DocumentCode
1637841
Title
Notice of Retraction
Dynamic customer segmentation analysis based on customer value in electronic business environment
Author
Jia, Peng ; Changqing, Li ; Jia, Liu
Author_Institution
Management College, Inner Mongolia University of Technology, Hohhot, China
fYear
2011
Firstpage
1
Lastpage
4
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In this paper, we broaden traditional marketplace segmentation index by creating a dynamic index system based on customer value, as in today´s changing electronic business environment, customer purchasing behavior is more complicated, diversified and fast changing with more channels to choose. BP neural network is applied to create dynamic customer segmentation model. This segmentation model helps to categorize customer type and find the most valued customer dynamically. Using this model long term optimized the limited resource usage dynamically.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In this paper, we broaden traditional marketplace segmentation index by creating a dynamic index system based on customer value, as in today´s changing electronic business environment, customer purchasing behavior is more complicated, diversified and fast changing with more channels to choose. BP neural network is applied to create dynamic customer segmentation model. This segmentation model helps to categorize customer type and find the most valued customer dynamically. Using this model long term optimized the limited resource usage dynamically.
Keywords
Artificial neural networks; Consumer electronics; Dynamic scheduling; Frequency measurement; History; Indexes; Electronic business; customer relation management; customer segmentation; customer val; dynamic model;
fLanguage
English
Publisher
ieee
Conference_Titel
E -Business and E -Government (ICEE), 2011 International Conference on
Conference_Location
Shanghai, China
Print_ISBN
978-1-4244-8691-5
Type
conf
DOI
10.1109/ICEBEG.2011.5881770
Filename
5881770
Link To Document