Follow My Lead? Impacts of Multidimensional Expert Reviews on Subsequent Consumer Ratings
研究汽车评论平台上多维专家评价如何影响后续消费者评分，发现专家评价通过信息披露效应提升消费者评分，且该效应受专家评分效价、专家与消费者评分差异及专家评分方差等因素调节。
To mitigate information asymmetry, Expert Review Programs, in which experts evaluate products on multiple dimensions, have gained traction on platforms. However, the role of multidimensional expert reviews and how they affect consumer behaviors remain unknown. Using an empirical opportunity on an automobile review platform, we investigate how multidimensional expert reviews affect subsequent consumer ratings and the underlying mechanism. Our findings first reveal that expert reviews tend to be neutral and more critical than consumer ratings. We then find that consumers provide reviews with higher ratings following expert reviews due to the information disclosure effect. Decomposing the effect by expert reviews’ multidimensional characteristics, we find the effect is attenuated by multidimensional expert rating valence and multidimensional rating discrepancy between experts and consumers but amplified by multidimensional expert rating variance. Natural language processing of consumer review texts unveils a positive impact of multidimensional expert reviews on consumer satisfaction and a negative impact on consumer disappointment, which speaks to the underlying mechanism behind the information disclosure effect. Lastly, we find that the effect varies with expert characteristics, product characteristics, and information channels, diminishes when multidimensional expert reviews are posted sooner after product launch, and decays over time but persists in the long run. These findings not only advance information theories in understanding expert reviews and multidimensional rating systems but also provide valuable insights for stakeholders, such as platforms, firms, and expert reviewers, to improve review program operations and consumer engagement.