The integration of Environmental, Social, and Governance (ESG) criteria in investment decision-making is increasingly critical for evaluating energy projects. This study develops a structured, quantifiable framework using the Fuzzy DEMATEL method to assess and rank ESG factors, addressing the limitations of traditional scoring-based models. The proposed methodology systematically identifies the most influential ESG criteria and accounts for their interdependencies, providing a more comprehensive decision-making tool. The analysis, based on expert evaluations, highlights the dominant role of renewable energy integration, resource efficiency, and risk management in determining project sustainability. The results demonstrate that the framework ensures a more transparent and adaptable assessment process, supporting both investors and policymakers in navigating complex energy investment landscapes. The study also establishes a scalable approach that can incorporate financial performance indicators, enhancing the practical applicability of ESG-based investment evaluation.

The stage of selecting creative ideas that have the prospect of further commercial use and can be used to create new products, services, or startups is one of the most complex and important stages of the innovation process. It is essential to take into account expert opinions and evaluations, often vague and ambiguous. The study aims to develop a methodological approach to measure the commercial potential of new product ideas based on fuzzy set theory and fuzzy logic. To this end, three calculation schemes are developed: the first two are based on fuzzy multicriteria analysis using Fuzzy SAW and Fuzzy TOPSIS methods, respectively; the third is based on building a logical-linguistic model with fuzzy expert knowledge bases and applying fuzzy inference using the Mamdani algorithm. Fuzzy numbers in triangular form with triangular membership functions are used to present linguistic estimates of experts and fuzzy data; the CoA (Center of Area) method is used to dephase the obtained values. For practical application of the proposed algorithm, the model is used as an Excel framework containing a general set of input expert information in the form of linguistic estimates and fuzzy data, a set of calculations using three schemes, and a set of defuzzification of the obtained results. The framework allows for simulation modeling depending on the modification of the list of defined evaluation criteria and their partial criteria, and adjustments to expert opinions. The developed methodological approach is suggested for the initial stages of the innovation process to facilitate the assessment of creative ideas and improve their implementation. AcknowledgmentThis scientific paper is published with the support of the International Visegrad Fund.

The article demonstrates that managing an enterprise’s strategic flexibility effectively is key to its competitiveness and market sustainability. The authors have developed a comprehensive model of strategic flexibility management of an agro-industrial enterprise operating in the Ukrainian agricultural market. This model integrates modern strategic analysis tools with fuzzy set theory, multicriteria evaluation, and fuzzy matrix analysis. Specifically, the Fuzzy PIPRECIA (PIvot Pairwise RElative Criteria Importance Assessment) method is used to prioritize the assessment directions of internal (ISF) and external (ESF) strategic flexibility. The Fuzzy Delphi method is used to harmonize expert opinions. In contrast, the Fuzzy SAW (Simple Additive Weighting) method, incorporating a 7-level term set, triangular fuzzy numbers, and triangular membership functions, calculates the fuzzy values of ISF and ESF levels. Based on the constructed ”ISF – ESF” fuzzy matrix, generalized recommendations for improving and managing the enterprise’s strategic flexibility are proposed. Considering the specifics of the studied agro-industrial enterprise’s activities and expert assessments for each component of its internal and external flexibility, a list of refined proposals, initiatives, and measures to enhance its strategic flexibility has been formulated. First published online 4 March 2026

A stratification model of enterprise strategies on the basis of tools of fuzzy set theory and fuzzy matrix analysis was developed. Classic methods of strategic diagnostics of the company, fuzzy methods of multi-criteria evaluation (Fuzzy Extension of Simplified Best-Worst Method (Fuzzy SBWM) and Fuzzy SAW) and fuzzy matrices were used to achieve the goals set. The classic Quantitative Strategic Planning Matrix (QSPM) criteria were used to make a strategic choice. The developed model is based on defined term sets of expert linguistic assessments (8-level – for determining the importance of SWOT factors and 7-level – for evaluating strategic alternatives) with their subsequent conversion into fuzzy numbers with triangular membership functions. The Fuzzy SBWM was used to calculate the importance of SWOT factors for each area of analysis, and the Fuzzy SAW method was used to determine the fuzzy integral evaluations of strategic alternatives for these areas. Strategic alternatives were positioned in fuzzy matrices “O – T” and “S – W” using the α-section. Stratification of strategies is based on the superposition of fuzzy matrices and the application of production rules for the obtained integral fuzzy estimates of strategic alternatives. The framework has been developed in the Excel software application to carry out calculations according to this approach, which contains the following components: a block for entering linguistic expert information (for each direction of analysis and evaluation of strategic alternatives) and transforming these linguistic data into fuzzy numbers in a triangular form, a block for calculating factor weighting coefficients by best and worst approaches and their fuzzy integral values, a block for calculating fuzzy values of strategies in the directions of “opportunities-threats” and “strengths-weaknesses” at different values of α-section, a block of production rules for stratification of strategies to carry out calculations according to this approach. The methodical approach enables the top management of the enterprise to determine the weighting coefficients of the SWOT factors and identify the list of preferable strategic alternatives for implementation.