БАГАТОВИМІРНЕ ОЦІНЮВАННЯ СТАНУ СІЛЬСЬКОГО ГОСПОДАРСТВА УКРАЇНИ В РЕГІОНАЛЬНОМУ РОЗРІЗІ: ВИКЛИКИ ВІЙНИ ТА ШЛЯХИ ЗАБЕЗПЕЧЕННЯ РЕЗИЛЬЄНТНОСТІ
Ключові слова:
аграрний сектор, таксономічний аналіз, регіональний розвиток, резильєнтність, Україна, сільське господарство, стійкість, багатовимірне моделювання, економічна політика.
Анотація
У дослідженні проаналізовано стан аграрного сектора України, зокрема регіональні відмінності, що посилюються тривалою війною. Використано таксономічний аналіз для оцінювання та ранжування регіонів України за основними шістьма сільськогосподарськими показниками. Результати дослідження і висновки не тільки надають цінну інформацію для регіональної політики та орієнтованої підтримки у післявоєнному відновленні, але й підкреслюють важливість застосування підходів, заснованих на даних, для вирішення сільськогосподарських проблем у контексті геополітичної нестабільності; вказують на необхідність розробки адаптивних аграрних стратегій, що враховують регіональні особливості, забезпечуючи сталий розвиток сільського господарства в процесі відновлення України.
Посилання
Andriushchenko, K., Kovtun, V., Shergina, L., Rozhko, O., & Yefimenko, L. (2020). Agro-based Clusters: A tool for effective management of regional development in the ERA of globalisation. TEM Journal, 9(1). 198-204.
2. Asheim, B.T. (2019). Smart specialisation, innovation policy and regional innovation systems: what about new path development in less innovative regions? Innovation: The European Journal of Social Science Research, 32(1). 8-25.
3. Bachev, H., Ivanov, B., & Sarov, A. (2021). Assessing governance aspect of agrarian sustainability in Bulgaria. Bulgarian Journal of Agricultural Sciences, 27(3). 429-440.
4. Bai, D., Ye, L., Yang, Z., & Wang, G. (2024). Impact of climate change on agricultural productivity: a combination of spatial Durbin model and entropy approaches. International Journal of Climate Change Strategies and Management, 16(4). 26-48.
5. Balakrishnan, S. (2019). Recombinant urbanization: Agrarian–urban landed property and uneven development in India. International Journal of Urban and Regional Research, 43(4). 617-632.
6. Bellon, M.R., Kotu, B.H., Azzarri, C., & Caracciolo, F. (2020). To diversify or not to diversify, that is the question. Pursuing agricultural development for smallholder farmers in marginal areas of Ghana. World Development, 125. 104682.
7. Biru, W.D., Zeller, M., & Loos, T.K. (2020). The impact of agricultural technologies on poverty and vulnerability of smallholders in Ethiopia: a panel data analysis. Social Indicators Research, 147(2). 517-544.
8. Boiko, V., Kwilinski, A., Misiuk, M., & Boiko, L. (2019). Competitive advantages of wholesale markets of agricultural products as a type of entrepreneurial activity: the experience of Ukraine and Poland. Економiчний часопис-XXI, 175(1-2). 68-72.
9. Bulut, E., & Bayraktar, Y. (2023). Do Agricultural Supports Affect Production? A Panel ARDL Analysis of Turkey. Journal of Agricultural Sciences, 29(1). 249-261.
10. Chandio, A.A., Jiang, Y., Fatima, T., Ahmad, F., Ahmad, M., & Li, J. (2022). Assessing the impacts of climate change on cereal production in Bangladesh: evidence from ARDL modeling approach. International Journal of Climate Change Strategies and Management, 14(2). 125-147.
11. Ding, J., Liu, B., & Shao, X. (2022). Spatial effects of industrial synergistic agglomeration and regional green development efficiency: Evidence from China. Energy Economics, 112. 106156.
12. Donkoh, S.A., Azumah, S.B., & Awuni, J.A. (2019). Adoption of improved agricultural technologies among rice farmers in Ghana: A multivariate probit approach. Ghana Journal of Development Studies, 16(1). 46-67.
13. Elavarasan, D., & Vincent, P.D. (2020). Crop yield prediction using deep reinforcement learning model for sustainable agrarian applications. IEEE access, 8. 86886-86901.
14. Feng, W., Liu, Y., & Qu, L. (2019). Effect of land-centered urbanization on rural development: A regional analysis in China. Land Use Policy, 87. 104072.
15. Gururani, S. (2023). Cities in a world of villages: Agrarian urbanism and the making of India's urbanizing frontiers. Changing Asian Urban Geographies. 97-115.
16. Hrytsiuk, P., Babych, T., Baranovsky, S., & Havryliuk, M. (2023). Assessing of Climate Impact on Wheat Yield using Machine Learning Techniques. ICST. 314-329.
17. Jiang, H., Hu, H., Zhong, R., Xu, J., Xu, J., Huang, J., & Lin, T. (2020). A deep learning approach to conflating heterogeneous geospatial data for corn yield estimation: A case study of the US Corn Belt at the county level. Global change biology, 26(3). 1754-1766.
18. Kozin, I.V., Maksyshko, N.K., & Perepelitsa, V.A. (2020). A Fragmented Model for the Problem of Land Use on Hypergraphs. Cybernetics and Systems Analysis, 56(5). 753-757.
19. Loizou, E., Karelakis, C., Galanopoulos, K., & Mattas, K. (2019). The role of agriculture as a development tool for a regional economy. Agricultural Systems, 173. 482-490.
20. Mao, L., Huang, Y., Zhang, X., Li, S., & Huang, X. (2022). ARIMA model forecasting analysis of the prices of multiple vegetables under the impact of the COVID-19. Plos one, 17(7). e0271594.
21. Ntim-Amo, G., Qi, Y., Ankrah-Kwarko, E., Ankrah Twumasi, M., Ansah, S., Boateng Kissiwa, L., & Ruiping, R. (2022). Investigating the validity of the agricultural-induced environmental Kuznets curve (EKC) hypothesis for Ghana: Evidence from an autoregressive distributed lag (ARDL) approach with a structural break. Management of Environmental Quality: An International Journal, 33(2). 494-526.
22. Paul, P.K., Bhuimali, A., Sinha, R.R., Tiwary, K.S., Baby, P., Rajesh, R., & Chancellor, P. V. (2020). Big Data and Data Analytics in Agricultural Space: Towards Sustainable and Intelligent Agro Sector Development. Management of Data in AI Age. 95-120.
23. Rahmati, O., Falah, F., Dayal, K. S., Deo, R.C., Mohammadi, F., Biggs, T., & Bui, D.T. (2020). Machine learning approaches for spatial modeling of agricultural droughts in the south-east region of Queensland Australia. Science of the total environment, 699. 134230.
24. Reardon, T., Echeverria, R., Berdegué, J., Minten, B., Liverpool-Tasie, S., Tschirley, D., & Zilberman, D. (2019). Rapid transformation of food systems in developing regions: Highlighting the role of agricultural research & innovations. Agricultural systems, 172. 47-59.
25. Santika, T., Wilson, K.A., Budiharta, S., Law, E.A., Poh, T.M., Ancrenaz, M., & Meijaard, E. (2019). Does oil palm agriculture help alleviate poverty? A multidimensional counterfactual assessment of oil palm development in Indonesia. World Development, 120. 105-117.
26. Schrijver, R., Westerink, J., de Jong, K., Smit, B., van der Meer, R., & Dijkshoorn, M. (2022). Regional development and spatial use biodiversity and policy performance and impact agrosectors, green economy and landuse.
27. Shpak, N., Kulyniak, I., Gvozd, M., Vveinhardt, J., & Horbal, N. (2021). Formulation of development strategies for regional agricultural resource potential: The ukrainian case. Resources, 10(6). 57.
28. Storm, H., Baylis, K., & Heckelei, T. (2020). Machine learning in agricultural and applied economics. European Review of Agricultural Economics, 47(3). 849-892.
29. Teixeira, D.S.J.A., Koblianska, I., & Kucher, A. (2023). Agricultural production in Ukraine: An insight into the impact of the Russo-Ukrainian war on local, regional and global food security. Journal of Agricultural Sciences (Belgrade), 68(2). 121-140.
30. Trusova, N., Hryvkivska, O., Kepko, V., Prystemskyi, O., & Yavorska, T. (2020). Innovative development and competitiveness of agribusiness subjects in the system of ensuring of economic security of the regions of Ukraine. Rivista di Studi sulla Sostenibilita, 2. 141-156.
31. Vdovyn, M., & Zomchak, L. (2022). Export in services of Ukraine: pre-pandemic period, Covid-19 and war. Věda a perspektivy, 8(15). 48-57
32. Wang, M., Xu, M., & Ma, S. (2021). The effect of the spatial heterogeneity of human capital structure on regional green total factor productivity. Structural Change and Economic Dynamics, 59. 427-441.
33. Wen, Q., Wang, Y., Zhang, H., & Li, Z. (2019). Application of ARIMA and SVM mixed model in agricultural management under the background of intellectual agriculture. Cluster computing, 22. 14349-14358.
34. Zomchak, L., & Kukhotska, T. (2023). Wheat market price dynamics in Ukraine: quantitative exploration and forecasting. European Journal of Economics and Management, 4(9). 14-22.
35. Zomchak, L., Hakava, S. (2025). Unveiling Disparities and Resilience in Ukrainian Regional Labor Markets: Multidimensional Ranking Approach. Developments in Information and Knowledge Management Systems for Business Applications. Studies in Systems, Decision and Control, 578. Springer, Cham. https://doi.org/10.1007/978-3-031-80935-4_23
36. Zomchak, L., Kukhotska, T. (2025). Building Food Security Resilience in Ukraine: The Autoregressive Approach to Food Price Forecasting. Developments in Information and Knowledge Management Systems for Business Applications. Studies in Systems, Decision and Control, 578. Springer, Cham. https://doi.org/10.1007/978-3-031-80935-4_19
2. Asheim, B.T. (2019). Smart specialisation, innovation policy and regional innovation systems: what about new path development in less innovative regions? Innovation: The European Journal of Social Science Research, 32(1). 8-25.
3. Bachev, H., Ivanov, B., & Sarov, A. (2021). Assessing governance aspect of agrarian sustainability in Bulgaria. Bulgarian Journal of Agricultural Sciences, 27(3). 429-440.
4. Bai, D., Ye, L., Yang, Z., & Wang, G. (2024). Impact of climate change on agricultural productivity: a combination of spatial Durbin model and entropy approaches. International Journal of Climate Change Strategies and Management, 16(4). 26-48.
5. Balakrishnan, S. (2019). Recombinant urbanization: Agrarian–urban landed property and uneven development in India. International Journal of Urban and Regional Research, 43(4). 617-632.
6. Bellon, M.R., Kotu, B.H., Azzarri, C., & Caracciolo, F. (2020). To diversify or not to diversify, that is the question. Pursuing agricultural development for smallholder farmers in marginal areas of Ghana. World Development, 125. 104682.
7. Biru, W.D., Zeller, M., & Loos, T.K. (2020). The impact of agricultural technologies on poverty and vulnerability of smallholders in Ethiopia: a panel data analysis. Social Indicators Research, 147(2). 517-544.
8. Boiko, V., Kwilinski, A., Misiuk, M., & Boiko, L. (2019). Competitive advantages of wholesale markets of agricultural products as a type of entrepreneurial activity: the experience of Ukraine and Poland. Економiчний часопис-XXI, 175(1-2). 68-72.
9. Bulut, E., & Bayraktar, Y. (2023). Do Agricultural Supports Affect Production? A Panel ARDL Analysis of Turkey. Journal of Agricultural Sciences, 29(1). 249-261.
10. Chandio, A.A., Jiang, Y., Fatima, T., Ahmad, F., Ahmad, M., & Li, J. (2022). Assessing the impacts of climate change on cereal production in Bangladesh: evidence from ARDL modeling approach. International Journal of Climate Change Strategies and Management, 14(2). 125-147.
11. Ding, J., Liu, B., & Shao, X. (2022). Spatial effects of industrial synergistic agglomeration and regional green development efficiency: Evidence from China. Energy Economics, 112. 106156.
12. Donkoh, S.A., Azumah, S.B., & Awuni, J.A. (2019). Adoption of improved agricultural technologies among rice farmers in Ghana: A multivariate probit approach. Ghana Journal of Development Studies, 16(1). 46-67.
13. Elavarasan, D., & Vincent, P.D. (2020). Crop yield prediction using deep reinforcement learning model for sustainable agrarian applications. IEEE access, 8. 86886-86901.
14. Feng, W., Liu, Y., & Qu, L. (2019). Effect of land-centered urbanization on rural development: A regional analysis in China. Land Use Policy, 87. 104072.
15. Gururani, S. (2023). Cities in a world of villages: Agrarian urbanism and the making of India's urbanizing frontiers. Changing Asian Urban Geographies. 97-115.
16. Hrytsiuk, P., Babych, T., Baranovsky, S., & Havryliuk, M. (2023). Assessing of Climate Impact on Wheat Yield using Machine Learning Techniques. ICST. 314-329.
17. Jiang, H., Hu, H., Zhong, R., Xu, J., Xu, J., Huang, J., & Lin, T. (2020). A deep learning approach to conflating heterogeneous geospatial data for corn yield estimation: A case study of the US Corn Belt at the county level. Global change biology, 26(3). 1754-1766.
18. Kozin, I.V., Maksyshko, N.K., & Perepelitsa, V.A. (2020). A Fragmented Model for the Problem of Land Use on Hypergraphs. Cybernetics and Systems Analysis, 56(5). 753-757.
19. Loizou, E., Karelakis, C., Galanopoulos, K., & Mattas, K. (2019). The role of agriculture as a development tool for a regional economy. Agricultural Systems, 173. 482-490.
20. Mao, L., Huang, Y., Zhang, X., Li, S., & Huang, X. (2022). ARIMA model forecasting analysis of the prices of multiple vegetables under the impact of the COVID-19. Plos one, 17(7). e0271594.
21. Ntim-Amo, G., Qi, Y., Ankrah-Kwarko, E., Ankrah Twumasi, M., Ansah, S., Boateng Kissiwa, L., & Ruiping, R. (2022). Investigating the validity of the agricultural-induced environmental Kuznets curve (EKC) hypothesis for Ghana: Evidence from an autoregressive distributed lag (ARDL) approach with a structural break. Management of Environmental Quality: An International Journal, 33(2). 494-526.
22. Paul, P.K., Bhuimali, A., Sinha, R.R., Tiwary, K.S., Baby, P., Rajesh, R., & Chancellor, P. V. (2020). Big Data and Data Analytics in Agricultural Space: Towards Sustainable and Intelligent Agro Sector Development. Management of Data in AI Age. 95-120.
23. Rahmati, O., Falah, F., Dayal, K. S., Deo, R.C., Mohammadi, F., Biggs, T., & Bui, D.T. (2020). Machine learning approaches for spatial modeling of agricultural droughts in the south-east region of Queensland Australia. Science of the total environment, 699. 134230.
24. Reardon, T., Echeverria, R., Berdegué, J., Minten, B., Liverpool-Tasie, S., Tschirley, D., & Zilberman, D. (2019). Rapid transformation of food systems in developing regions: Highlighting the role of agricultural research & innovations. Agricultural systems, 172. 47-59.
25. Santika, T., Wilson, K.A., Budiharta, S., Law, E.A., Poh, T.M., Ancrenaz, M., & Meijaard, E. (2019). Does oil palm agriculture help alleviate poverty? A multidimensional counterfactual assessment of oil palm development in Indonesia. World Development, 120. 105-117.
26. Schrijver, R., Westerink, J., de Jong, K., Smit, B., van der Meer, R., & Dijkshoorn, M. (2022). Regional development and spatial use biodiversity and policy performance and impact agrosectors, green economy and landuse.
27. Shpak, N., Kulyniak, I., Gvozd, M., Vveinhardt, J., & Horbal, N. (2021). Formulation of development strategies for regional agricultural resource potential: The ukrainian case. Resources, 10(6). 57.
28. Storm, H., Baylis, K., & Heckelei, T. (2020). Machine learning in agricultural and applied economics. European Review of Agricultural Economics, 47(3). 849-892.
29. Teixeira, D.S.J.A., Koblianska, I., & Kucher, A. (2023). Agricultural production in Ukraine: An insight into the impact of the Russo-Ukrainian war on local, regional and global food security. Journal of Agricultural Sciences (Belgrade), 68(2). 121-140.
30. Trusova, N., Hryvkivska, O., Kepko, V., Prystemskyi, O., & Yavorska, T. (2020). Innovative development and competitiveness of agribusiness subjects in the system of ensuring of economic security of the regions of Ukraine. Rivista di Studi sulla Sostenibilita, 2. 141-156.
31. Vdovyn, M., & Zomchak, L. (2022). Export in services of Ukraine: pre-pandemic period, Covid-19 and war. Věda a perspektivy, 8(15). 48-57
32. Wang, M., Xu, M., & Ma, S. (2021). The effect of the spatial heterogeneity of human capital structure on regional green total factor productivity. Structural Change and Economic Dynamics, 59. 427-441.
33. Wen, Q., Wang, Y., Zhang, H., & Li, Z. (2019). Application of ARIMA and SVM mixed model in agricultural management under the background of intellectual agriculture. Cluster computing, 22. 14349-14358.
34. Zomchak, L., & Kukhotska, T. (2023). Wheat market price dynamics in Ukraine: quantitative exploration and forecasting. European Journal of Economics and Management, 4(9). 14-22.
35. Zomchak, L., Hakava, S. (2025). Unveiling Disparities and Resilience in Ukrainian Regional Labor Markets: Multidimensional Ranking Approach. Developments in Information and Knowledge Management Systems for Business Applications. Studies in Systems, Decision and Control, 578. Springer, Cham. https://doi.org/10.1007/978-3-031-80935-4_23
36. Zomchak, L., Kukhotska, T. (2025). Building Food Security Resilience in Ukraine: The Autoregressive Approach to Food Price Forecasting. Developments in Information and Knowledge Management Systems for Business Applications. Studies in Systems, Decision and Control, 578. Springer, Cham. https://doi.org/10.1007/978-3-031-80935-4_19
Опубліковано
2025-02-26
Як цитувати
ZOMCHAK, L., & DYDA, A. (2025). БАГАТОВИМІРНЕ ОЦІНЮВАННЯ СТАНУ СІЛЬСЬКОГО ГОСПОДАРСТВА УКРАЇНИ В РЕГІОНАЛЬНОМУ РОЗРІЗІ: ВИКЛИКИ ВІЙНИ ТА ШЛЯХИ ЗАБЕЗПЕЧЕННЯ РЕЗИЛЬЄНТНОСТІ. Вісник Київського інституту бізнесу та технологій, 52(1), 22-38. https://doi.org/10.37203/kibit.2025.52(1).02
Розділ
Статьи
