摘要
利用决策树算法了解消费者网络购物时的影响因素,有利于商家改进营销策略.采用随机抽样的方式对500名被试进行问卷调查.对影响消费者网络购物决策的因素建立分类回归树.结果表明,决策树可以有效地用于网络购物决策的分类预测;按重要性提取规则,消费者自身的网络购物经验对网络购物决策影响较大,消费者对网络购物的财务风险、隐私风险等风险感知因素也是预测网络购物决策的重要指标,除此之外商家提供的售后服务、界面操作的便利性以及消费者自身的特征也会在一定程度上反映购物决策.
The Adoption of the Decision Tree Algorithm is helpful in finding out about the influencing factors that affect the consumer online shopping,which is rather important for the manufacturers to improve their marketing strategy.A random sampling of 500 customers was done by means of a questionnaire and a classification regression tree is established of the influencing factors that affect consumers＇ online shopping decision-making.The results showed that：Classification and Regression Tree could well be adopted in classified prediction of the online shopping decision-making;according to the importance extracting rules,consumers＇ online shopping experience exerts a greater impact on the decision-making of online shopping;the awareness of the financial risk and privacy risk and some other perception factors are also important in predicting the online shopping decision.In addition,after-sales service that a business can provide,the strong operability of interface operation and characteristics of the consumers themselves will also affect shopping decision to some degree.
出处
《内江师范学院学报》
2015年第2期24-27,共4页
Journal of Neijiang Normal University
关键词
决策树
分类回归树
网络购物
决策
decision tree
classification and regression tree
online shopping
decision-making
