(A) study on scoring models for R&D project evaluation and selection

Abstract

This study was undertaken to provide the decision-maker(s) with an optimum scoring model for R & D project evaluation and selection. The development and utilization of models in the R \& D project innovation process of the technologically based organizations are discussed. Four types of scoring models for the formation of the project score are formulated, i.e., according to the combinations of the super-factors score formation methods and the sub-factors score formation methods, an additive-additive, an additive-multiplicative, a multiplicative-additive, and a multiplicative-multiplicative model. Two kinds of factors weighting methods, "rank" weighting and "score" weighting methods, are also analyzed for use in the above four types of scoring models. An optimum scoring model for R \& D project evaluation and selection decision is selected from the above four types of scoring models which are applied to the real situation in the Korea Institute of Science and Technology. In the proposed optimum scoring model, five super-factors and twenty seven sub-factors are identified to be the most important, and it is suggested that "rank" weighting method is more convenient that "score" weighting method considering the almost same results. It is also suggested that an additive-multiplicative scoring model be used for R \& D project evaluation and selection at the exploratory and advanced stages. In this study, five super-factors which are believed to be the most important in the scoring model formulation are identified as follows; technological, production, marketing, economic, and national requirement super-factors. The weights for those superfactors are identified as 0.3, 0.2, 0.2, 0.2, and 0.1, respectively. These findings are important because they may be used in the technologically based organizations which deal with competing R \& D projects or proposals for limited resources, such as time, money, and skills.