The effect of different types of comparative reviews on product sales

Comparative online reviews have evolved into a vital instrument for consumers in decision-making, offering valuable comparisons and available options. Drawing on the insights from the linguistic category model (LCM) and elaboration likelihood model (ELM), we propose that different types (attribute-based and experience-based) of comparative reviews can affect consumers' perceived credibility of online reviews, thus impacting product sales. We analyzed 136,260 reviews on e-commerce platforms to assess these effects and introduced review valence as a boundary condition. Utilizing a combination of pattern discovery, supervised learning techniques, and manual coding, we identified attribute-based and experience-based comparative reviews and subsequently classified them based on positive, neutral, and negative valence. Subsequently, we took the product sales as the dependent variable and applied a two-way fixed effects model. The results indicate that attribute-based comparative reviews exert a more favorable influence on product sales compared to experience-based ones. Additionally, positive comparative reviews, irrespective of their attribute-based or experience-based nature, demonstrate a greater impact than regular positive reviews. However, negative and neutral comparative reviews, only when associated with attribute-based information, exhibit a significant effect. The results highlight the value of different types of comparative reviews and illuminate the moderating role of review valence. Our findings offer new insights and practical guidance for marketers and e-commerce platforms in capitalizing on the important influence of comparative reviews and enhancing the presentation of online reviews.