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Statistical and neural network methods for analyzing indicators of healthy administration

DOI 10.18127/j19998554-201810-07

Keywords:

Yu.Yu. Petrunin - Dr.Sc. (Phil.), Professor, Head of the Department of Mathematical Methods and Information Technologies in the Management, Head of Laboratory of Big Data analysis, Faculty of Public Administration, Lomonosov Moscow State University
E-mail: Petrunin@spa.msu.ru
Y.A. Siluyanova - Post-graduate Student, Department of Sociology, Faculty of Public Administration, Lomonosov Moscow State University
E-mail: zernovaju@gmail.com


This study reveals the signs and factors of stable and harmonious development of organizations of various types. Based on the data obtained during the questioning of employees of various institutions: from state and municipal workers to employees of business structures and NGOs.
We used a complex model, including both traditional methods of data analysis and mathematical statistics, as well as the methods of artificial neural networks implemented in the software products Statistica and Viscovery SOMine.
Our research showed, that the overall main problem of administration is a lack of motivation.
According K. Shapiro and J. Stiglitz, the most important factor that influences the opportunistic motivation of employees is the expected duration of the employee's relationship with the organization [QQ]. The study revealed the factors, having have a negative impact on this indicator. List of factors:
exclusion of an employee from the decision-making process
Opaque career growth
an incomprehensible statement of tasks
lack of feedback on the quality of the work performed
disapproval of forms of control in the organization
It was also found that an employee who does not associate his future with this organization, trusts informal sources of information.

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