可靠性
启发式
价(化学)
明星(博弈论)
产品(数学)
广告
心理学
代理(统计)
排名(信息检索)
社会心理学
计算机科学
数学
业务
情报检索
物理
量子力学
操作系统
机器学习
数学分析
法学
政治学
几何学
作者
Seoyeon Hong,Matthew Pittman
标识
DOI:10.1080/02650487.2019.1703386
摘要
Consumers encounter many cues when making online purchases, particularly when reading product reviews. When competing heuristics are triggered, which emerges as more persuasive? This study explores online reviews of an Amazon-like platform to see how star ratings, numbers of reviews, and review valence provide cues to consumers which influence perceived credibility. Two experiments utilizing different samples provide converging evidence that negatively valanced reviews tend to supersede star ratings, with the number of reviews serving as a proxy for argument strength. When a review was positive, participants trusted the star ranking system, perceiving a high star ranking to be most credible. However, when a review is negative, an alternate heuristic leads to reduced credibility for star ratings, and participants instead placed greater importance on a high number of reviewers, trusting the eWOM "recommendation" of the reviewer. Theoretical and practical implications are discussed.
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