Contingent Portfolio Programming for the Management of Risky Projects

Methods for the selection of a research and development (R&D) project portfolio have attracted considerable interest among practitioners and academics. However, these methods have found limited use in practice, partly because they have encountered difficulties in capturing uncertainties and interdependencies related to R&D projects. Motivated by these difficulties, we develop Contingent Portfolio Programming (CPP) which extends earlier approaches in that it (1) uses states of nature to capture external uncertainties, (2) models resources through dynamic state variables, and (3) provides explicit guidance for the selection of a portfolio which is compatible with the decision maker’s risk attitude. While CPP is framed here in the context of R&D project portfolios, it is applicable to a variety of investment problems where the dynamics and interactions of investment opportunities must be accounted for. (Research and development, project selection; Decision analysis, theory; Programming, linear, applications)