Optimal timing of partial outsourcing decisions

This article combines a real options approach to the optimal timing of outsourcing decisions with a linear programming technique for solving one-dimensional optimal stopping problems. We adopt a partial outsourcing model proposed by Y. Moon (2010) which assumes profit  flows to follow a geometric Brownian motion and explicitly takes into account the benets and costs of all eorts which a firm spends on the project prior to the outsourcing date. The problem of deciding when to outsource and how much efort to spend is solved when the underlying profit  flows or index processes are modeled by general one-dimensional diffusions. Optimal outsourcing times are proved to be of threshold type, and sensitivity results regarding market volatility and other quantities are derived. The corresponding optimal stopping problems are reformulated in terms of finnite dimensional linear programs and nonlinear optimization problems. These reformulations are exploited to prove sensitivity results in a novel way. Specific  management recommendations are provided.