网上消费者购物动机、点击流行为及其之间的关系

Online shopping has been a growing phenomenon all over the world as well as China in the recent years. Studies on online shopping with clickstream data have become a new research stream. But it is a pity that the online conversion rate is low. Accordingly, we can study on online consumers focusing on their shopping motivation, and put their shopping motivation and clickstream behavior into an integrative frame, study on the both construction and their relationship, and then we can get insight in chinese online consumers. This study has two processes. First, this study will use the questionnaire to explore all kinds of consumers’ online shopping motivation, and then emend the questionnaire and form the ultimate one for the second process. Second, we will simulate a shopping site to get clickstream data, participants need to complete the ultimate questionnaire at the same time. We will analyse the integrated data from two measures, cluster analysis separately, and explore the correspondence between the two cluster methods. Results show that, first, Chinese online shoppers contain five steady motivation factors: usefulness, fashion involvement, ease of use on searching, ease of use on alternative evaluation, ease of use after trade. Fashion involvement is comparatively independent, while the other have correlations between each two. Second, Chinese consumers can be clustered into five steady clusters according to online shopping motivation: functional shoppers, following shoppers, surfing shoppers, conflicting shoppers, e-laggard. The five clusters have significant differences on job, monthly income and online shopping experience of late six months, while have no significant differences on gender, age and education. Third, Chinese consumers can be clustered into five steady clusters according to clickstream data: functional browsers, hedonic browsers, impulsive shoppers, comparative shoppers and knowledge building browsers. The five clusters have significant differences only on age, while have no significant differences on other demographic variables. Fourth, the cluster methods according to motivation and according to clickstream data are two comparatively independent cluster frame, but they have limit correspondence.

近年来，全球范围和我国的网上购物蓬勃发展，利用点击流数据来研究网上购物成为一种新的研究潮流。但是网上购物的购买转换率普遍较低，这就提示我们从购物动机的角度来研究网上消费者，并将动机与点击流行为联系起来，研究两者的结构及其之间的关系，以期对中国的网上消费者有更深刻的了解。 研究分两个阶段：首先通过问卷调查的方法探测消费者的网上购物动机，并修订问卷；然后通过实验室模拟合问卷调查同时进行的方法获取网上购物动机和点击流信息，分别分类网上消费者，并探讨两种方法的对应关系。 结果表明：第一，中国消费者网上购物动机包括以下五个稳定的因素：网上购物有用性、时尚卷入、信息搜索好用性、选择性评价好用性、交易后好用性。其中，时尚卷入相对独立，其他四个动机因素两两相关。 第二，根据消费者网上购物动机，可以将中国的消费者细分成以下五种稳定的消费者人群：功能型购物者、跟随型购物者、信息冲浪型购物者、矛盾型购物者、网上购物迟钝者。这五类人群在职业、个人月收入水平和最近半年的网上购物经验上差异显著，而在性别、年龄和受教育水平上差异不显著。 第三，根据消费者的点击流行为，可以将中国消费者细分成五种消费者人群：功能型浏览者，享乐型浏览者，刺激型购物者，比较型购物者和知识建立者。这五类人群只在年龄上差异显著，而在其他人口统计变量上差异不显著。 第四，根据动机和根据点击流这两种分类方法是两种相对独立的分类体系，但也存在着一定程度的对应关系。