International Conference on Technology, Engineering and Science (IConTES), Antalya, Türkiye, 16 - 19 Kasım 2022, cilt.21, sa.28, ss.218-227
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.