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

Nan Hu, H. Cavusoglu, Lingbing Liu, Chenkai Ni
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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.
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。
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