Видання зареєстровані авторами шляхом самоархівування
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Item Systematic bibliometric review of artificial intelligence technology in organizational management, development, change and culture(Vilnius Gedminas Technical University, 2022) Bilan, S.; Suler, P.; Скринник, Олена Вікторівна; Скрынник, Елена Викторовна; Skrynnyk, Olena Viktorivna; Krajnakova, E.; Васильєва, Тетяна Анатоліївна; Васильева, Татьяна Анатольевна; Vasylieva, Tetiana AnatoliivnaEven now, in the times of advanced digitization, the planning and implementation of many organizational meas-ures remain human-driven. Corresponding to a global trend of application of artificial intelligence in all areas of life, it has received more attention in the last few years and garnered emerging clusters of research in usage of this technology for organizational issues. Some companies already offer tools that support different management tasks in the area of organiza-tional development, but they are not holistic. According to the Google trend analysis of the search for artificial intelligence, the inquiry to this topic continues increasing. The purpose of the described investigation was to identify the academic trends in research interaction between such sci-entific fields, as Artificial Intelligence, Organizational Management, Organizational Development, Organizational Change, and Organizational Culture using bibliometric and network publication analysis. In order to achieve this purpose, we sys-tematically analysed 191 publications between 1983 and 2020 as well as cited and citing publications. The findings of this study provide important conclusions of the current research state. The insightful results are presented in the form of critical review and frame the body of knowledge.Item Systematic bibliometric review of artificial intelligence technology in organizational management, development, change and culture(Vilnius Gedminas Technical University, 2022) Bilan, S.; Suler, P.; Скринник, Олена Вікторівна; Скрынник, Елена Викторовна; Skrynnyk, Olena Viktorivna; Krajnakova, E.; Васильєва, Тетяна Анатоліївна; Васильева, Татьяна Анатольевна; Vasylieva, Tetiana AnatoliivnaEven now, in the times of advanced digitization, the planning and implementation of many organizational measures remain human-driven. Corresponding to a global trend of application of artificial intelligence in all areas of life, it has received more attention in the last few years and garnered emerging clusters of research in usage of this technology for organizational issues. Some companies already offer tools that support different management tasks in the area of organizational development, but they are not holistic. According to the google trend analysis of the search for artificial intelligence, the inquiry to this topic continues increasing. The purpose of the described investigation was to identify the academic trends in research interaction between such scientific fields, as Artificial Intelligence, Organizational Management, Organizational Development, Organizational Change, and Organizational Culture using bibliometric and network publication analysis. In order to achieve this purpose, we systematically analysed 191 publications between 1983 and 2020 as well as cited and citing publications. The findings of this study provide important conclusions of the current research state. The insightful results are presented in the form of critical review and frame the body of knowledge.Item Neural network modeling of the economic and social development trajectory transformation due to quarantine restrictions during COVID-19(Centre of Sociological Research in co-operation with University of Szczecin (Poland); Széchenyi István University (Hungary); Mykolas Romeris University (Lithuania); Dubcek University of Trencín, Faculty of Social and Economic Relations (Slovak Republic), 2021) Васильєва, Тетяна Анатоліївна; Васильева, Татьяна Анатольевна; Vasylieva, Tetiana Anatoliivna; Кузьменко, Ольга Віталіївна; Кузьменко, Ольга Витальевна; Kuzmenko, Olha Vitaliivna; Kuryłowicz, M.; Летуновська, Наталія Євгенівна; Летуновская, Наталия Евгеньевна; Letunovska, Nataliia YevhenivnaThe article uses neural networks to model the effects of quarantine restrictions on the most important indicators of the country's socio-economic development. The authors selected the most relevant indicators and formed a specific sequence of its calculation to study the direction of transforming the trajectory of socio-economic development of a particular country due to quarantine restrictions. They used a multilayer MLP perceptron and networks based on radial basis functions. They chose BFGS and RBFT algorithms in neural network modeling. Collinearity study was the basis for data mining in terms of key factors of change. The author's approach is unique due to an iterative procedure of numerical optimization and quasi-Newton methods ("self-learning" and step-by-step "improvement" of neural networks). The model projected gross domestic product and the number of unemployed in the country affected by the COVID-19 pandemic over the three years.