This paper proposes a quantitative model for balancing and optimizing portfolio of R&D projects. The model focuses on two dimensions of uncertainty -- market and technical - to formulate R&D portfolio budget allocation problem. The investment is broken into two critical stages, namely R&D phase and commercialization phase. The real options analysis is then employed to allow for management flexibility, such as to defer the investment or to stop and later restart the investment costlessly. We utilize Monte- Carlo simulation technique to illustrate the model calculation using Gillette''s MACH3 numerical data. The simulation and sensitivity analysis results, which are studied through risk-return tradeoff, offer comparison and recommendation of an optimal portfolio management of R&D investment projects.
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