05 April 2016
Many strategic business decisions revolve around economics of supply and demand. It can be difficult to fully capture such concerns within typical decision analysis models. The problem is that the language and methods of economic analysis makes key distinctions between real-valued variables and functions of real-valued variables, e.g., quantity supplied and demanded vs. supply and demand functions. In contrast, decision analytic modeling typically incorporates decision variables and random variables which have either nominal values or real values, consequences of which are then mapped to preferences with a utility function. To reconcile these approaches, we can create decision models where functions themselves are variables, e.g., an uncertain demand function. Such decision modeling builds on standard decision analytic techniques, but also presents some challenges. An illustration of this modified approach is its previous use on the problem of R&D portfolio selection for carbon abatement technologies. Currently, this approach may be useful in supporting decisions about emerging platform ecosystems.
Last edited: 31 March 2016
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