Abstract
Research management requires practical and effective decision tools to support selection of investment alternatives. In recent years, many research organizations have changed from a discipline orientation to a focus on integrated programs and related outcomes. For managers of these high-profile research programs, it is critical to understand which activities are most important, considering both technical impact and cost-effectiveness. This article proposes a model that integrates quality function deployment and data envelopment analysis to perform this essential task. Based on information from these two decision science tools, the model develops a two-axis evaluation space for research alternatives. By locating particular activities in this decision space, a program manager can compare and prioritize alternative research investments.
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