Distribution characteristics of star ratings in online consumer reviews

Vilakshan XIMB Journal of Management Pub Date : 2020-12-21 DOI:10.1108/xjm-10-2020-0171

R. Venkatesakumar, S. Vijayakumar, S. Riasudeen, S. Madhavan, B. Rajeswari

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引用次数: 2

Abstract

Purpose The star rating summarises the review content and conveys the message faster than other review components. Star ratings influence helpfulness of the reviews, and extreme reviews are considered as less helpful in the decision process. However, literature has rarely addressed variations in star ratings across product categories and variations between two online retailers. In this paper, the authors have compared the distribution of star ratings across 11 products and among the retailers. Design/methodology/approach Online reviews for 11 product categories have collected, and the authors compared the distribution of star ratings across 11 products and retailers. Correspondence analysis has been applied to show the association between star ratings and product categories for the e-retail firms. Findings The Amazon site contains proportionately more number of 1-star rated reviews than Flipkart. In Amazon reviews, few product categories are closely associated with 1-star and 2-star reviews, whereas no product categories are closely associated with 1-star and 2-star reviews in Flipkart reviews. The results indicate two distinct communication strategies followed by the firms in managing online consumer reviews. Research limitations/implications The authors did not analyse data across demographic details because of access restriction policies of the websites. Practical implications Understanding the distribution of review characteristics will improve the consumer’s decision-making ability and using online review content judiciously. Social implications This study’s results show significant insights on online retailing by providing cues in using shopping sites and online review characteristics of two prominent retailers. Originality/value This paper has brought out a distinct distribution pattern of online review between Amazon and Flipkart. Amazon allows a higher degree of negative contents, whereas Flipkart allows more number of positive reviews.

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在线消费者评论中星级评价的分布特征

目的星级评价比其他评价成分更能概括评价内容，传达信息。星级评价影响评价的有用性，极端评价在决策过程中被认为是不太有用的。然而，文献很少涉及产品类别和两个在线零售商之间星级评级的差异。在本文中，作者比较了11种产品和零售商之间的星级评分分布。设计/方法/方法在线收集了11种产品类别的评论，作者比较了11种产品和零售商的星级评分分布。对应分析已经被应用于显示电子零售公司的星级和产品类别之间的关联。调查结果亚马逊网站的一星评论数量比Flipkart多。在亚马逊的评论中，很少有产品类别与1星和2星的评论密切相关，而在Flipkart的评论中，没有产品类别与1星和2星的评论密切相关。结果表明，两种不同的沟通策略遵循的公司管理在线消费者评论。研究局限性/启示:由于网站的访问限制政策，作者没有分析人口统计细节的数据。实际意义了解评论特征的分布将提高消费者的决策能力，明智地使用在线评论内容。社会影响本研究的结果通过提供使用购物网站的线索和两家知名零售商的在线评论特征，显示了对在线零售的重要见解。原创性/价值本文提出了亚马逊和Flipkart在线评论的独特分布模式。亚马逊允许更多的负面内容，而Flipkart允许更多的正面评论。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Vilakshan XIMB Journal of Management

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审稿时长

10 weeks