• DocumentCode
    3461294
  • Title

    Customer Satisfaction Data Analysis Based on BP ANN

  • Author

    Zhang, Guozheng ; Zhou, Faming ; Liu, Junfeng ; Lan, Yong

  • Author_Institution
    Coll. of Bus., Hunan Agric. Univ., Changsha
  • fYear
    2008
  • fDate
    12-14 Oct. 2008
  • Firstpage
    1
  • Lastpage
    3
  • Abstract
    One of the most important benefits of ANN (artificial neural networks) is the free of the restrictions of the classic statistical techniques. Some literatures points to several limitations in multiple regressions that are overcome by ANN. This paper demonstrates the usefulness of ANN in customer satisfaction analysis and compares ANN and regression, based on data from a China company customer satisfaction survey. Based on the results of this study, there is sufficient evidence to suggest that the application of ANN in customer satisfaction analysis is useful in identifying existing patterns in the data, and synergies between the drivers of satisfaction. The advantages of using ANN are highlighted and the managerial implications of ANN to identify the key drivers and set priorities for improvements are demonstrated.
  • Keywords
    backpropagation; customer satisfaction; data analysis; neural nets; regression analysis; China company customer satisfaction survey; artificial neural networks; backpropagation; classic statistical technique; customer satisfaction data analysis; regression analysis; Artificial neural networks; Customer satisfaction; Data analysis; Educational institutions; Electronic mail; Multi-layer neural network; Neural networks; Neurons; Pattern analysis; Regression analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08. 4th International Conference on
  • Conference_Location
    Dalian
  • Print_ISBN
    978-1-4244-2107-7
  • Electronic_ISBN
    978-1-4244-2108-4
  • Type

    conf

  • DOI
    10.1109/WiCom.2008.1961
  • Filename
    4680150