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.
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