{"title":"Exploring an incongruence frame for online reviews","authors":"Praveen Sugathan, Subin Sudhir, Rahul Ramachandran","doi":"10.1002/cb.2384","DOIUrl":null,"url":null,"abstract":"Given the growth in the internet and e‐retailing, consumers are extremely reliant on online user‐generated reviews (“reviews”) for decision‐making. Reviews often combine informational cues such as numeric (i.e., star) ratings and qualitative text, and these may not always be in alignment. To understand conflicting informational cues, this research conceptualizes and tests an incongruence frame that captures the inconsistency between a review's textual and numeric message cue components. Incongruence occurs when the valence of the review text is not in alignment with the product star rating given by the reviewer. To further qualify the findings, the paper introduces two types of incongruences: Type A (Type B) is categorized as involving low (high) star ratings alongside a positive (negative) review text. The research findings shed light on an underexplored dimension of review processing based on inconsistency between the textual and numeric components of a single review. Using primary and secondary data across four studies, the incongruence effect is shown to undermine review usage. Incongruence is found to influence both review diagnosticity and review authenticity. The initial heuristics of review evaluation generate differential effects between Type A and Type B. Incongruence in the review is also shown to influence product purchases. The incongruence frame, therefore, helps reconcile some of the inconsistencies in the extant literature and offers fruitful avenues of future research for both academics and practitioners.","PeriodicalId":48047,"journal":{"name":"Journal of Consumer Behaviour","volume":null,"pages":null},"PeriodicalIF":4.4000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Consumer Behaviour","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1002/cb.2384","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0
Abstract
Given the growth in the internet and e‐retailing, consumers are extremely reliant on online user‐generated reviews (“reviews”) for decision‐making. Reviews often combine informational cues such as numeric (i.e., star) ratings and qualitative text, and these may not always be in alignment. To understand conflicting informational cues, this research conceptualizes and tests an incongruence frame that captures the inconsistency between a review's textual and numeric message cue components. Incongruence occurs when the valence of the review text is not in alignment with the product star rating given by the reviewer. To further qualify the findings, the paper introduces two types of incongruences: Type A (Type B) is categorized as involving low (high) star ratings alongside a positive (negative) review text. The research findings shed light on an underexplored dimension of review processing based on inconsistency between the textual and numeric components of a single review. Using primary and secondary data across four studies, the incongruence effect is shown to undermine review usage. Incongruence is found to influence both review diagnosticity and review authenticity. The initial heuristics of review evaluation generate differential effects between Type A and Type B. Incongruence in the review is also shown to influence product purchases. The incongruence frame, therefore, helps reconcile some of the inconsistencies in the extant literature and offers fruitful avenues of future research for both academics and practitioners.
随着互联网和网络零售的发展,消费者在做出决策时非常依赖网上用户产生的评论("评论")。评论通常结合了数字(即星级)评分和定性文字等信息线索,而这些信息线索并不总是一致的。为了理解相互冲突的信息线索,本研究构思并测试了不协调框架,该框架捕捉了评论的文字和数字信息线索之间的不一致性。当评论文本的价值与评论者给出的产品星级不一致时,就会出现不一致。为了进一步证实研究结果,本文引入了两种不一致类型:A 类(B 类)被归类为涉及低(高)星级评价以及正面(负面)评论文本。研究结果揭示了评论处理中一个未被充分探索的方面,即单篇评论的文字和数字部分之间的不一致性。通过使用四项研究的主要数据和二手数据,不一致效应被证明会影响评论的使用。研究发现,不一致会影响评论的诊断性和真实性。评论评价的初始启发式在 A 型和 B 型之间产生不同的效果。因此,不一致性框架有助于调和现有文献中的一些不一致之处,并为学术界和从业人员提供了富有成效的未来研究途径。
期刊介绍:
The Journal of Consumer Behaviour aims to promote the understanding of consumer behaviour, consumer research and consumption through the publication of double-blind peer-reviewed, top quality theoretical and empirical research. An international academic journal with a foundation in the social sciences, the JCB has a diverse and multidisciplinary outlook which seeks to showcase innovative, alternative and contested representations of consumer behaviour alongside the latest developments in established traditions of consumer research.