FORMATION OF A KPI SYSTEM FOR ASSESSING THE EFFECTIVENESS OF AGRIBUSINESS SOCIAL RESPONSIBILITY

Abstract

The article substantiates a system of key performance indicators (KPIs) for assessing agribusiness social responsibility in the context of rural development. The relevance of the study is determined by the influence of agricultural enterprises on employment, local budgets, natural resources, and rural communities, as well as by the need to adapt ESG and sustainability assessment approaches to the sectoral and territorial characteristics of agribusiness. The purpose of the study is to develop a KPI system and a methodological approach to evaluating social responsibility performance and the contribution of agricultural enterprises to rural development. The research is based on the generalization and comparative analysis of scientific approaches, international sustainability standards, and reporting frameworks, together with the systematization of indicators relevant to agribusiness and its stakeholders. The methodology includes normalization of heterogeneous indicators to a scale from 0 to 1, calculation of integrated scores for individual blocks, and their aggregation into an overall social responsibility performance index. The assessment system comprises five blocks: social, economic, environmental, stakeholder, and institutional. Each block includes five indicators, resulting in 25 KPIs. A model calculation based on conditional data demonstrates KPI normalization, calculation of block scores, and determination of the integrated index. The resulting value of 0.74 corresponds to a high level according to the proposed five-level interpretation scale and is used only to illustrate the calculation procedure, not to characterize a specific enterprise. The practical significance of the approach lies in its potential use for monitoring social responsibility performance, comparing assessment blocks and enterprises of different scales, identifying areas that require improvement, and supporting management decisions related to rural communities. Further research should focus on empirical testing using actual data from agricultural enterprises, refinement of weighting coefficients, and substantiation of normative or target normalization thresholds.