Moscow State University. M.V. Lomonosov (Department of Socio-Cultural Design and Development of Territories, Professor)
Moskva, Moscow, Russian Federation
The relevance of the presented study is determined by the fact that the integration of artificial intelligence technologies into the scientific management system of F. Taylor can improve the efficiency of its functioning, including by increasing employee motivation, adapting strategies to individual characteristics, especially during periods of economic instability. The purpose of the presented research was to assess the potential capabilities and prospects for the integration of artificial intelligence technologies into the scientific management system of F.W. Taylor in terms of assessing the impact of this integration on the efficiency of taking into account individual motivation characteristics in the context of the ongoing global economic crisis, as well as in the phase of exiting it with competitive advantages, if possible. The scientific novelty of the research lies in the formation of a model for taking into account individual motivation characteristics of employees using artificial intelligence technologies, including: as an input layer of the neural network - a database of individual abilities and motivation characteristics of company employees {X}; as a hidden layer of the neural network - a database of correlation links between individual abilities and motivation characteristics of the company's employees and the company's tasks that require solving R {X; Y}; as the output layer of the neural network: a database of company tasks requiring solutions {Y}. The practical significance of the results obtained is that the proposed model allows taking into account the individual characteristics of employee motivation using artificial intelligence technologies in an inextricable connection with their ability to perform certain tasks requiring solutions for the company.
F. Taylor's scientific management system, modern conditions, socio-economic development
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