The empirical analysis of automobile logistics based on multivariate statistical analysis

Abstract

With the logistics outsourcing gradually increases, automobile logistics can be an important tache to assess and select the automobile logistics vendors justly and equitably in the outsourcing process of enterprises. And the proper evaluation of automobile logistics would enhance auto enterprise core competence, improve added-value service, reduce cost and optimize enterprise resources etc. But a new quantitative approach is adopted to assess the automobile logistics through the principal component, the fisher method and K-Nearest Neighbor method, it could grade them. And then identify the Misclassified automobile logistics by K-NN on the base of above analysis. Moreover, this method contributes to the classification and selection of the automobile logistics vendors on the basis of some objective information provided by this method and then the analysis result might be taken as one of main reference for outsourcing decision making.