METHODS AND TOOLS FOR EARLY DIAGNOSTICS OF THE COMMERCIAL POTENTIAL OF KNOWLEDGE
Abstract
The article presents a comprehensive analysis of methods and tools for early diagnostics of the commercial potential of knowledge in the context of improving the efficiency of innovation activities of enterprises and organizations in Ukraine, particularly under conditions of limited financial, human, and infrastructure resources. Key assessment approaches are examined, including: determination of technological maturity considering technical, market, and regulatory parameters; financial and economic analysis of profitability and payback; integrated models with decision-making control points; multi-criteria methods and fuzzy logic tools for working with incomplete data; and digital technologies such as AI and Big Data. A review of scientific sources revealed that existing approaches mainly focus on evaluating already developed innovative products, while early diagnostics methods for knowledge remain insufficiently explored. The international experience of the top countries in the Global Innovation Index is analyzed, and possibilities for its adaptation to Ukrainian realities, considering the needs of small and medium-sized businesses, are identified. Five core methods of early diagnostics are systematized, and the feasibility of their combined application to achieve a balance between speed, cost, and evaluation accuracy is substantiated. A conditional modeling of costs for separate and combined application of these methods demonstrated a saving effect of up to 19% due to data reuse, shared infrastructure, and interdisciplinary teams. It is emphasized that early diagnostics enables timely identification of knowledge with the highest commercial potential, improves the accuracy of selecting promising ideas, reduces risks, shortens time-to-market, and accelerates the commercialization of research results. Recommendations are proposed for developing a national adaptive methodology for early diagnostics integrated into “university–business” partnerships to ensure more effective management of innovation projects and increase the return on investment in knowledge.
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