• DocumentCode
    2499744
  • Title

    Improving customer satisfaction by the expert system using artificial neural networks

  • Author

    Qian, Feng ; Xu, Linwen

  • Author_Institution
    Inst. of Manage. Sci. & Inf. Eng., Hangzhou Dianzi Univ., Hangzhou
  • fYear
    2008
  • fDate
    25-27 June 2008
  • Firstpage
    8303
  • Lastpage
    8306
  • Abstract
    CRM, which aims to enhance the effectiveness and performance of the businesses by improving the customer satisfaction and loyalty, has now become a leading business strategy in highly competitive business environment. The objective of this research is to improve customer satisfaction on productpsilas colors with the aid of the expert system developed by the authors by using artificial neural networks. The expert systempsilas role is to capture the knowledge of the experts and the data from the customer requirements, and then, process the collected data and form the appropriate rules for choosing productpsilas colors. In order to identify the hidden pattern of the customerpsilas needs, the artificial neural networks technique has been applied to classify the colors based upon a list of selected information. Moreover, the expert system has the capability to make decisions in ranking the scores of the colors presented in the selection. In addition, the expert system has been validated with a variety of customer types.
  • Keywords
    customer satisfaction; expert systems; neural nets; CRM; artificial neural networks; business strategy; customer requirements; customer satisfaction; expert system; Artificial neural networks; Automation; Color; Customer satisfaction; Engineering management; Expert systems; Information management; Intelligent control; Neurons; Pattern recognition; Artificial neural networks; Customer relationship management; Expert system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4244-2113-8
  • Electronic_ISBN
    978-1-4244-2114-5
  • Type

    conf

  • DOI
    10.1109/WCICA.2008.4594228
  • Filename
    4594228