How Merchants' Response And Inconsistency Between Text And Rating Of Online Review Affect Product Sales

With the rapid development and popularization of the Internet,online shopping has become the main way for people to consume.In order to eliminate the risk caused by network virtuality,people usually make reference to online reviews to evaluate goods,services and businesses.Numerous studies have demonstrated the importance of online reviews for business performance,but they generally quantify the features of online reviews directly from consumer ratings.In reality,when people are browsing online reviews,they mostly get the information of goods,services and businesses from the textual contents of online reviews.Therefore,there is a great limitation in using only ratings of online reviews to conduct research.Whether the text of an online review has an impact on the performance of the business,how the difference between the text and the rating affects the performance of the business,and what kinds of response the business takes to moderate the impact,these valuable questions are all worth further study.This research is based on the background of JD.com,and conducts an in-depth research on the impact of online reviews and merchant response on the sales of merchant's merchandise for children's wear products.Based on the previous research theories and research results,this study determined the valence,dispersion,sentiment richness,inconsistency between text and ratings,the quantity and type of merchant response as independent variables to build a multi-dimensional Econometric model to explore the effects of independent variables on the sales of goods.Among them,this study uses text sentiment analysis technology to conduct sentiment analysis of online text reviews,and on the basis of this,quantifies the characteristics of online text reviews.In addition,this study refers to the previous classification of merchant response,divides the merchant response into four types:thanks,apologies,explanations and promises,and classifies the collected merchant response data in combination with the text classification algorithm.The main research results of this study are as follows:1,the valence and sentiment richness of online text reviews have a significant positive impact on the sales of goods,while the dispersion of online text reviews and the sales of businesses have an inverted "U" type relationship.2,the inconsistency between text and rating of online reviews can negatively affect the sales of goods.3,the number and type of business response have a significant impact on the sales of goods,and the number of business response,thanks class and apology class have significant impact.4,the number and type of business response significantly moderate the relationship between online reviews and the merchandise sales.