• Title of article

    Mining customer knowledge to implement online shopping and home delivery for hypermarkets

  • Author/Authors

    Liao، نويسنده , , Shu-Hsien and Chen، نويسنده , , Yin-ju and Lin، نويسنده , , Yi-tsun، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2011
  • Pages
    10
  • From page
    3982
  • To page
    3991
  • Abstract
    With advances in modern technology, the Internet population has increased year by year globally. For young customers who consider convenience and speed as prerequisites, online shopping has become a new type of consumption. In addition, business-to-customer (B2C) home delivery markets have taken shape gradually, because virtual stores have risen and developed, e.g. mail-order, TV marketing, e-commerce. To integrate the above statements, this study combines online shopping and home delivery, and attempts to use association rules to determine unknown bundling of fresh products and non-fresh products in a hypermarket. Customers are then divided up in clusters by clustering analysis, and the catalog is design based on each of the cluster’s consumption preferences. By this method, to increase the catalogue’s attraction to customers, hypermarkets are offered an online shopping and home delivery business model for sales services and propositions. With such a model, we can expect to attract more customers open up more broad markets, and earn the higher profits for hypermarkets.
  • Keywords
    Electronic commerce , Database marketing , DATA MINING , Association Rule , home delivery , On-line shopping , Cluster analysis
  • Journal title
    Expert Systems with Applications
  • Serial Year
    2011
  • Journal title
    Expert Systems with Applications
  • Record number

    2349057