Natalia Maslii
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Modern technologies of detection and prevention of corruption in emerging information society
Natalia Maslii , Natalia Zakharchenko , Viktoriia Butenko , Oksana Savastieieva , Tetiana Butenko , Liudmyla Shyriaieva doi: http://dx.doi.org/10.21511/ppm.16(1).2018.06Problems and Perspectives in Management Volume 16, 2018 Issue #1 pp. 58-67
Views: 1924 Downloads: 417 TO CITE АНОТАЦІЯWith the development of the information society, there has been rapidly growing number of international research on the role of various (information, innovation, intelligent) technologies as a catalyst to fight corruption. As you know, the problems posed by corruption are economic, social and political consequences. In recent years economists and various researchers have shown increasing interest in studying the phenomenon of corruption. Many researchers in the field of studying corruption phenomenon are of theoretical nature, which studied different behaviors without having developed effective methods and technologies to identify and prevent corruption in the various spheres of government. In this regard, there is a need to study the world experience of application of technologies in the prevention of corruption and anti-corruption platform in Ukraine. This will allow to adapt them to positive experience in the implementation of mechanisms to identify and prevent corruption in Ukraine. The authors believe that to obtain a more accurate picture of the corruption situations that provide characteristics and its quantitative description is possible only by means of modelling the corruption phenomenon. In this regard, the analysis of theoretical models of corruption was made: the modelling made by the mathematical notation of the models and conclusions on the effectiveness of their application in management. Using simulation, the authors came to the conclusion that the detection and prevention of corruption should be carried out with the use of technologies and the system approach: from the study of statistics and use of anti-corruption platforms, public registers and databases to logical and probabilistic (LP) risk models of corruption.
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