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This thesis is an application of decision analysis techniques to the problem of evaluating competing research and development investments and selecting the best portfolio from among the alternatives. In contrast to the current ad hoc approach, decision analysis provides an explicit and easily explained rationale for investment choices, complete and consistent incorporation of multiple objectives, and direct insight into the effects of uncertain investment returns. A hierarchical objective decomposition was used to capture the user's preference structure. The hierarchy was then used to develop a computer-based decision aid to allow the users to quickly and consistently evaluate technology investment options. The decision aid includes the ability to automatically perform several deterministic and probabilistic sensitivity analyses.
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