Goal Discriminant Analysis A New For Classification Strategy In Management Science

Classification of statistical elements is one of the challenging areas in management science. This subject has changed to an interesting research areas. Although methods of cluster analysis and discriminant analysis are used as common methods in the classification, there is a doubt about their application due to high statistical errors of the methods. In this paper, it is tried to combine analysis approach of statistical discrimination and OR technique and a new method titled goal discriminant analysis is developed. Four discriminant analysis methods titled FLDF, FG, GP1 and GP2 are applied in this paper. In order to evaluate its efficiency in management science area, the fourfold technique has been employed in 5 managerial case studies. The results show that the FLDF method, which is a discriminant analysis method, is more efficient than other methods. Moreover, goal discriminant methods have more efficiency in management classification with over two groups.