A Model for Allocating Resources to Research Programs by Evaluating Technical Importance and Research Productivity

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.