e-government applications within the public sector in Dubai.
Methodology: Specifically, qualitative and quantitative studies were conducted, and qualitative and quantitative studies will be conducted considering the trading method as an instrument combining qualitative and quantitative components. For the quantitative aspect of data collection, a self-administered questionnaire was used, while interviews were conducted for the qualitative. An e-survey was administered to 50 employees drawn from the public sector, and five employees were interviewed in detail. For both the collection of data, convenient sampling was adopted. Descriptive statistics were used to analyze quantitative data, including mean, median, mode, and frequency distribution. Quantitative data were also collected through interviews, and qualitative analysis was performed to derive themes.
Findings: The results indicate that big data analytics positively affect the utilization of e-government applications in terms of the effectiveness of decision-making, better management of resources, more substantial transparency, and citizens' engagement. Overall, the findings suggest that citizens get efficient services through big data. In return, they can present their opinions and needs more efficiently to the government. It creates better interactions with government organizations, predicts people's needs, and enables better tracking and representation of results. However, some of the threats included This despite the following identified drawbacks. It is suggested that constant training has to be given at the workplace to create ample data proficiency among the workforce, data privacy has to be established, and further, technological support has to be procured.
Unique Contribution to Theory, Practice and Policy: Moreover, the frequency of citizens' increase through marketing promotions and adopting changes over time is fundamental. This means that the inclusion of big data in e-government applications promotes the delivery of handy services to the citizens and enhances the efficiency of the government, hence promoting government transparency. Future research should ensure a more extensive population, investigate other industries, and use statistical analysis to understand big data on e-government better.
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References
Al-Mushayt, O. S. (2019). Automating E-government services with artificial intelligence. IEEE Access, 7, 146821-146829.
Al-Sai, Z. A., & Abualigah, L. M. (2017, May). Big data and E-government: A review. In 2017 8th international conference on information technology (ICIT) (pp. 580-587). IEEE.
Anshari, M., & Lim, S. A. (2017). E-government with big data enabled through smartphone for public services: Possibilities and challenges. International Journal of Public Administration, 40(13), 1143-1158.
Bertot, J. C., & Choi, H. (2013, June). Big data and e-government: issues, policies, and recommendations. In Proceedings of the 14th annual international conference on digital government research (pp. 1-10).
Bertot, J. C., Gorham, U., Jaeger, P. T., Sarin, L. C., & Choi, H. (2014). Big data, open government and e-government: Issues, policies and recommendations. Information polity, 19(1-2), 5-16.
Davis, F. D., Granić, A., & Marangunić, N. (2023). The technology acceptance model 30 years of TAM. Technology, 1(1), 1-150.
GarcÃa-Avils, J. A. (2020). Diffusion of innovation. The international Encyclopedia of media psychology, 1-8.
Granić, A., & Marangunić, N. (2019). Technology acceptance model in educational context: A systematic literature review. British Journal of Educational Technology, 50(5), 2572-2593.
Hou, H. (2017, July). The application of blockchain technology in E-government in China. In 2017 26th International Conference on Computer Communication and Networks (ICCCN) (pp. 1-4). IEEE.
Hussain, A., Mkpojiogu, E. O., Ishak, N., Mokhtar, N., & Ani, Z. C. (2019). An Interview Report on Users' Perception about the Usability Performance of a Mobile E-Government Application. Int. J. Interact. Mob. Technol., 13(10), 169-178.
Jacob, D. W., Fudzee, M. F. M., Salamat, M. A., & Herawan, T. (2019). A review of the generic end-user adoption of e-government services. International Review of Administrative Sciences, 85(4), 799-818.
Manoharan, A. P., & Ingrams, A. (2018). Conceptualizing e-government from local government perspectives. State and Local Government Review, 50(1), 56-66.
SALISU, K. (2015). E-Government Adoption And Framework For Big Data Analytics In.
Shebli, K. A., Said, R. A., Taleb, N., Ghazal, T. M., Alshurideh, M. T., & Alzoubi, H. M. (2021, June). PUBLIC SECTOE 's employees' perceptions toward the efficiency of artificial intelligence and big data utilization in providing smart services to the residents of Dubai. In The International Conference on Artificial Intelligence and Computer Vision (pp. 573-585). Springer, Cham.
Twizeyimana, J. D., & Andersson, A. (2019). The public value of E-Government-A literature review. Government information quarterly, 36(2), 167-178.
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