What happens when platforms disclose the purchase history associated with product reviews?

IF 6.7 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Miaomiao Liu , Xiaohua Zeng , Cheng Zhang , Yong Liu
{"title":"What happens when platforms disclose the purchase history associated with product reviews?","authors":"Miaomiao Liu ,&nbsp;Xiaohua Zeng ,&nbsp;Cheng Zhang ,&nbsp;Yong Liu","doi":"10.1016/j.dss.2024.114367","DOIUrl":null,"url":null,"abstract":"<div><div>In striking a balance between attracting more product reviews versus maintaining review quality, online platforms have started to label reviews with whether they are associated with verifiable purchases. This paper examines the impact of such disclosure policy on the strategic behavior of review writers and the helpfulness of verified reviews (VRs) and non-verified reviews (NVRs) for review users. We propose that the introduction of the verified purchase tag induces two competing effects for VRs, increased credibility and concerns for acquisition bias, which in turn influence the behaviors of both writers and users. By exploiting the exogenous shock resulting from a policy change on Amazon, we find that, after the disclosure, NVRs became longer in length and VRs started to contain more unique information. Surprisingly, we find strong evidence that VRs receive fewer helpfulness votes than NVRs. We further explore the underlying mechanism, namely review users' concerns about acquisition bias associated with VRs, and identify conditions under which these unexpected effects can be mitigated. Our findings generate important implications for online platforms seeking to design a more effective review ecosystem and for review writers aiming to produce more helpful content.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"188 ","pages":"Article 114367"},"PeriodicalIF":6.7000,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Decision Support Systems","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167923624002008","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

Abstract

In striking a balance between attracting more product reviews versus maintaining review quality, online platforms have started to label reviews with whether they are associated with verifiable purchases. This paper examines the impact of such disclosure policy on the strategic behavior of review writers and the helpfulness of verified reviews (VRs) and non-verified reviews (NVRs) for review users. We propose that the introduction of the verified purchase tag induces two competing effects for VRs, increased credibility and concerns for acquisition bias, which in turn influence the behaviors of both writers and users. By exploiting the exogenous shock resulting from a policy change on Amazon, we find that, after the disclosure, NVRs became longer in length and VRs started to contain more unique information. Surprisingly, we find strong evidence that VRs receive fewer helpfulness votes than NVRs. We further explore the underlying mechanism, namely review users' concerns about acquisition bias associated with VRs, and identify conditions under which these unexpected effects can be mitigated. Our findings generate important implications for online platforms seeking to design a more effective review ecosystem and for review writers aiming to produce more helpful content.
当平台披露与产品评论相关的购买记录时会发生什么?
为了在吸引更多产品评论和保持评论质量之间取得平衡,在线平台开始标注评论是否与可验证的购买相关联。本文研究了这种披露政策对评论作者策略行为的影响,以及已验证评论(VR)和未验证评论(NVR)对评论用户的帮助。我们认为,经过验证的购买标签的引入会对 VR 产生两种竞争效应:可信度的提高和对获取偏差的担忧,这反过来又会影响撰写者和用户的行为。通过利用亚马逊政策变化带来的外生冲击,我们发现,在政策披露后,NVR 的长度变长,VR 开始包含更多独特信息。令人惊讶的是,我们发现了强有力的证据,表明 VR 比 NVR 获得的有用性投票更少。我们进一步探讨了其背后的机制,即评论用户对与 VR 相关的获取偏差的担忧,并确定了可以减轻这些意外影响的条件。我们的发现对寻求设计更有效的评论生态系统的在线平台和旨在制作更有帮助内容的评论作者具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Decision Support Systems
Decision Support Systems 工程技术-计算机:人工智能
CiteScore
14.70
自引率
6.70%
发文量
119
审稿时长
13 months
期刊介绍: The common thread of articles published in Decision Support Systems is their relevance to theoretical and technical issues in the support of enhanced decision making. The areas addressed may include foundations, functionality, interfaces, implementation, impacts, and evaluation of decision support systems (DSSs).
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信