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New Technology of Library and Information Service  2010, Vol. 26 Issue (9): 42-47    DOI: 10.11925/infotech.1003-3513.2010.09.08
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Study on Quick Response Information Service Model of E-government
Li Jiao, Liu Xilin
School of Management,Northwestern Polytechnical University,Xi’an 710129,China
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Abstract  

In view of user’s urgent demand to quick response information service of present E-government and from the perspective of information resources organization,this article provides solutions to E-government quick response information service in micro-level of data element. It also constructs an E-government information service model which is oriented by quick response, and then the model is validated.

Key wordsE-government      Information      service      Quick      response      Data      element      Information      package     
Received: 28 May 2010      Published: 26 October 2010
: 

TP399

 

Cite this article:

Li Jiao, Liu Xilin. Study on Quick Response Information Service Model of E-government. New Technology of Library and Information Service, 2010, 26(9): 42-47.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2010.09.08     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2010/V26/I9/42


[1] Tung L L, Rieck O. Adoption of Electronic Government Services Among Business Organizations in Singapore
[J].Journal of Strategic Information Systems,2005,14(4):417-440.

[2] 陈子侠.现代物流学理论与实践
[M].杭州: 浙江大学出版社, 2003.

[3] Reference Model for an Open Archive Information System . .http://ssdoo.gsfc.nasa.gov/nost/isoas/refmode1.

[4] Fitzsimmons J A,Fitzsimmons M J. Service Management:Operations, Strategy, and Information Technology
[M]. Beijing:China Machine Press,2002.

[5] 蔡文.物元模型及其应用
[M]. 北京:科学技术文献出版社,1994.

[6] 刘巍,季晟,康松林.可拓信息的基本理论与方法研究
[J]. 系统工程理论与实践 ,2000,20(11):125-131.

[7] 邹国成.可拓信息初探
[J]. 广东工学院学报 ,1996,13(1):18-22.

[8] ISO/IEC 11179 Information Technology——Specification and Standardization of Data Elements
[S].2003.

[9] 高贵锦,龙翔.基于数据元的交换数据标准维护
[J]. 吉林大学学报:信息科学版 ,2005,23(1):38-41.

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