DocumentCode :
1984915
Title :
Clothing Brand Competitiveness Evaluation Based on B-P Neural Network
Author :
Weijun Chen ; Xixiang Sun ; Xiaobo Hu
Author_Institution :
Manage. Sch., Wuhan Univ. of Technol., Wuhan, China
Volume :
2
fYear :
2013
fDate :
28-29 Oct. 2013
Firstpage :
317
Lastpage :
320
Abstract :
This paper establishes an evaluation indicator system of clothing brand competitiveness from four aspects: brand loyalty degree, brand innovation ability, brand market ability and brand basic ability. Among those, brand loyalty degree reflects customer value of brands, while brand innovation ability, brand market ability and brand basic ability reflects enterprise value of brands. We select B-P neural network as the evaluation method. We have made empirical analyses based on the introduction of the evaluation mechanism of B-P neural network. The results of the analyses not only indicate that customer value is important for clothing enterprises and the amount of customer value reflects the strength of the competence of an enterprise, but also show that the application of B-P neural network to evaluate the competence of clothing enterprises is very effective, objective and accurate.
Keywords :
backpropagation; clothing industry; competitive intelligence; consumer behaviour; customer satisfaction; innovation management; marketing data processing; neural nets; BP neural network; brand basic ability; brand innovation ability; brand loyalty degree; brand market ability; clothing brand competitiveness; clothing enterprises; customer value; enterprise competence strength; enterprise value; evaluation indicator system; evaluation method; Clothing; Indexes; Neural networks; Standards; Technological innovation; Training; B-P neural network; brand competitiveness; clothing brands;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Design (ISCID), 2013 Sixth International Symposium on
Conference_Location :
Hangzhou
Type :
conf
DOI :
10.1109/ISCID.2013.193
Filename :
6804892
Link To Document :
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