Applying Decision Tree Data Mining for Online Group Buying Consumers’ Behaviour

Abstract

This paper treated `amount of invested money` and `use times` of online group buying as the dependent variables, and applied the clustering algorithm and the decision tree data mining technique to deeply analyse the influences of independent variables on each dependent variable and observe the possible association rules existing among them. We found that the consumers` past online shopping experience would directly affect their decision-making. Noticeably, the people who tended to be willing to participate in the money-saving group buying, were not the ones with lower incomes; instead, they were the ones with more incomes.