DocumentCode :
2967331
Title :
Research on the early warning mechanism for corruption risk in Chinese clean-government promotion
Author :
Zhu Xiao-ning ; Zhang Meng-meng
Author_Institution :
Sch. of Political Sci. & Public Adm., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
fYear :
2013
fDate :
17-19 July 2013
Firstpage :
2230
Lastpage :
2235
Abstract :
As corruption becomes more complicated and concealed, anti-corruption, which is a part of the clean-government promotion, meets greater challenges. The success of anti-corruption lies in the prevention measure whose key point is to understand the trend and discover the symptoms of the corruption promptly. Along with the rules of development of corruption, the corruption risk during the operation of power can be detected then warning will be made. Starting from the rules of the development of corruption, this thesis explores the early warning on corruption risk mechanism and preliminarily establishes an early warning on corruption mechanism covering information collection system, evaluation system, risk identification system, warning and feedback system. And in the context of corruption in China, it proposes some principles and routes for establishing this mechanism, in hope for making some contribution to Chinese clean-government promotion.
Keywords :
feedback; government; information systems; risk analysis; Chinese clean-government promotion; anti-corruption; corruption risk; early warning mechanism; evaluation system; feedback system; information collection system; risk identification system; Educational institutions; Ethics; Government; Inspection; Market research; Monitoring; Presses; clean-government promotion; corruption; corruption risk; early warning mechanism;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Management Science and Engineering (ICMSE), 2013 International Conference on
Conference_Location :
Harbin
ISSN :
2155-1847
Print_ISBN :
978-1-4799-0473-0
Type :
conf
DOI :
10.1109/ICMSE.2013.6586573
Filename :
6586573
Link To Document :
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