資料包絡分析法排序模式與鑑別度提升之研究

Ranking Models and Discrimination Improvement in DEA

曾幸瑋(Hsing-Wei Tseng)

指導教授 ： 蔡榮發

國立臺北科技大學/管理學院/商業自動化與管理研究所/碩士(2006年)

https://doi.org/10.6841/NTUT.2006.00355

摘要

資料包絡分析法(Data Envelopment Analysis，DEA)方法可用來處理多項產出及多項投入指標的效率評估難題，無需先預設產出、投入指標權重值，所以，DEA在績效評估上常被應用至不同領域做績效評估，但DEA仍存在一些問題，例如(1)DEA在績效評估上有鑑別度不高的問題，(2)多個有效率受評單位(Decision Making Units，DMUs)產生多組權重解，(3)目標式只考慮到絕對效率觀點，忽略相對效率觀點。針對第一個問題，本研究以正規化權重向量模型來提高DEA的鑑別度；針對第二問題，本研究提出共同權重模式來改良多組有效率DMUs產生多組權重解的問題；針對第三個問題，本研究提出最小化排名模式的新排序模式來說明。
最後，本研究舉了二個實際的例子，來說明並比較原始DEA方法的評估結果與本研究所提出方法的評估結果。

關鍵字

資料包絡分析法 ； 正規化權重向量 ； 共同權重 ； 排序模式

並列摘要

Data Envelopment Analysis (DEA) is a tool of performance assessment manipulating multiple inputs and outputs without giving subjective weights of each input and output in advance. Although DEA has been applied in many fields to evaluate performance, the method still has following problems. i.e., (1) Result in to many efficient decision making units (DMUs) , i.e., low discrimination. (2) Obtain many sets of weight for DMUs. (3) Consider absolute efficiency instead of relative efficiency.
This study adopts weight normalization approach to treat the problem (1) to increase the discrimination of DEA. To deal with problem (2) this study present a common weight model to find a set of weight for all DMUs with the maximum score. A rank minimization model is developed to assess the DMUs to eliminate the problem (3) mentioned above.
Practical examples are also presented to illustrate the differences between the DEA and the proposed method.

並列關鍵字

Data Envelopment Analysis ； Weight Normalization ； Common Weights ； Ranking Model

參考文獻

[15] M. J. Farrel, "The measurement of productive efficiency," Journal of the Royal Statistical Society A, Vol.120, 1957, p253-281.

[16] A. M. Lidia and P. E. L. Marcos, "Review of methods for Increasing Discrimination in Data Envelopment Analysis," Annals of Operations Research, Vol.116, 2002, p225-242.

[17] J. Sarkis, "An Analysis of Operational Efficiency of Major Airports in the United States," Journal of Operations Management, Vol.18, No.3, 2000, p335-351.

[18] P. Anthony and N.C. Petersen, "A procedure for ranking efficient unites in data envelopment analysis," Journal of Operations Management, Vol.20, No.1, 1993, p19-32.

[21] M.Halme, T.Joro, P. Korhonen, S. Salo, and J. Wallenius, "A value efficiency approach to incorporating preference information in data envelopment analysis," Management Science, Vol.45, No.1, 1999, p103-115.