With the growth of e-commerce, online product reviews have become a major information source in consumer purchase decisions. However, anyone can easily provide product review in the manner of anonymous, which may lead to the enormous amount of reviews available for consumers and the manipulation behavior of reviews by vendors. Therefore, many website owners have invested in rating systems that allow consumers to provide and read product review not only on product per se, but also on the credibility of the review content and reviewer. In other words, the “helpfulness” feature of online product reviews helps consumers cope with information overloads and facilitates decision-making. A few recent studies have explored the helpfulness of online customer review, but we still know very little about why a customer perceives a particular review to be helpful or not helpful. Drawing on the elaboration likelihood model (ELM), the objective of this study is to investigate the effects of online review factors on perceived helpfulness from the content quality and the source credibility. More specifically, we investigate two information processing modes – central route (argument quality) and peripheral route (source credibility) in motivating reader’s helpful voting for product reviews. Furthermore, the study also examines the extent to which review quality and source credibility influence the formation of helpful perception is moderated by the product price that consumer actually payment. For this research, online product reviews were collected from ipeen.com.tw using a Web data crawler.
Mei-Ju Chen, Chienkuo Technology University, Taiwan
Stream: Computational Social Science
This paper is part of the ACSS2015 Conference Proceedings (View)
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