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New Technology of Library and Information Service  2005, Vol. 21 Issue (12): 48-50    DOI: 10.11925/infotech.1003-3513.2005.12.11
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Research on the Comprehensive Evaluation of Information System Based on Preference DEA Model
Yu Xiuyan   Li Minghui
(Department of Management, Shandong University of Technology, Zibo 255049, China)
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Abstract  

The preference DEA model is put forward based on the traditional DEA model to solve the comprehensive evaluation, and to solve the same efficient DMU with the average cross-efficiency. The preference DEA model is applied to the evaluation of information system. The result shows that the preference DEA model reflects the preference and offers lots of information for decision-makers.

Key wordsPreference      Information system      Comprehensive evaluation      DEA model     
Received: 29 September 2005      Published: 25 December 2005
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Corresponding Authors: Yu Xiuyan,Li Minghui     E-mail: yuxiuyan123456@163.com
About author:: Yu Xiuyan,Li Minghui

Cite this article:

Yu Xiuyan,Li Minghui. Research on the Comprehensive Evaluation of Information System Based on Preference DEA Model. New Technology of Library and Information Service, 2005, 21(12): 48-50.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2005.12.11     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2005/V21/I12/48

1管政.信息系统的价值评估模型.软件工程师,2000,Z1:94-95
2邵培基.AHP方法综合评价管理信息系统.系统工程理论与实践,2000,(10):63-67
3Kenneth C Laudon, Jane P Laudon.Management information system.New Approaches to Organization and Technology, 5th ed. Prentice-Hall, Inc, New Jersey,1998
4张新红,郑丕谔.基于神经网络的管理信息系统综合评价方法.系统工程学报,2002,17(5):445-450
5魏权龄.评价相对有效性的DEA模型.北京:中国人民大学出版社,1988
6刘卫国.一种信息系统的评价模型及其实现.计算机应用,2003,23(1):33-35

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