Xiaoling Lu, Yuzhu Li, Zhe Zhang, Bharatendra Rai
Consumers who lack personal experience with online products and virtual shops perceive a high level of risk in the ecommerce context. Consumers need to learn about online products and vendors before they make a purchase decision. Electronic word-of-mouth (eWOM) is a medium for such learning that not only includes specific recommendations about online products and vendors, but also supports social interaction among past and potential future consumers on transaction platforms. Based upon consumer learning theories and the Elaboration Likelihood Model, this study proposes a framework for the analysis of how eWOM carries consumer learning and influences future consumers. Based on the proposed framework, a large set of consumer-generated reviews of online transactions was analyzed using content analysis methodology. After the categorization of review messages with learning cues by review valence, our study examined the impact of buyers’ experience levels on the development of review content. The results showed that the experienced buyers tended to deliver more social cues and the novice buyers included more transactional cues in text reviews. In addition, the results indicate that consumer learning dimensions are not independent of review valence. Our study provides insights into theoretical and practical implications.