Authors:
Olena Vasyl’yeva
1
;
Lidiia Horoshkova
2
;
Denis Morozov
1
and
Olena Trokhymets
3
Affiliations:
1
Department of International Tourism and Economics, National University «Zaporizhzhia Polytechnic», 64 Zhukovskoho Street, Zaporizhzhia, Ukraine
;
2
Department of Environmental Studies, National University of «Kyiv-Mohyla Academy», Kyiv, Ukraine
;
3
Department of National Economy, Marketing and International Economic relations, Classic Private University, 70b Zhukovskoho Street, Zaporizhzhia, Ukraine
Keyword(s):
Agricultural Sector, Labour Potential, Sustainable Development, Labour Productivity, Artificial Neural Network.
Abstract:
Sustainable development paradigm is a combination of economic, social and environmental components represented by a significant number of interconnected factors. Their comprehensive impact determines the ways and dynamics of achieving sustainable development goals. Sustainable development forecasting is accompanied by the analysis and processing of a significant set of indicators and requires special methods of data processing. The neural network modelling allowed to form a multifactorial impact model on the final indicator, namely labour productivity, according to the sustainable development goals. The proposed model allows not only to model and forecast, based on the previously obtained indicators and their dynamics, but also to set target benchmarks to obtain a range of possible scenarios of system development, which depends on the forecasting conditions and parameters. They do not only increase the validity of managerial decision-making, but also ensures relevant adaptation of th
e management object to the changing environment, affects not only the final result, but also the process of its achievement, including optimization of sustainable development levers.
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