在线评论对新旧产品销量影响实证研究
发布时间：2018-08-16 17:23
【摘要】：互联网的普及带动了电子商务的蓬勃发展,网络购物越来越受到消费者的青睐。与传统的线下购物相比,网上购物增加了消费者对产品和服务质量的不确定性,为了降低消费者的不确定感,购物网站纷纷建立了用户评价系统,鼓励购买过产品的用户对产品质量以及购物过程进行评价。CNNIC调查表明在线评论成为影响消费者购买决策最重要的因素。与此同时在线评论引起学术界高度关注,对在线评论的研究大致可以分为两大类,一类是在线评论在个体层面对消费者购买意愿的影响研究,另一类是在线评论在市场层面对产品销售情况的影响研究。本文在大量阅读国内外相关文献的基础上,对在线评论相关的研究进行了综述。由于针对处于不同销售阶段的产品,用户对在线评论的依赖程度不同,本文试图探索在线评论对新旧产品销量的影响及其差异。 基于消费者购买决策行为理论、创新扩散理论、信息过载理论和信息价值理论,作者提出了本文的研究假设。结合文献研究,识别出评论数量大小、评论数量分布均匀程度、好评率、差评率作为解释变量,产品价格作为控制变量,共同影响交易网站产品销量,除了评论数和评论情感倾向这些常规的变量,本文首次关注评论数量分布情况对销量的影响。本文使用爬虫软件抓取京东商城手机类产品的产品信息和评论信息,按照上架时间不同,将手机划分为新产品和早期上架产品(旧产品),具体分析由三部分组成,首先是消费者新旧产品评论行为对比分析,其次是在线评论对产品销量影响研究,最后是在线评论对新旧产品销量影响的对比分析。 本文通过实证数据分析,发现在线评论数量、在线评论离散系数和价格对产品销量有显著影响,好评率在低于0.9时,对产品销量有影响,在高于0.9时无显著影响,评论数对新产品的影响大于对旧产品即旧产品的影响。在数据分析的基础上本文提出了在线评论系统设计以及评论管理相关建议。
[Abstract]:The popularity of the Internet has led to the vigorous development of e-commerce, online shopping more and more favored by consumers. Compared with traditional offline shopping, online shopping increases consumers' uncertainty about the quality of products and services. In order to reduce the uncertainty of consumers, shopping websites have established user evaluation systems. The CNNIC survey shows that online reviews are the most important factors affecting consumers' purchasing decisions. At the same time, online reviews have attracted great attention in academic circles. The research on online reviews can be divided into two categories, one is the impact of online reviews on consumers' willingness to buy at the individual level. The other is the impact of online reviews on product sales at the market level. On the basis of reading a lot of relevant literature at home and abroad, this paper summarizes the research on online review. Due to the different degree of dependence of users on online reviews, this paper attempts to explore the impact of online reviews on the sales of new and old products and their differences. Based on the consumer purchase decision behavior theory, innovation diffusion theory, information overload theory and information value theory, the author puts forward the research hypothesis of this paper. Combined with the literature research, we can identify the number of comments, the uniform distribution of the number of comments, the rate of praise, the rate of poor evaluation as the explanatory variable, the price of the product as the control variable, which together affect the sales volume of the products on the trading website. In addition to the conventional variables such as the number of comments and the tendency of comment emotion, this paper focuses for the first time on the impact of the distribution of the number of comments on sales. In this paper, crawler software is used to grab the product information and comment information of mobile phone products in JingDong Mall. According to the different time on shelves, the mobile phone is divided into new products and early products (old products). The detailed analysis is made up of three parts. The first is the comparative analysis of the behavior of consumers' reviews of new and old products, the second is the impact of online reviews on product sales, and the last is the comparative analysis of the impact of online reviews on the sales of new and old products. Through the empirical data analysis, it is found that the quantity of online reviews, the dispersion coefficient and price of online reviews have significant effects on the sales volume of products. When the praise rate is lower than 0.9, it has an impact on the sales volume of products, but it has no significant effect on the sales when it is higher than 0.9. The effect of the number of comments on the new product is greater than on the old product, that is, the old product. On the basis of data analysis, this paper puts forward some suggestions on the design of online comment system and comment management.
【学位授予单位】：北京邮电大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F724.6;F224
本文编号：2186667
[Abstract]:The popularity of the Internet has led to the vigorous development of e-commerce, online shopping more and more favored by consumers. Compared with traditional offline shopping, online shopping increases consumers' uncertainty about the quality of products and services. In order to reduce the uncertainty of consumers, shopping websites have established user evaluation systems. The CNNIC survey shows that online reviews are the most important factors affecting consumers' purchasing decisions. At the same time, online reviews have attracted great attention in academic circles. The research on online reviews can be divided into two categories, one is the impact of online reviews on consumers' willingness to buy at the individual level. The other is the impact of online reviews on product sales at the market level. On the basis of reading a lot of relevant literature at home and abroad, this paper summarizes the research on online review. Due to the different degree of dependence of users on online reviews, this paper attempts to explore the impact of online reviews on the sales of new and old products and their differences. Based on the consumer purchase decision behavior theory, innovation diffusion theory, information overload theory and information value theory, the author puts forward the research hypothesis of this paper. Combined with the literature research, we can identify the number of comments, the uniform distribution of the number of comments, the rate of praise, the rate of poor evaluation as the explanatory variable, the price of the product as the control variable, which together affect the sales volume of the products on the trading website. In addition to the conventional variables such as the number of comments and the tendency of comment emotion, this paper focuses for the first time on the impact of the distribution of the number of comments on sales. In this paper, crawler software is used to grab the product information and comment information of mobile phone products in JingDong Mall. According to the different time on shelves, the mobile phone is divided into new products and early products (old products). The detailed analysis is made up of three parts. The first is the comparative analysis of the behavior of consumers' reviews of new and old products, the second is the impact of online reviews on product sales, and the last is the comparative analysis of the impact of online reviews on the sales of new and old products. Through the empirical data analysis, it is found that the quantity of online reviews, the dispersion coefficient and price of online reviews have significant effects on the sales volume of products. When the praise rate is lower than 0.9, it has an impact on the sales volume of products, but it has no significant effect on the sales when it is higher than 0.9. The effect of the number of comments on the new product is greater than on the old product, that is, the old product. On the basis of data analysis, this paper puts forward some suggestions on the design of online comment system and comment management.
【学位授予单位】：北京邮电大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F724.6;F224
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