The Real Options Method in Innovation Project Evaluation: Gaps and Modification (Upravlenets)

Summary

• The study combines a bibliometric analysis of 246 international Scopus publications for 2023–2026, a thematic analysis of 62 articles and a comparison with 61 Russian eLibrary publications.p.1
• The Russian search found 243 publications, narrowed to a final sample of 61 after screening.p.3
• Keyword co-occurrence maps identified six thematic clusters of international research and six of Russian research.p.1
• Four types of uncertainty and four categories of evaluation objects were systematized, with three directions of hybridization of the method.p.1
• Ignoring at least one of the uncertainty factors understates a project's option value by 25–40%.p.11
• Thematic analysis of the 62 most relevant articles produced six content clusters.p.4

Key insights

1. Discounted cash flow methods cannot capture managerial flexibility, which becomes critical for innovation projects with long horizons and irreversible costs.p.2
2. The cluster on digital assets and new evaluation objects was practically absent from publications before 2023.p.4
3. International studies use a detailed typology of uncertainty (EPU, CPU, GPR, technological), while Russian works use a generalized category.p.6
4. Classical real options theory relied on geometric Brownian motion, risk neutrality and homogeneous agents.p.6
5. Evaluation objects now include R&D and patents, green and climate innovations, digital assets and AI, and ESG investments.p.7
6. Behavioral factors and institutional context of developing markets are largely ignored by existing models.p.8
7. The proposed modification combines a composite uncertainty index with game theory, multi-criteria analysis and machine learning.p.12