FUZZY-TENSOR MODELLING OF RISKS IN PUBLIC-PRIVATE PARTNERSHIP PROJECTS FOR SUSTAINABLE RURAL DEVELOPMENT

Abstract

The purpose of this article is to develop and validate a multidimensional fuzzy-tensor model for the assessment and forecasting of the aggregate risks of public-private partnership projects for sustainable rural development, based on the integration of natural and climatic, market, financial, institutional and legal, and technological factors, taking into account their correlation interaction, regional asymmetry, and scenario dynamics. The article examines the issues of risk assessment and management in public-private partnership projects for sustainable rural development under conditions of high uncertainty, climate change, market volatility, and institutional instability. The limitations of traditional linear and deterministic approaches to risk analysis are substantiated, as they fail to capture the multidimensional and cumulative nature of the interaction between natural and climatic, financial and economic, market, institutional and legal and technological factors. A fuzzy-tensor model for assessing the overall risk environment is proposed, combining tools of economic and mathematical modelling, fuzzy set theory, and scenario analysis. An integral risk index is developed, enabling a comparative assessment of the investment acceptability of public-private partnership projects with due regard to regional asymmetry, the correlation interaction among specific risk groups, and the non-linear effects of their combined impact on financial performance. The empirical basis of the study is formed using statistical data from the ERA5 climate reanalysis, indicators of price, exchange rate and inflation dynamics, as well as expert assessments of the institutional and market environment of Ukraine’s agricultural sector. Scenario modelling is conducted for typical infrastructure, logistics, processing and irrigation projects, which makes it possible to quantify the expected losses in efficiency and identify critical risk zones. The findings confirm the expediency of applying differentiated mechanisms for risk allocation between public and private partners, strengthening the role of insurance and guarantee instruments, and integrating climate adaptation and financial stabilisation measures into the contractual architecture of public-private partnerships for sustainable rural development.