• DocumentCode
    2247475
  • Title

    Applying a fuzzy measure to evaluate the service quantity of a convenient store

  • Author

    Lai, Shun-Jen ; Hsieh, Ling-Ling

  • Author_Institution
    Dept. of Bus. Adm., Asia Univ., Wufeng, Taiwan
  • Volume
    5
  • fYear
    2010
  • fDate
    11-14 July 2010
  • Firstpage
    2372
  • Lastpage
    2376
  • Abstract
    There is a strong link between customer satisfaction and repurchase intention. Thus, the investigation of the overall customer satisfaction has important managerial implications. The weighted arithmetic mean method and regression method are most often ways of evaluating the overall customer satisfaction. The attributes may be redundant or work well together. We need to select important attributes to evaluate the overall customer satisfaction correctly. A fuzzy measure is a good candidate to do that. This study uses Shannon interaction information as fuzzy measure to study how the joint attributes affect the overall customer satisfaction. First, identify the important attributes that would evaluate the overall customer satisfaction by Shannon interaction information. Then, use them to evaluate the overall customer satisfaction. In this study, four methods (i.e., the weighted arithmetic mean method with all attributes, the regression method with all attributes, the weighted arithmetic mean method with important attributes, and the regression method with important attributes) were used to evaluate the overall customer satisfaction. The results show that the regression method with important attributes method which we proposed to evaluate the overall customer satisfaction is the best among the four methods.
  • Keywords
    customer satisfaction; entropy; fuzzy set theory; regression analysis; retailing; Shannon interaction information; convenient store; customer satisfaction; fuzzy measure; mutual entropy; regression method; repurchase intention; service quantity evaluation; weighted arithmetic mean method; Correlation; Customer satisfaction; Entropy; Joints; Machine learning; Mutual information; Random variables; Entropy; Fuzzy measure; Mutual entropy; Shannon interaction information;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4244-6526-2
  • Type

    conf

  • DOI
    10.1109/ICMLC.2010.5580668
  • Filename
    5580668