INNOVATION-INVESTMENT PROJECT AS A FACTOR OF ENTERPRISE DEVELOPMENT: RISK OPTIMISATION AND EFFICIENCY CRITERIA - Polozova, Tetiana; Khudiakov, Denys (Current Problems of Sustainable Development, 2026)
The article examines the theoretical and methodological foundations of an innovation-investment project as a factor of enterprise development. The relevance of the topic is determined by the low innovation activity of domestic enterprises (7.2% in 2022), critically low expenditure on R&D (0.3% of GDP), and the need for post-war recovery of the Ukrainian economy. Scientific approaches to the essence of an innovation-investment project are analysed, and its product, process, and organisational types are identified. The main groups of risks (financial, technological, institutional, personnel, and market) are systematised, and the most critical among them are determined. A strategic-target risk management model is proposed, which includes five consecutive stages: identification, assessment, selection of management methods, implementation of measures, and monitoring of effectiveness. A system of efficiency criteria for an innovation-investment project is developed, covering economic, innovation, social, and environmental indicators. An integral efficiency index based on the multiplicative aggregation of four components is proposed. A conceptual scheme of integral assessment is presented, which allows for informed management decisions. The necessity of applying digital tools (artificial intelligence, big data analytics) for risk forecasting and reduction is substantiated. It is proved that effective innovation-investment policy requires synergy between the internal resources of an enterprise and external conditions. The conclusions of the article can be used in the development of enterprise innovation development strategies and the improvement of state support for innovative business. Prospects for further research lie in the development of sectoral efficiency assessment methodologies, improvement of risk forecasting tools using artificial intelligence, and investigation of the impact of integration processes with the EU on innovation-investment activity.