Integrated Comprehensive Methodology based on DEA and PCA
Data Envelopment Analysis (DEA) is a kind of comprehensive evaluation method to rank and calculate the corresponding efficiency for each Decision Making Unit (DMU) by constructing a production frontier in multiple inputs and outputs system. For each DMU, we can use multiple variables to describe the characters of DMU, which can be classified as input variables and output variables separately. In traditional DEA models, we neednt do any transformation for input and output variables when we apply DEA into evaluation procedure because the linear programming can allocate optimal weights for different variables based on the principle of the lower inputs and higher outputs the better. However, traditional DEA models can obtain weak evaluation results that most of DMUs are efficient when each DMU has large amount input variables and output variables. To overcome the shortcoming of DEA models, we proposed an integrated DEA model, denoted as PCA-DEA, in this paper. By using CPA arithmetic, the original data for each DMU can be transferred into uncorrelated data. Then, CPADEA models have stronger evaluation capability than traditional DEA models.
Data Envelopment Analysis Principle Component Analysis comprehensive evaluation weights
Chunyan Yao
Research Institute of Regional Economy Beihua University Jilin, China
国际会议
太原
英文
42-46
2011-02-26（万方平台首次上网日期，不代表论文的发表时间）