Investment attractiveness of the enterprise under conditions of uncertainty: integration of risk management and growth strategy

Анотація

Purpose. The purpose of this article is to develop a conceptual framework for integrating Enterprise Risk Management (ERM) and growth strategies to enhance the investment attractiveness of enterprises under conditions of uncertainty and risk. Methodology of research. The study is based on the development of a comprehensive methodology for assessing the investment attractiveness of enterprises in uncertain and risky environments, combining several modern analytical approaches. The core of the methodology is an integral investment attractiveness index, constructed on the basis of financial, market, production, innovation, and ESG indicators. Unlike traditional indices, the proposed model applies dynamic weights determined through the Analytic Hierarchy Process (AHP) with elements of fuzzy logic, which allows incorporating expert evaluation and adapting the significance of individual criteria in response to changes in the external environment. To model the effects of uncertainty, the Monte Carlo method was employed, enabling the estimation of ranges of possible values for key indicators and the probability of achieving a certain level of investment attractiveness. Additionally, scenario analysis was conducted, generating three development scenarios for each enterprise: optimistic, inertial, and pessimistic. Findings. The research results can be applied in the formation of industry-level strategies, the development of investment programs, and the design of state policies aimed at supporting key sectors of the economy. Future studies may focus on the integration of macroeconomic indicators, the application of machine learning models to forecast the investment attractiveness index, and the expansion of the research base to include enterprises from other industries. Originality. The scientific novelty of the research lies in the combination of several elements: the integration of classical index-based methods with modern machine learning algorithms and fuzzy logic; the incorporation of scenario-based and stochastic modeling into the core calculation procedure; and the use of adaptive weighting of criteria based on predictive efficiency, which enables synchronization of the assessment with real changes in the enterprise environment. Practical significance of research results. The proposed methodology provides a comprehensive assessment of enterprise investment attractiveness under uncertainty by combining tools of financial analysis, risk management, and strategic forecasting. Its practical application allows investors and managers to make more informed decisions, taking into account not only the current state but also potential risks and opportunities for development.

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