Swayed by the reviews: Disentangling the effects of average ratings and individual reviews in online word‐of‐mouth

口头传述的 产品(数学) 突出 营销 情感(语言学) 构造(python库) 对比度(视觉) 实证研究 心理学 业务 广告 计算机科学 统计 沟通 人工智能 程序设计语言 数学 几何学
作者
Zhanfei Lei,Dezhi Yin,Sabyasachi Mitra,Han Zhang
出处
期刊:Production and Operations Management [Wiley]
卷期号:31 (6): 2393-2411 被引量:20
标识
DOI:10.1111/poms.13695
摘要

Online word‐of‐mouth studies generally assume that a product's average rating is the primary force shaping consumers’ purchase decisions and driving sales. Similarly, practitioners place more emphasis on average ratings by displaying them at more salient places than individual reviews. In contrast, emerging evidence suggests that individual reviews also affect the decision‐making of those consumers who consult both kinds of information. However, because average ratings and individual reviews are often correlated and confounded empirically, little research has attempted to disentangle their effects. To address this empirical challenge, we construct trade‐off situations in which the average ratings and top‐ranked reviews of different product options do not align with each other. We then investigate consumers’ preferences that can indirectly reveal the relative impact of average ratings versus top reviews. Through an archival analysis of a panel dataset and two laboratory experiments, we find consistent evidence for a swaying effect of individual reviews and reveal their textual content as a likely reason. These findings challenge the commonly accepted assumption of average ratings being the primary driver of consumers’ purchase decisions and suggest that consumers may not be as rational as previous literature assumed. In addition, this paper is the first to disentangle the effects of average ratings and individual reviews on consumer decision‐making and explore a possible reason for the swaying effect of individual reviews. Our paper illustrates the importance of information accessibility in consumers’ purchase decisions, and our findings offer valuable insights for product manufacturers, online retailers, and review platforms.
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