Abstract
<jats:p>In this article, the author discusses the development of an econometric model for the spatial distribution of resources for logistics communication in the Arctic zone, taking into account sustainable development factors. The proposed approach aims to improve the efficiency of material and technical flow distribution and optimize logistics routes in conditions of high uncertainty, significant spatial differentiation, and specific natural and climatic constraints. The study substantiates the choice of explanatory variables that reflect economic, infrastructural, and institutional aspects, as well as sustainability indicators: environmental risks, socioeconomic impact, and sustainability of supply chains. Spatial econometrics (including the consideration of spatial autocorrelation and heterogeneity) is used to describe spatial relationships, allowing for more accurate estimation of the impact of factors on consumption levels and resource distribution across territorial units. Based on data from the Arctic regions, a model is formed and calibrated, its adequacy and interpretability are assessed, and scenarios are analyzed to support decision-making in the field of logistics and transport infrastructure. The practical significance of this work lies in the possibility of using the model to predict resource needs, select optimal logistics communication routes, and form resource programs that are focused on sustainable development goals. The research results can be used to develop regional infrastructure development programs and support management decisions in the field of Arctic logistics, as well as to plan logistics and distribute resource flows between Arctic territories, support decision-making in regional and federal sustainable development policies, including consideration of environmental constraints and socio-economic effects. when choosing logistical solutions, substantiating investment projects, optimizing budgets and improving the efficiency of public procurement (state support) in terms of providing the northern territories, forecasting resource needs and forming supply schedules, in scientific research and analytical reports: as a methodological basis for further research on spatial econometrics and sustainable logistics in the Arctic.</jats:p>