Research On Influencing Factors Of Customer Comment Usefulness Of Cross-Border E-Commerce Platform

The rapid development of the Internet and the outbreak and continuation of COVID-19 have greatly changed people’s shopping methods.China’s online shopping groups are becoming larger and larger,and consumer demand is developing to high-end and high quality.Domestic goods can no longer satisfy consumers’ needs completely,and cross-border e-commerce platform has become another main battleground for consumer online shopping.Due to the limitation of distance and space,compared with domestic online and offline shopping,there is a stronger information asymmetry between merchants and consumers in cross-border online shopping.Consumers can not fully understand the information and characteristics of goods only through the description of goods and the display of advertising pictures in the web page.Consumers can understand the quality of goods by browsing and reading the online comments in the cross-border e-commerce platform,so as to reduce the risk of overseas shopping.However,with the massive storage of information,the number of online comments is filling the shopping platform with explosive increments.The accumulation of a large number of online comments blurs the accuracy of consumers’ information processing and weakens their judgment on the usefulness of online comments.Therefore,it is necessary to analyze the influencing factors and mechanism of the usefulness of cross-border e-commerce platform customer comments to judge the value of online comments,so that consumers can select useful online comments for reading in the shortest time.At the same time,it can also provide a more useful online comment template guidance for cross-border e-commerce platforms.This study draws on the relevant research results of domestic and foreign scholars,takes the signal theory and the fine processing model of information as the theoretical basis of model construction,and constructs the influencing factor model of online comment usefulness from the two main lines of central path and peripheral path.Amazon China cross-border e-commerce platform is selected as the research object.According to the characteristics of the platform,the emotional polarity of comments,the number of comment pictures,the length of comment text,the characteristics of comment goods,the price stress of comments,the influence of commentators and the integrity of commentators’ information are selected as independent variables,the type of goods is used as regulatory variables,the number of comment replies and comment time are used as control variables to build a feasibility model and put forward corresponding assumptions.The crawler program is developed through Python software,and the online reviews of goods in Amazon China cross-border e-commerce platform are mined as sample data.The sample data are analyzed by descriptive analysis,frequency analysis,correlation analysis and Regression Analysis Using stata analysis software to test the hypothesis.Based on the results of this research on online comments,first,it can provide suggestions for Amazon China cross-border e-commerce platform,think about how to create an online comment writing interface and guide consumers to write online comments with higher usefulness value,so as to increase the stickiness of users,further attract consumers to buy goods and promote the sales volume of merchants;Second,it can provide users with online comments with high value and strong credibility,reduce the time of reading online comments,and have a definite understanding of goods faster.There are 7 figures,24 tables and 78 references in this thesis.