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Administrative Corruption as a Moral and Social Pest in Iran's Public Organizations
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Abstract: (462 Views) |
Background: Corruption is widely recognized as a moral and social scourge. In the fight against administrative corruption, a deep and original set of moral values is needed. Both the public sector and the private sector suffer from corruption, and the main goal of this research is to design a model for identifying administrative corruption with a data mining approach in Iran's government organizations.
Method: This research was applied and descriptive. The statistical population of the research is the experts and senior experts working in the government offices of Tehran, and 327 people who were selected by the proportional sampling method formed the research sample. The data collection tool in this research was a questionnaire, and content validity and Cronbach's coefficient were used for its validity and reliability. To analyze the data in this research, one of the most widely used data mining and machine learning methods, i.e. artificial neural network, was used.
Results: According to the obtained results, it was determined that the prediction rate of the model was 66.1 percent and based on the ranking of the input layers of unethical variables such as: the extravagance of people and the low quality of laws and regulations as the most important input variables. Artificial neural network was identified.
Conclusion: Administrative corruption is a complex and multidimensional phenomenon that arises for many reasons and has many effects that manifests itself in various roles and aspects. Due to the importance of this issue in different countries, extensive studies have been conducted in recent years to identify and determine the causes of this problem, and without a doubt, unethical variables and populism are the most important factors in creating this problem. |
Article number: 7 |
| Keywords: Administrative corruption, Moral hazard, Public organizations |
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Full-Text [PDF 561 kb]
(223 Downloads)
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Type of Study: Research |
Subject:
Special
Received: 2022/12/21 | Accepted: 2023/01/28 | Published: 2023/08/1
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