A fuzzy approach to government sponsored private sector R&D project selection problem

Governments fund R&D projects proposed by private sector for to make progress in technological advancements and increase competitiveness power of industry. Accordingly, public authorities come across a decision making problem while they select R&D projects eligible for public funding. In order to spend public funds efficiently and coordinate these funding mechanisms in line with science and technology policy, public authorities need to perform R&D project selection process ideally. This thesis study aims to examine evaluation criterias of government sponsored private sector R&D project selection problem, to build a network identifing interactions between these evaluation criterias and to assess to what extent these criterias are important in selection process. Within this framework, R&D project selection process of Industrial R&D Funding Program coordinated by The Scientific and Technological Research Council of Turkey is analyzed. Present studies propose to investigate interactions between evaluation criterias concerning R&D project selection problem and advise to use fuzzy analytic network process method. Because of the fact linguistic variables take the stage on R&D project selection process in order to quantify intangibles, government sponsored private sector R&D project selection problem studied in this thesis is modelled with a multi attribute decision making method- fuzzy analytic network process- and local and global weights of the evaluation criterias obtained with this model.