METHODOLOGICAL APPROACH TO EVALUATING INNOVATIVE PROJECTS IN THE CONTEXT OF DIGITAL TRANSFORMATION - Lytovchenko, Iryna; Kostin, Illia (Social Economics, 2025)
The paper examines the evolution of innovation evaluation methods, which is directly influenced by technological advancement and changes in the socio-economic environment. Initially, innovation activities were evaluated primarily from a financial perspective, using classic methods such as NPV, IRR, and Payback Period, focusing on economic feasibility but often neglecting the social and environmental impact. Modern approaches, however, are oriented towards a more holistic consideration of various factors, including intangible assets such as knowledge, ecological sustainability, and strategic significance. Digitalization, according to the authors, requires the integration of new methods such as multi-criteria analysis, which accounts for economic, social, environmental, and technological factors, as well as the creation of hybrid models that combine traditional financial tools and innovative approaches. Specifically, real options and digital twins provide flexible evaluation and forecasting, considering potential changes in the market and technology. The paper also highlights the limitations of traditional evaluation methods like NPV and IRR in the context of high uncertainty, typical of innovative projects. The study proposes a methodological approach for comprehensive evaluation of innovative projects based on the integration of financial, social, environmental, and technological factors, utilizing advanced digital technologies. Authors suggest a multi-step evaluation model, which includes multidisciplinary assessment of basic parameters, real options for evaluating strategic flexibility, and digital twins for real-time project implementation forecasting and optimization. These approaches allow for the consideration of dynamic market changes and provide more accurate and adaptive information for strategic decision-making. An interesting aspect of the study is the application of artificial intelligence and digital twins, which significantly enhance the precision of project evaluations and increase their adaptability to external changes. Through case studies of innovative projects, particularly in logistics process management, the paper demonstrates how the proposed methods allow for a comprehensive evaluation, taking into account financial indicators, ecological sustainability, and technological innovation. The results of the study highlight the necessity of integrated approaches to evaluating innovative projects, as digitalization and technological innovations dramatically transform the evaluation processes. These methods enable the creation of more adaptive and accurate models that account for a wide range of factors and can respond promptly to changes in the market environment, which is particularly crucial in the context of digital business transformation.