Consumer behaviors have always been the hot spot of the study. With the arrival of the network age and the popularity of e-commerce, the consumption pattern of shopping online is beginning. Until December of 2014, there were 649 million Internet users in China, and it's increasing. In the year of 2014, the number of most mainstream online shoppers has increased by 23.7% and shopping online has become an irresistible trend. New consumption mode can produce a new research subject, the study of Internet consumer behaviors becomes very important. This article used LocoySpider, a data mining software, to mine Taobao online reviews. Through the analysis of online reviews, we can study the effect of online reviews on consumer behaviors. During the study, we set the risk perception as intermediary variable. By the study, we can help the electronic commercial enterprises to attract customers, retain customers and reduce the information search cost.
TopIntroduction
With the development of the Internet, we have entered the e-commerce age. Great changes have taken place in people’s lives: sites like Alibaba, Amazon, Jingdong have changed people’s consumption patterns. According to CNNIC, the number of Internet users has reached 649 million by December 2014 in China. Compared with the previous year, the growth rate is 5%. The number of active buyers on Alibaba platform has reached 255 million. Only in the third quarter of 2015, Taobao’s GMV has arrived 438,000 million yuan, it's growth rate is 15% year-on-year. From the data above, we can see that shopping online has become a hot trend. When the consumers go shopping online, they would browse online reviews to find the merchandise news which can help them know more information about the goods. The historical and cultural environment of our country has great influences on the consumers, so consumers’ purchase decisions are easily affected by others. According to the survey by Deloitte’s Consumer Products, we can see that there will be 67% of Internet users to browse online reviews, 82% of them think that online reviews can affect their purchase decisions directly. So, online reviews have important influences on consumers’ purchase decisions. So, it has great importance to study online reviews.
Through the study of online reviews, we can know the characteristics of online reviews, so that we can grasp the focus of consumers. Based on the understanding the mechanism of reviews’ influences on consumer behaviors, the online merchants can find out their disadvantages. So, they can improve the quality of products and services and control the influences of online reviews dissemination effectively. Some specialists have made some studies about online reviews, for examples Gu and Xu (2015) built the index system of online reviews from two dimensions which are the quality of content and the value of the reviewers. The online reviews can be divided into four categories. They are efficient reviews, suspicious comments, potential comments and invalid comments. Through the analysis of their usefulness, we can distinguish the efficient comments and use them. Mudambi and Schuff (2010) published a paper in MISO, it has defined the concept of online reviews’ usefulness. They used the theories of information economics and the framework of decision-making uncertainty. Based on the data of Amazon, their analysis showed that the extreme comments and the length of the comments has directly influences on online comments’ usefulness. At the same time, they researched the regulatory effects about search products and experience products. Yan, Zhang, and Zhang (2015) studied whether the content of online reviews has impacts on the usefulness of comments. They found that the deeper and more objective the online comments are, the higher the usefulness of comments is. The higher the product matches the description degrees and the more information of product characteristics the reviews have, the higher are the usefulness of comments. Chen and Xu (2014) studied the online comments from two perspectives, they are the characteristics of review and the information of reviewers.
They analyzed the factors that could affect the online review to acquire online comments’ useful votes. From the study, they found that the comment score has a negative effect on online reviews’ useful votes and the richness of comment information. The historical evaluation has a positive influence on its usefulness. Hao, Ye, and Li (2010) had set up the model of influential factors of online comments usefulness. They found that positive emotional tendency, the higher mixed degree of the positive and negative emotion, the higher mixed degree of subjective and objective expression and the longer the average sentence have significant positive effect on the usefulness of comments. Ning and Sun (2014) studied the influences of negative online comments on online consumers’ purchase intention from the aspects of the number of negative comments, the degree of its negative, the contents, etc. On this basis, Zhou, Li, and Mou (2015) took the psychological distance as intermediary variables to study online reviews’ influences on online consumers’ purchase intention. They also studied the mediation comments’ influences on online purchase intention which is under the regulation of different commodity types. Mo and Li (2015) studied the number of mixed reviews, favorable reviews and unfavorable reviews. Thus, it is concluded that the number of them has effects on consumer purchase intention. These studies made great contributions to the study of online reviews later.