Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4937521 | Computers in Human Behavior | 2017 | 9 Pages |
Abstract
This paper analyzes review efficacy on Amazon.com. Specifically, review efficacy is conceptualized as the readership and the helpfulness of reviews submitted on the website. Informed by the Matthew effect and the Ratchet effect- “the rich grow richer and the poor grow poorer,” the paper examines if reviews submitted by reputed reviewers are deemed more efficacious compared with those contributed by novices. A research framework is proposed to identify antecedents that could promote review efficacy. The antecedents include both quantitative and qualitative aspects related to review titles and descriptions. Three key findings are gleaned from the results. First, the antecedents of review readership are not necessarily identical to those of review helpfulness. Second, both titles and descriptions of reviews are related to review efficacy. Third, the antecedents of review efficacy are different for reputed and novice reviewers. The paper concludes by highlighting its theoretical contributions and implications for practice.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Alton Y.K. Chua, Snehasish Banerjee,