A Decision Tree-Based Method for Selection of Input-Output Factors in DEA

摘要

We propose a method for selection of input-output factors in DEA. It is designed to select better combinations of input-output factors that are well suited for evaluating substantial performance of DMUs. Several selected DEA models with different combinations of input-output factors are evaluated, and the relationship between the computed efficiency scores and a single performance criterion of DMUs is investigated using decision tree. Based on the results of decision tree analysis, a relatively better DEA model can be chosen, which is expected to effectively assess the true performance of DMUs. We illustrate the effectiveness of the proposed method by applying it to the efficiency evaluation of 101 companies in steel and metal industry listed on the Korean stock market.