A Budget Allocation Model for Large Hierarchical R&D Organizations

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Abstract
A model is developed which allocates an available budget to research alternatives subject to budgetary constraints on both organizational and technical entities. The solution algorithm is based on the out-of-kilter minimum cost network flow algorithm and is programmed for use in a time-share, conversational mode. Although the model does not describe the decision processes observed empirically, its output is sufficiently similar to actual allocations that it can be viewed as predictive. Strengths and weaknesses of the model are detailed based on questionnaire and interview data provided by the potential users of the system. The decision information system is used to illustrate that experimentation concerned with better understanding of the adoption process can be used to facilitate model design and application.

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