Online consumer reviews (OCRs) have become an important part of online consumers’ decision-making to purchse products. Consumers use OCRs not only to get a better understanding of the characteristics of products but also to learn about other customers’ experiences with them. Drawing upon Elaboration Likelihood Model, this research investigates the predictors of popularity and helpfulness of OCRs. The results of the study show that longer reviews, as well as those with extreme star ratings, are more popular. Moreover, the amount of hedonic and utilitarian cues in a review and its sentiment significantly influence perceptions of online consumers regarding its helpfulness. The results also show how product type moderates the effect of utilitarian and hedonic cues on helpfulness. Our results can be used by online review websites to develop more efficient methods for sorting OCRs.

在线消费者评论（OCR）已成为在线消费者购买产品决策的重要组成部分。消费者使用OCR不仅可以更好地了解产品的特性，还可以了解其他客户对它们的体验。利用精细加工可能性模型，本研究调查了OCR受欢迎程度和有用性的预测因素。研究结果表明，较长的评论以及具有极高星级的评论更受欢迎。此外，评论中的享乐主义和功利主义线索的数量及其情绪会显着影响在线消费者对其帮助的看法。结果还显示产品类型如何缓解功利主义和享乐主义提示对帮助的影响。