摘要
随着互联网的迅速发展,消费者购物决策越来越依赖于在线评论。从信息接受模型对信息有用性影响出发,构建在线评论有用性投票增量的时间窗,建立在线评论有用性影响因素模型,研究在线评论内容和评论者对在线评论有用性的影响。基于Trip Advisor.com的4 258条酒店评论数据,运用负二项回归进行实证分析。研究发现评论内容长度、评论极端性、评论有用性投票数、评论者认可度和个人信息披露对在线评论有用性具有显著正影响,这对在线零售商和消费者具有重要的启发和建议。
With rapid development of the Internet,consumers have increasingly relied on online reviews prior to making purchase decisions.This paper discussed the determinants of helpfulness of online consumer reviews from the perspective of information adoption model.By designing time window of helpful votes and building concept model of review helpfulness,the paper mainly discussed the influence of review content and reviewers’ characteristics on review helpfulness.Based on 4258 hotel review data of Tripadvisor.com,the paper did empirical analysis by using negative binomial regression.The results found that review length,rating extremity,number of helpful votes,peer recognition and information disclosure have significantly positive influence on review helpfulness.The conclusions would give some important implications and suggestions for both online retailers and consumers.
出处
《现代情报》
CSSCI
北大核心
2015年第4期52-56,74,共6页
Journal of Modern Information
关键词
在线评论
评论有用性
负二项回归
大数据
online reviews
review helpfulness
negative binomial regression
big data