Assessment of the potential of the agro-industrial complex in a border region: diagnostics and substantiation of management decisions
Type:
Article
Pages:
from 513
to 518
Status:
In work
Received:
15.08.2026
Accepted:
15.08.2026
Published:
15.08.2026
Language:
Russian
Keywords:
agro-industrial complex, border region, diagnostics, economic potential, management methodology, gross regional product, business climate, Khabarovsk Krai, machine learning methods
Funding:
The research was funded through a competition for the implementation of expert analytical work in order to implement the development program of the Pacific National University.
Abstract:
The article examines methodological approaches to assessing the economic potential of the agro-industrial complex in the context of border regions of the Russian Federation. The necessity of updating existing methods to account for the specific characteristics of border territories is substantiated. The theoretical framework of the study is based on an analysis of scientific publications in the fields of regional economics and industry development management. The empirical part is based on data from Khabarovsk Krai as a typical border region of the Far Eastern Federal District, using statistical data for the period 2014-2025. The research methodology includes regression modeling and machine learning methods implemented in the Rstudio environment. The content of the concept "agro-industrial complex potential of a border region" is clarified, encompassing resource, scientific-technical, investment, economic, and digital components. The conducted diagnostics revealed a high degree of linear relationship between the gross regional product and the development indicators of the agro-industrial complex (multiple R=0.99, R²=0.98), with the volume of agricultural output exerting the most significant influence. The study identified systemic challenges constraining the development of the agricultural sector in border territories: reduced technical capacity (a 71% decrease in the number of tractors), investment deficit (lack of investment in fixed capital in 2020-2025), climatic constraints, import dependence, insufficient development of land reclamation, withdrawal of land from agricultural use, including due to the lack of up-to-date information on land owners. The results can be applied by public authorities in the development of regional agricultural development programs and in substantiating management decisions aimed at increasing the contribution of the agricultural sector to the economy of border regions and fostering a favorable business climate.
The article examines methodological approaches to assessing the economic potential of the agro-industrial complex in the context of border regions of the Russian Federation. The necessity of updating existing methods to account for the specific characteristics of border territories is substantiated. The theoretical framework of the study is based on an analysis of scientific publications in the fields of regional economics and industry development management. The empirical part is based on data from Khabarovsk Krai as a typical border region of the Far Eastern Federal District, using statistical data for the period 2014-2025. The research methodology includes regression modeling and machine learning methods implemented in the Rstudio environment. The content of the concept "agro-industrial complex potential of a border region" is clarified, encompassing resource, scientific-technical, investment, economic, and digital components. The conducted diagnostics revealed a high degree of linear relationship between the gross regional product and the development indicators of the agro-industrial complex (multiple R=0.99, R²=0.98), with the volume of agricultural output exerting the most significant influence. The study identified systemic challenges constraining the development of the agricultural sector in border territories: reduced technical capacity (a 71% decrease in the number of tractors), investment deficit (lack of investment in fixed capital in 2020-2025), climatic constraints, import dependence, insufficient development of land reclamation, withdrawal of land from agricultural use, including due to the lack of up-to-date information on land owners. The results can be applied by public authorities in the development of regional agricultural development programs and in substantiating management decisions aimed at increasing the contribution of the agricultural sector to the economy of border regions and fostering a favorable business climate.
Keywords:
agro-industrial complex, border region, diagnostics, economic potential, management methodology, gross regional product, business climate, Khabarovsk Krai, machine learning methods
agro-industrial complex, border region, diagnostics, economic potential, management methodology, gross regional product, business climate, Khabarovsk Krai, machine learning methods
