Fuzzy regression model of R&D project evaluation

Engineering and technology play an important role in strengthening the competitive power of a company and in surviving a severe competition in the world. About 70% of the total R&D investment in Japan comes from the private sector. It is the most important to decide which research projects have to be adopted for a future research out of proposals from divisions and sections in a company. The objective of this paper is to analyze the results of experts’ evaluation in selecting submitted proposals for R&D and to model the experts’ evaluation. This paper analyzes a research and development of a certain manufacturing company in a heavy metallurgy industry. We employed a principal component model, dual scaling, AHP and fuzzy regression analysis to analyze the results that experts evaluated proposed research projects for single or plural of fiscal years. The experts’ evaluation was pursued on the basis of (1) the objective of a research project, (2) its background, (3) its research contents, (4) the expected effect, (5) the possibility of obtaining patents, (6) project schedule, (7) developing cost, etc. The obtained model results in the same selection of projects as the experts did. # 2007 Elsevier B.V. All rights reserved.