A study for allocating resources to research and development programs by integrated fuzzy DEA and fuzzy AHP

Abstract

A decision model is developed to help managers select the most appropriate sequences of plans for product research and development (R&D) projects under strict constraints on budget and resources. In recent years, many organizations have changed from discipline-oriented to focusing on integrated programs and related outcomes. For a decision-maker of these high-profile R&D programs, it is critical to understand which activities are the most important, considering both investment feasibility and cost-effectiveness. This paper proposes a two-dimensional decision model that integrates fuzzy data envelopment analysis and analytic hierarchy process to perform this essential task. Using the 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. © 2011 Academic Journals.