• 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