METHODICAL APPROACHES TO INFORMATION SUPPORT AND ASSESSMENT OF REGIONAL SUSTAINABLE DEVELOPMENT

Abstract

Objective. To develop methodological approaches to information support and assessment of sustainable development in the region and to test them using the example of the ecological state of the Volyn region. Methods. The methodological foundation of sustainable development assessment is based on a systematic approach, emphasizing the interconnection of indicators characterizing the social, economic, and ecological development of a region. The testing of the methodology employs a set of key indicators for the ecological subsystem. The assessment methodology encompasses three levels of indicator aggregation: basic indicators reflecting the state of the ecological subsystem of the region based on statistical data; aggregated indicators derived from multiple basic indicators, enabling the assessment of related groups (macro-indicators) within the subsystem; integrated indicators formed from aggregated indicators, allowing for a comprehensive evaluation of the ecological subsystem’s condition. Regression models were developed to analyze the dependencies between indicator changes over time. The coefficient of determination (R2) was used as a criterion for evaluating the model’s reliability and its ability to explain indicator variation. Results. The article advances methodical approaches for assessing regional sustainable development by integrating systematic and hierarchical approaches with a multi-level structure for aggregating basic indicators. This development is based on a review and synthesis of the work of domestic and international scholars. The methodology for sustainable development assessment was tested using the ecological state of Volyn region. Aggregated indicators of the ecological subsystem include: air quality; land and nature reserves; water resource utilization; drinking water quality; and waste management. Results of ecological development modeling for Volyn region are presented, including regression equations and R2 values, based on the analysis of 23 indicators. The results demonstrate medium to high levels of the coefficient of determination, validating the models’ suitability for forecasting. Calculations show that after normalizing the basic indicators and aggregating them into integrated indicators, the ecological development index (I1) for Volyn region is evaluated as satisfactory, with a value of 0.59. Conclusions. The regression analysis identified key patterns and trends in the ecological subsystem of Volyn region during 2000–2020. Notably, there is a gradual improvement in air and water quality, while land resource conditions and waste management remain challenging. The high R2 values of the regression models confirm the reliability of the results and their applicability for regional development forecasting. The integrated ecological development indicator for Volyn region allows its state to be assessed as satisfactory. These findings are significant for forming sustainable development strategies for Volyn Region, highlighting key areas for interventions aimed at balancing social, economic, and ecological components.