Ar-Ge projelerinin bulanık çok ölçütlü karar verme teknikleri kullanılarak değerlendirilmesi

In recent years, global competitive environment leads many organizations to venture in research and development activities. Thus, R&D project selection constitutes a significant part of project management in order to achieve the desired results and outputs. In the literature, several studies employed different methods to determine the most adequate R&D project alternative. In this thesis, hierarchical fuzzy multi-criteria decision making (MCDM) method and fuzzy integral (FI) method are employed to determine the most suitable R&D project for R&D center of a firm working on a project-oriented in the machinery manufacturing sector. The proposed project selection framework consists of six main criteria as technological, environmental, marketing, organizational, national benefits and financial issues, and 27 sub-criteria. Eight project alternatives are evaluated considering data obtained from four decision makers. Ordered weighted average (OWA) aggregation method is used for aggregating decision makers' opinions. The results obtained from hierarchical fuzzy MCDM and FI methodologies are compared and analyzed.