| Recently, with the development of computer and internet technology, the internet population has grown tremendously in China. According to the latest CNNIC Survey (published in January 2009), the internet population in China is more than 0.298 billion. E-commerce has also developed sharply. The number of people purchasing online, according to the same survey, has exceeded 67 million,60% more than last year.[1] All of this represents a huge marketing opportunity to the marketers. To grasp this opportunity, online shop owners must understand online customers'behavior and deal with the relationship between online shops and customers. To help online shop owners achieve their goals, many scholars pay attention to factors affecting customers'online shopping behavior. However, most researches are conducted by western scholars, who only focus on the customers of their own countries. Few people pay attention to the customers' differences between China and western countries. One obvious difference is that Chinese customers are more likely to be affected by what other people do and what other people say, in the progress of accepting new things. In one way, Chinese customers can be easily affected by others'behavior in the progress of accepting new things. When a customer feels that a new thing is very popular or when a person finds that a lot of people around this person is using a new thing, the person will be attracted by the new thing and be more likely to accept this new thing. In other words, the more consumers use a new thing the more it raises the interest of a new consumer. In the other way, Chinese customers can be easily affected by others' words in the progress of accepting new things. A consumer tends to be more interested in a new thing when the consumer is recommended by someone or overheard something about the advantages. In the other words, the higher the reputation of the new thing is, the more passionate a consumer want to know and use it.So, this research thinks that Perceived popularity of online shopping and perceived public praise of online shopping may have a significant impact on Chinese customers'online shopping intention. Although some Chinese scholars research factors affecting Chinese customer's online shopping behavior, by interviewing Chinese customers, none of them considers these two factors as variables affecting customer's online shopping behavior.To address this gap, the present study considers perceived popularity of online shopping (PP) and perceived public praise of online shopping (PPP) as key factors that lead an individual to shop online. Based on the TAM model, the present study constructs a new model, called FACOSI model, by adding some new variables, including PP and PPP. The new model is used to research the factors affecting online shopping behavior.This paper obtains research data by questionnaires. There are three steps to design questionnaires and interview customers. First, after reading a lot of reference materials, we get 12 variables, which may have impacts on customers' online shopping behavior, and 61 items, which are used to test these variables. Then according suggestions from some specialist, we change some of these variables and items and design an unofficial questionnaire, which includes 7 variables and 36 items. Secondly, we do some unofficial interview using the unofficial questionnaires. According the suggestions from interviewees, we modify the variables and items again and finally design an official questionnaire, which includes 7 variables and 25 items. Thirdly, Approximately 300 questionnaires are distributed, of which 267 are returned. After excluding problematic and unanswered questionnaires,256 are suitable for data analysis, resulting in a valid response rate of 89 percent.The data collected by questionnaires is then analyzed by different kinds of statistical tools. First, In order to check the reliability and validity of the questionnaires, the data is analyzed by SPSS for reliability analysis and validity analysis. Then, to check the goodness of the model and test the hypotheses, the data is analyzed by LISREL using structural equation modeling analysis. Finally, SPSS is used to check whether groups with different internet age are distinctive in PU, PEOU, PR, PSQ, PP, PPP and SHOP.Based on these analysis and tests, we get some conclusions. First PU, PEOU, PP, PSQ and PPP have a significantly positive and direct impact on customers'online shopping intention. PP has the greatest impact on customers'online shopping intention (affecting coefficient is 0.26), then sequentially has PPP, PEOU, PU, and PSQ. Secondly, PR is negatively related to online shopping intention. In other words, the greater risk customers feel, the less possibility they shop online. Thirdly, PP also can affect customers'online shopping intention through intermediary variables. In one hand, PP can affect online shopping intention by positively impacting PU, PEOU. In the other hand, PP can affect online shopping intention by inhibit PR. Fourthly, PP and PPP are the most important factors which affect online shopping intention, on both directly and entirely aspects. Fifthly, groups with different internet age are singnificantly different in PU, PEOU, PR, PP, PPP and SHOP, but not singnificantly different in PSQ. Sixthly, groups spending different hours surfing online are significantly different in PEOU, PR, PP, PPP and SHOP, but not significantly different in PSQ and PU.Based on these conclusions, this paper gives some suggestions to online shop owners. Fist, in order to enhance online shops' marketing efficiency, online shops should find the proper customers to promote their products. Secondly, they should pay attention to the effects of public praise. Thirdly, online shops should simply the progress of online shopping. Fourthly, online shops try to let customers feel that online shopping is useful. Fifthly, online shops should also improve their service quality. Sixthly, online shops should try to reduce the risk perceived by customers. |
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