评分不一致性对在线评论有用性的影响——归因理论的视角

哪些因素会影响在线评论的有用性一直是理论界和实践界都十分关心的问题，但现有研究对在线评论的星级评分是如何影响评论有用性这一问题仍未形成统一的结论。基于此，本文以归因理论为分析框架，构建了在线评论的星级评分与产品的平均星级间的不一致性对评论有用性的影响的研究模型，并重点探讨产品的评论总量以及评论的星级评分和平均星级间差异的方向对这一影响的调节作用。本文以携程网上832233条酒店评论为样本，采用零膨胀负二项回归方法对理论模型进行了实证检验，研究结果表明，评分不一致性对评论的有用性有显著的负向影响，而某种产品的评论总量以及星级评分和平均星级间差异的方向对评分不一致性和评论有用性间的关系起到调节作用。当产品的评论总量越高或评论的星级评分与产品的平均星级间的差异为正向差异时，评分不一致性对评论有用性的负向影响越强。本文的研究成果既为理解在线评论有用性提供了理论贡献，也有助于电子商务或第三方评论网站管理和应用在线评论。

The Impact of Rating Inconsistency on Online Review Helpfulness: A Perspective on Attribution Theory

Helpful online reviews can decrease information overload, help customers make better decisions and increase customers' satisfaction about the websites. Therefore, so what makes a helpful online review has become an important topic for scholars and practitioners. Individual review rating has been investigated to be an import factor impacting the review helpfulness by the extant literature, but the literature provides inconsistent views on the direction of the impact. From the perspective of attribution theory, the inconsistent findings are reconciled by proposing the inconsistency between the individual review rating and the average rating as a factor influencing review helpfulness and taking the number of product reviews and the direction of rating inconstitency as moderators. 832233 online hotel reviews are collected from Ctrip.com using a Web data crawler and analyzed by zero-inflated negative binomial regression model. The empirical results show that rating inconsistency has a significant negative impact on review helpfulness. The high rating inconsistency will lead consumers' non-product-related attributions of the review and decrease the review helpfulness. The number of product reviews and the direction of rating inconsistency moderate the impact of rating inconsistency on review helpfulness. The impacts are more salient for the reviews with high product review volumns and for the reviews whose rating is bigger than the average rating. Our findings provide new perspective for understanding the review helpfulness and for online market owners on how to design online review systems and manage reviews on their websites.