在线评论对创新扩散影响的实证研究

发布时间：2018-04-28 21:12

本文选题：创新扩散 + 在线评论　；参考：《浙江大学》2012年硕士论文

【摘要】：随着互联网技术融入人们的日常生活、电子商务的迅速发展壮大,以互联网为媒介的创新扩散越来越受到学者和企业的重视。人们逐渐习惯在网上交换关于产品的信息和看法,其中,在线评论成为人们信息交流的重要方式之一。在线评论为消费者提供产品信息,降低消费者购买不确定性,成为影响消费者采纳决策的重要因素,从而对创新扩散过程产生重要的影响。本文根据创新扩散的微观个体决策模型,从主观效用和社会影响两个方面,分析在线评论对创新扩散的影响机理。在文献研究和案例分析的基础之上,本文将在线评论的主要影响因素分为在线评分、评论有用性、评论数量、评论者特征以及评论时间等,并且提出了在线评论对创新扩散的影响模型。本文通过统计分析对模型及相关假设进行了验证,利用SPSS统计分析软件对豆瓣书评网站的100本图书以及相应的861条在线评论进行聚类分析以及多元线性回归分析,得到以下结论： (1)在线评分对创新扩散的正向影响不显著,但在线评分高是创新扩散速度快的必要非充分条件。(2)评论有用性、评论数量对创新扩散产生显著的正向影响,即评论有用性越高或者评论数量越多,创新扩散速度越快。(3)评论者的特征对在线评论影响创新扩散的过程起显著的调节作用。(4)评论出现的时间越早,则评论有用性对创新扩散的正向效应越大。
[Abstract]:With the integration of Internet technology into people's daily life and the rapid development of e-commerce, scholars and enterprises pay more and more attention to the diffusion of innovation based on the Internet. People are gradually used to exchange information and opinions about products on the Internet. Among them, online reviews become one of the important ways for people to exchange information. Online reviews provide consumers with product information, reduce consumer purchase uncertainty, and become an important factor affecting consumer adoption decisions, thus having an important impact on innovation diffusion process. According to the micro individual decision model of innovation diffusion, this paper analyzes the influence mechanism of online comment on innovation diffusion from two aspects: subjective utility and social influence. On the basis of literature research and case study, this paper divides the main influencing factors of online review into online rating, comment usefulness, number of comments, reviewer characteristics and comment time, etc. The influence model of online comment on innovation diffusion is put forward. This paper verifies the model and related hypotheses by statistical analysis, and makes cluster analysis and multivariate linear regression analysis of 100 books and 861 online reviews of Douban Book Review website by using SPSS software. The following conclusions were drawn: (1) the positive effect of online scoring on innovation diffusion is not significant, but high online rating is a necessary and insufficient condition for rapid innovation diffusion, and the number of comments has a significant positive impact on innovation diffusion. That is, the higher the usefulness or the number of reviews, the faster innovation diffuses. (3) the characteristics of reviewers play a significant role in regulating the process of online reviews affecting innovation diffusion. The positive effect of comment usefulness on innovation diffusion is greater.
【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：F49;F224

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