Academic journal article Journal of Electronic Commerce Research

Consumer Learning Embedded in Electronic Word of Mouth

Academic journal article Journal of Electronic Commerce Research

Consumer Learning Embedded in Electronic Word of Mouth

Article excerpt

1. Introduction

With 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; Gutiérrez 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]. In the ecommerce context, consumers learn by observing sales volume, reviewing others' recommendations and advice in text comments, seeking information that confirms prior judgment [Mudambi and Schuff, 2010; Chen, et al., 2011; Cheung et al., 2012].

The past literature has studied observational learning (learning by observing summary sales statistics) and cognitive processing of eWOM messages in the ecommerce environment [Hennig-Thurau et al. 2004; Cheung and Lee, 2012; Yap et al., 2013]. But past studies simply treated eWOM as opinion-based comments. We argue that EWOMs reflect past consumers' learning outcomes and form a valuable pool of knowledge as more eWOMs are generated. EWOM not only includes specific recommendations about products and vendors, but also facilitates social learning. EWOM becomes a representation of what past buyers have learned on a transaction platform and a source of information for potential future consumers to learn.

Because eWOM messages are processed by potential consumers to acquire new knowledge and form attitudes, this is a process of persuasion, in which communications between a message sender and a receiver influence message processing [Park and Lee, 2009; Cheung and Thadani, 2012]. Studies in persuasion have confirmed that the effectiveness of a persuasive communication is in part a function of message content learning [Greenwald, 1968]. …

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