METHODOLOGICAL FRAMEWORK FOR ASSESSING SUSTAINABLE RURAL DEVELOPMENT

Abstract

Purpose. The purpose of the study is to improve the methodological framework for assessing sustainable rural development in Ukraine. Methods. The methodological foundation is formed by systemic and interdisciplinary approaches to the cognition of sustainable development processes. The study employs a set of general scientific and specialised methods, including abstract-logical, structural-functional, and index methods, as well as techniques of normalisation, standardisation, and weighting of indicators. Results. An original integral model for assessing sustainable rural development is substantiated, based on a four-dimensional structure: economic, social, environmental, and institutional. A system of indicators and an algorithm for calculating the integral index of sustainable rural development have been developed, encompassing the stages of data collection, normalisation, weight determination, sub-index aggregation, and territorial classification. The introduction of an adjustment security coefficient is proposed, accounting for the impact of military and technogenic threats. The expediency of applying machine learning methods to identify non-linear relationships, threshold effects, and inter-factor interactions within the system of sustainable rural development of rural areas is demonstrated. Approaches to the typologisation of rural territories by sustainability levels and to the formation of differentiated managerial development strategies have been refined. The relevance of machine learning methods for detecting non-linear dependencies, threshold effects, and cross-factor interactions within the sustainable development system is further confirmed. Conclusions. A comprehensive methodological framework for the integral assessment of sustainable rural development has been formed, combining a multi-level indicator approach, tools of explainable analytics, and adaptation to the conditions of martial law and post-war recovery. The practical significance of the methodology lies in its applicability by public administration bodies for monitoring disparities, prioritising investments, strategic planning, and shaping differentiated rural development policies. Prospects for further research are associated with the approbation of the proposed model at the level of territorial communities, expansion of the spatial-statistical database, and integration of GIS and digital analytical decision-support platforms.