Do Vendors’ Pricing Decisions Fully Reflect Information in Online Reviews?

Nan Hu, H. Cavusoglu, Lingbing Liu, Chenkai Ni
{"title":"Do Vendors’ Pricing Decisions Fully Reflect Information in Online Reviews?","authors":"Nan Hu, H. Cavusoglu, Lingbing Liu, Chenkai Ni","doi":"10.1145/2361256.2361261","DOIUrl":null,"url":null,"abstract":"By using online retail data collected from Amazon, Barnes & Nobel, and Pricegrabber, this paper investigates whether online vendors’’ pricing decisions fully reflect the information contained in various components of customers’ online reviews. The findings suggest that there is inefficiency in vendors’ pricing decisions. Specifically, vendors do not appear to fully understand the incremental predictive power of online reviews in forecasting future sales when they adjust their prices. However, they do understand demand persistence. Interestingly, vendors reduce price if the actual demand is higher than the expected demand (positive demand shock). This phenomenon is attributed to the advertising effect suggested in previous literature and the intense competitiveness of e-Commerce. Finally, we document that vendors do not change their prices directly in response to online reviews; their response to online reviews is through forecasting consumer’s future demand.","PeriodicalId":178565,"journal":{"name":"ACM Trans. Manag. Inf. Syst.","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Trans. Manag. Inf. Syst.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2361256.2361261","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

By using online retail data collected from Amazon, Barnes & Nobel, and Pricegrabber, this paper investigates whether online vendors’’ pricing decisions fully reflect the information contained in various components of customers’ online reviews. The findings suggest that there is inefficiency in vendors’ pricing decisions. Specifically, vendors do not appear to fully understand the incremental predictive power of online reviews in forecasting future sales when they adjust their prices. However, they do understand demand persistence. Interestingly, vendors reduce price if the actual demand is higher than the expected demand (positive demand shock). This phenomenon is attributed to the advertising effect suggested in previous literature and the intense competitiveness of e-Commerce. Finally, we document that vendors do not change their prices directly in response to online reviews; their response to online reviews is through forecasting consumer’s future demand.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
供应商的定价决策是否充分反映了在线评论中的信息?
本文通过使用亚马逊、Barnes & Nobel和Pricegrabber收集的在线零售数据,研究了在线供应商的定价决策是否充分反映了客户在线评论的各个组成部分所包含的信息。研究结果表明,供应商的定价决策存在低效率。具体来说,当供应商调整价格时,他们似乎并没有完全理解在线评论在预测未来销售方面的增量预测能力。然而,他们确实理解需求的持久性。有趣的是,如果实际需求高于预期需求(正需求冲击),供应商会降低价格。这一现象与以往文献中提出的广告效应和电子商务的激烈竞争有关。最后,我们记录了供应商不会直接根据在线评论改变他们的价格;他们对在线评论的反应是通过预测消费者未来的需求。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Using Social Media to Analyze Public Concerns and Policy Responses to COVID-19 in Hong Kong COVID-Safe Spatial Occupancy Monitoring Using OFDM-Based Features and Passive WiFi Samples SymptomID: A Framework for Rapid Symptom Identification in Pandemics Using News Reports Leveraging Individual and Collective Regularity to Profile and Segment User Locations from Mobile Phone Data Write Like a Pro or an Amateur? Effect of Medical Language Formality
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1