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In the article we proved that rural tourism in a market economy is becoming increasingly important, because it helps to solve the problems of rural development, namely: the outflow of young people to cities, declining employment, low incomes of the rural population, and more. The purpose of the article is to study rural agritourism and substantiate the tourist potential of rural areas of Ukraine on the basis of sustainable development. In the process of studying the dynamics of rural green tourism in Ukraine, it was found that the number of farmsteads in Ukraine is increasing and the development of agritourism is intensifying. In the article we found that the saturation of rural tourist farmsteads is unevenly distributed throughout Ukraine, due to natural and climatic conditions, the presence of historical and cultural sites, and the preservation of ethnic traditions. In the article we proved that the development of rural green tourism not only helps to preserve and develop recreational areas in rural areas but also helps to solve socio-economic problems of the village, which reduces rural unemployment by attracting youth and the local population, reproduction of labour potential, slowing down migration processes in villages, increasing the level of infrastructure in the region, replenishing local rural budgets. [ABSTRACT FROM AUTHOR]

In the article we have substantiated and conducted statistically assess the impact of the final results of economic activity on the current socio-demographic situation of rural areas in Ukraine. Based on the results of determining the influence of conditioned factors on the level of labour migration of the rural population in Ukraine, we have developed a regression equation. Also, based on the results of the study, we built two cartograms, comparison of which provides an opportunity to assess the dynamics of the formation of the total fertility rate in rural areas (per 1 woman) for 2016 - 2020. We built a cartogram that visualizes the results of grouping regions of Ukraine by natural increase, decrease population in rural areas of Ukraine. The results of our study provide an opportunity to confirm that in the context of Ukraine's official accession to the European Union and the serious challenges of today, the Ukrainian state should perform the functions of regulating the most important spheres of society in general and rural areas in particular. The task of increasing the employment of the rural population should be raised to the level of state priorities, which would provide an opportunity to create new jobs for the rural population in industries that can provide the maximum competitive effect. [ABSTRACT FROM AUTHOR]

The European-wide environmental obstacles of inefficient and unsustainable recycling systems and flows constrain household waste (HW) management, endangering the circular economy. The European 2020 strategy and ongoing environmental disasters indicate the ineffectiveness of the current HW sustainability practices. This paper introduces an artificial intelligence (AI) approach for calculating urban residual waste, based on its generation level. It reforms the current diverse and high discrepancy levels of HW residual for EU-countries and Ukraine. Adopting a k-means clustering method with a multi-criteria taxonomic development level index (TIDL), it produces uniform clusters with higher accuracy and manageability. Findings discover and remedy opaque managerial practices, enabling sustainable and environment-friendly development at national and regional levels for EU-countries. Results reveal an increased number of clusters in crisis, contributing to a methodological reference for environmental planning. In conclusion, this AI approach could have a European-wide impact on sustainable economic value-chain, converging toward an eco-friendly economy. [Display omitted] • Analysis of household waste management strategies in EU and Ukraine. • A methodological reference for environmental planning that moves away from the current centralized model. • Implementation of k-means household waste clustering approach with situational analysis and planning. • AI clustering approach with a multi-criteria taxonomic index for higher accuracy and manageability of waste. • Exploration of integrated AI-development economics for EU-Ukraine environmental policy. [ABSTRACT FROM AUTHOR]