有用性
产品(数学)
可靠性
广告
过程(计算)
信息过载
营销
计算机科学
业务
心理学
万维网
社会心理学
操作系统
数学
法学
政治学
几何学
作者
Hyunmi Baek,JoongHo Ahn,Youngseok Choi
标识
DOI:10.2753/jec1086-4415170204
摘要
With the growth of e-commerce, online consumer reviews have increasingly become important sources of information that help consumers in their purchase decisions. However, the influx of online consumer reviews has caused information overload, making it difficult for consumers to choose reliable reviews. For an online retail market to succeed, it is important to lead product reviewers to write more helpful reviews, and for consumers to get helpful reviews more easily by figuring out the factors determining the helpfulness of online reviews. For this research, 75,226 online consumer reviews were collected from Amazon.com using a Web data crawler. Additional information on review content was also gathered by carrying out a sentiment analysis for mining review text. Our results show that both peripheral cues, including review rating and reviewer's credibility, and central cues, such as the content of reviews, influence the helpfulness of reviews. Based on dual process theories, we find that consumers focus on different information sources of reviews, depending on their purposes for reading reviews: online reviews can be used for information search or for evaluating alternatives. Our findings provide new perspectives to online market owners on how to manage online reviews on their Web sites.
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