Experimental Research On Customers’ Buying Behavior On The Product Page

With penetration rate of Internet continues to improve, and unceasing expansion of the scale of online shopping transactions, online shopping has become a very important shopping way, there are a very large potential for development in the future. Recently, researchers increasingly deep into some specific areas. In online shopping, consumers exhibit different shopping behaviors. Network reseller only have a more accurate understanding of consumer shopping behavior in order to properly understand the behavior of consumers, grasp the influencing factors behind consumer behavior, and thus targeted guide them to participate in online shopping. According to the online shopping decision theory, the consumer product evaluation and selection behavior is a very important link in the process of online shopping, and a direct impact on consumers’ shopping decisions. Consumer product evaluation and selection behavior occurs mainly on the product page, research the online shopping behavior of product page can help network retailer understand consumer product selection and evaluation process more clearly and accurately. Therefore, the research about consumer behavior of product page is very meaningful.In recent years, research on online shopping behavior is very popular, but only a few studies on product pages consumers shopping behavior. At home and abroad, some of the researchers have already research consumer’s purchase behaviors from their shopping path and trying to apply path theory to the field of electronic commerce, but what have been applied to specific areas of e-commerce research are also very few. Therefore, the paper study on the costumer buying behavior of the product page and some factors may affect the shopping behavior through the experiments, and look forward to be able to explain some of the buying behavior path characteristics.According to the study design, we organize experiment for data collection. Let subjects did online shopping on the laboratory computer, screen record collection of 45 videos and extract a test on the product page 274paths. Collection of 45 video screen recordings and extracted 274 valid shopping path on the product page. In the analysis of the shopping video, record operating behavior of consumers in each product page. From open a product page to off the page is called a path, the shopping behaviors are divided into two parts:search behaviors and reading behaviors. Search behavior is the behavior of selected information, like searching and filtering. Reading behavior is read the product information, parameters, pictures and other acts. The paper take the path clustering analysis from two different dimensions of time and purchase products, and found that the behavioral characteristics of consumers shopping on the product page.Collected the information of goal-specificity and online shopping experience through questionnaires and interviews. We selected the goal-specificity and online shopping experience as independent variable, online shopping behavior path time as the dependent variable. Study the impact of these two factors and their interaction on the path of shopping behavior through experiment. Use online shopping expenses to describe the shopping experience, the total time of the path, the search time and reading time to describe the time invested in different shopping behavior. Then,use the one-way ANOVA analysis and multivariate analysis of variance to do data analysis.Through empirical research on the product page online shopping behavior and its influencing factors, we found that read time is greater than the search time on the product page, and some subjects also exhibit some differences. The goal-specificity has significant impact on total time, reading time and the search time. The online shopping experience did not significantly affect the the total time and reading time,but significantly affect the path search time. We explore the cause and mechanism of the analysis, which may help the online merchants to better understand the behaviors of online shoppers.