DocumentCode :
1690849
Title :
Modeling to Plan and Evaluate the E-Supply Chain Management Platform
Author :
Huang, Lijuan
fYear :
2009
Firstpage :
326
Lastpage :
330
Abstract :
This article mainly introduces some approaches and strategies on how to plan and evaluate the e-supply chain management platform (E-SCMP) based on the Elman artificial neural network (Elman ANN) so as to improve Chinese supply chain performance. This article divides into 4 sections: The first is to review current situation of the E-SCMP and point out there are a few weaknesses in the theories and application of E-SCMP on the International. The second is to analyze main six differences between Chinese supply chain and foreign supply chain and suggest that foreign mode can meet the requirements of Chinese supply chains not well, as is main factor that leads most famous Chinese enterprises to fail in E-SCMP. The third is to describe how to plan and design the E-SCMP in detail from three aspects. The last is evaluate the E-SCMP based on the Elman ANN and apply its model to two examples in China. Modeling to plan and evaluate the E-SCMP based on the Elman ANN is a comparatively novel methodology and complicated system engineering. So, the result of research in this article is only for reference.
Keywords :
electronic commerce; enterprise resource planning; neural nets; supply chain management; Chinese enterprise; Chinese supply chain performance; Elman ANN; Elman artificial neural network; e-supply chain management platform; foreign supply chain; planning; Artificial neural networks; Conference management; Electronic commerce; Electronic government; Financial management; Information management; Internet; Logistics; Supply chain management; Supply chains; ANN; E-SCMP; Evaluating; e-business; modeling; planning; supply chain;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Management of e-Commerce and e-Government, 2009. ICMECG '09. International Conference on
Conference_Location :
Nanchang
Print_ISBN :
978-0-7695-3778-8
Type :
conf
DOI :
10.1109/ICMeCG.2009.120
Filename :
5279903
Link To Document :
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