Mitigation of Corruption by Implementing e-Government Using Soft Computing

Electronic government (e-government) allows citizens to contact government authorities directly through computers, smartphones, and the Internet. In the return reducing face-to-face interaction with government employees decreases their permissive role and the potential for corruption, hence enabling...

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Bibliographic Details
Published inAdvances in fuzzy systems Vol. 2022; pp. 1 - 9
Main Author Shareef, Shareef M.
Format Journal Article
LanguageEnglish
Published New York Hindawi 07.10.2022
Hindawi Limited
Subjects
Accountability
Advisors
Algorithms
Developing countries
Electronic government
Fuzzy logic
Information dissemination
LDCs
Performance management
Politics
Power
Public sector
Public services
Soft computing
Success
Transparency
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Summary:Electronic government (e-government) allows citizens to contact government authorities directly through computers, smartphones, and the Internet. In the return reducing face-to-face interaction with government employees decreases their permissive role and the potential for corruption, hence enabling the government to be more effective and trustworthy and provide transparency and accountability. However, e-government is not the only aspect of the larger battle against corruption; it is not the only way to reduce corruption. e-government is successful in the fight against trivial and administrative corruption. In spite of that, broad governmental actions, including both preventative and perhaps disciplinary anticorruption measures are required to combat corruption. This research aims to identify the factors that affect success in reducing the level of corruption in e-government, and then evaluate these factors by developing a model that determines the effective factors that impact the mitigation of corruption. We believe that a soft computing-fuzzy logic algorithm is an appropriate method for evaluating and determining the effective factors, and hence might lead to a feasible way to the success of e-government. The findings revealed that the model is adaptable and may be used in e-government performance applications for government authorities and experts.
ISSN:1687-7101
1687-711X
DOI:10.1155/2022/3375567