Consumer Learning Embedded in Electronic Word of Mouth

ABSTRACTConsumers 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.Keywords: Consumer learning; Electronic word-of-mouth (eWOM); Review valence; Elaboration Likelihood Model; Content analysis1. IntroductionWith the advent of the Web 2.0 paradigm, Internet users have multiple tools such as customer review systems, online discussion forums, and social network sites to share their opinions and exchange information. This new form of word-of-mouth (WOM), electronic WOM (eWOM), is characterized as any positive or negative messages available to any Internet user that is originated by past or potential future consumers about a product, service or company [Hennig-Thurau et al., 2004]. When Internet users make purchase decisions, they tend to trust online reviews generated by consumers and regard them as more persuasive than traditional advertisement from marketers and companies, and reports from third party consumer reporting companies [Goldsmith and Horowitz, 2006]. Industry reports state that 61% of consumers consult online reviews before making a new purchase and that they are essential for ecommerce websites [Charlton, 2012]. Research studies have found that EWOMs have a significant impact on product sales [Godes and Mayzlin, 2004; Forman et al., 2008; Lu et al., 2014]. In addition to its impact on product sales, eWOMs have been examined in terms of message senders, message receivers, eWOM characteristics, and in terms of its antecedents and effects on purchase intention and sales [Hennig-Thurau et al., 2004; Liu, 2006; Park and Kim, 2008; Yap et al., 2013].One area which has received only limited research attention is eWOM as a source of consumer learning in the ecommerce context [Chen et al., 2011; Cheung et al., 2012]. Consumers and e-retailers are physically and temporally separated on an online transaction platform such as Amazon or EBay [Lee, 1998; Gutierrez et al., 2010]. Consumers perceive a high level of risk in online shopping because they cannot personally interact with a product to determine its characteristics before making a selection. In addition, the lean online communication medium eliminates many social cues, such as body language, that consumers can use to analyze online vendors' trustworthiness.The process by which individuals acquire the purchase and consumption knowledge and experience they apply to future behavior is termed consumer learning [Schiffman and Kanuk, 1983]. Several consumer learning theories, including observational learning, cognitive learning and social learning, are widely studied in the marketing literature, which has found that in a traditional shopping context, consumers learn through direct experience such as the personal experience of product trial and through indirect experience such as word-of-mouth and third party consumer reports [Smith and Swinyard, 1983]. …