Research On Critical Factors Of Online Consumer Decision-making Based On Data Mining

As the electronic information technology is developping rapidly in China, online consuming has become a part of work and life of Chinese netizens who has accepted it as one new type of commercial mode and seen it as one kind of purchasing method. As a result,online consuming is attracting more and more experts and scholars to study and research,and we found that consumer psychology, motivation and behavior under the network environment have been studied a lot, however, those factors effecting consumer's purchasing decisions are researched are so rare.On the base of given research findings,this paper adopt data mining method to research the critical factors of online consumer decision-making,combining the latest developpment of practice and theory in e-commerceand field. First,the paper clusted 7 critical factors from 47 common factors using R-system clustering method.The 7 critical factors are customized Web site service, web entertainment, Web site address is easy to be remembered, a network of advertising, open and transparent trading information, shop's goods are famous brand goods and store credit. Then critical factors were mined by data mining algorithm:decision tree,based on the former 7 critical factors,and through the decision tree algorithm the paper finally finds how significant the critical factors influening the online consumer decision-making. Hoping that the research results can be helpful to network sellers and can provide references to scholars in related fields.This paper concludes two innovations as follows:Content innovation:At present, the research on online consuming are mostly focused on consumer psychology, consumer motivation and behavior,and only a few studies on the factors of online consumer decision-making.It is an exploration to take factors of online consumer decision-making as the object of study.Up till now,among the researchs on the factors of online consumer decision-making,most of them only make one factors or a few factors as object of study, this study attempts to make improvement by systematically considering the factors of consumer decision-making in a whole environment,to make the study results more resonable and closed to practical situation.Method Innovation:R-system cluster algorithm is often applied to solve problems which is complex,descriptive and difficult to quantify. In this study, R-system clustering algorithm is applied to choose the critical factors of online consumer decision-making,which is used as input of decision tree data mining,finally the order of critical factors listed by significance is figured out.