R&D Project Portfolio Selection with Fuzzy Data Envelopment Analysis

Abstract

R&D investments are becoming increasingly important in the developing world. Companies with limited resources should make the most favorable investments for their own strategies. It is crucial that these investments are transferred to the right projects. It is difficult to make decisions in an environment where there are technical difficulties as well as uncertainties. At this point, it is necessary to decide which projects should be done and which projects should not be done. In this study, project portfolio selection that seeks a systematic solution to this decision, is covered. To solve this problem, data envelopment analysis that can evaluate the parameters without the need to build precedence relationship, is used. Parameters were set after a detailed research. Vagueness that is associated with difficulty of making precise judgment, was included in the model by introducing linguistic variables. Ambiguity that characterizes the situation where there are two or more alternatives, is defined with triangular fuzzy sets and α cut method. Different models are constructed for different extreme cases to solve the ambiguity. The models provide the optimal value regardless of the α value. A sample dataset of 30 projects is created to test the models and observe the results. Optimal parameters weights are found in the models. Full pairwise comparisons are considered while examining the interdependencies. These parameters weights are recalculated according to interdependencies. Using these weights, the efficiency score of each project is calculated for each model. Projects are prioritized for different strategies by using decision making under uncertainty.

Keywords

• Project portfolio selection
• Data envelopment analysis
• Fuzzy sets