Risk and uncertainty in the patent race: a probabilistic model

This article develops a novel probabilistic approach to evaluate, through an approximation, a patent-protected R&D project at a fixed date under very general conditions. In a real options framework, we introduce spatial mixed Poisson processes to describe the dynamics of the project value. In such a fashion, the model is able to account for competition among firms and several sources of uncertainty such as time-to-completion of the project, exogenous shocks, input cost uncertainty, technical uncertainty and asymmetric information under different cost structures. The proposed evaluation procedure is of Bayesian type, in that it moves from a specific a-priori information on the phenomenon under scrutiny.