A Dea based sorting approach for industrial R&D projects

Aker, Pınar
In this study, multicriteria sorting methods based on Data Envelopment Analysis (DEA) are developed to evaluate industrial Research and Development (R&D) projects proposed to Technology and Innovation Grant Programmes Directorate (TEYDEB) of the Scientific and Technological Research Council of Turkey (TÜBİTAK). Even though DEA is used extensively as a multicriteria decision making (MCDM) tool for ranking; to our knowledge, this study is the first attempt utilizing DEA for sorting purpose. A five level R&D project selection criteria hierarchy and an assisting point allocation guide with a scale of ten-points are derived to measure and quantify the performance of the proposals. The interval pairwise comparison matrices determined from the judgments of TEYDEB managers are used to obtain weight intervals from Analytic Hierarchy Process (AHP) model. These weights are employed as assurance region constraints. Motivated from the fact that derived criteria constitute inputs and outputs of R&D projects; DEA determining efficiencies based on inputs and outputs is utilized for sorting. Based on this approach, two threshold estimation models, PM1 and PM2, and five assignment models, APM1, APM2, APM3, APM4 and APM5, are proposed. The models are applied to a case study in which 60 projects are placed into four groups according to two reference sets composed of proposals from the year 2009. The well-known muticriteria sorting method, UTADIS, is also implemented for comparison. It is concluded that proposed methods are more stable than UTADIS and the integrated application of threshold estimation model PM2 and assignment model APM4 provides the best results.


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Citation Formats
P. Aker, “A Dea based sorting approach for industrial R&D projects,” M.S. - Master of Science, Middle East Technical University, 2010.