NDLI: Fuzzy multiple ibjective programming for performance evaluation of public sectors in Taiwan

Content Provider	IEEE Xplore Digital Library
Author	Hua-Kai Chiou Yu-Yuan Tsou Gwo-Hshiung Tzeng
Copyright Year	2005
Description	Author affiliation: Dept. of Stat., National Defense Univ., Taipei, Taiwan (Hua-Kai Chiou)
Abstract	The traditional data envelopment analysis model so called CCR model proposed by Charnes et al.(1978), which model evaluates the relative efficiency of each decision making unit with multiple input and multiple output variables. However, there are two reasons make the CCR model weak discriminative power. One is impractical weights of decision variables; the other is the insufficient number of decision making units. Chiang and Tzeng (2000) introduced fuzzy multiple objective programming (FMOP) to improve the discriminative power of evaluating model This FMOP model derived the common weights for all decision making units and improved the problem of discrimination in CCR model. In this study, we applied these evaluation models to derive the efficiency score of the Accounting & Statistics Departments of Air Force in Taiwan. We also compared the results of these models and then summarized some research findings in the end of this paper, it might provides some useful implications for improving the competition of decision making units, which is one of the most important factors of modern war.
Starting Page	3742
Ending Page	3746
File Size	385520
Page Count	5
File Format	PDF
ISBN	0780392981
DOI	10.1109/ICSMC.2005.1571728
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-10-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data envelopment analysis Decision making Statistics Production Cybernetics Fuzzy systems Statistical analysis Business Data security Certification Performance Evaluation Data Envelopment Analysis Fuzzy Multiple Objective Programming
Content Type	Text
Resource Type	Article

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