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Modeling consumer learning from online product reviews

机译：从在线产品评论中模拟消费者学习

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摘要

Experiential products such as books, movies etc., unlike other products are consumed solely for the personal pleasure and experiences and are less repetitive in nature. However there is uncertainty that the specific product/item matches the consumer's preference. Therefore, consumers rely on either past experience or other consumer reviews. The research work has tried to propose a model that examines both types of learning: from one's own experience with the category and from information about others' experiences with the specific product especially using online consumer reviews. The proposed model also takes into account the review credibility which is termed as the precision with which product reviews reflect the consumer's own product evaluation. The Bayesian learning framework to model consumer learning on both product quality and review credibility has been extended. The proposed model was been applied to a panel data set comprising 1,919 book purchases by 243 consumers at a large product reviews website. The empirical analysis in terms of three unique findings has been discussed.
机译：与其他产品不同的是，诸如书籍，电影等体验性产品仅出于个人娱乐和体验而消费，并且本质上没有重复性。但是，不确定特定产品/项目是否符合消费者的偏好。因此，消费者依赖于过去的经验或其他消费者评论。研究工作试图提出一个模型来研究两种学习类型：从一个人自己对类别的经验以及从他人对特定产品的经验的信息，特别是使用在线消费者评论的信息。所提出的模型还考虑了审核可信度，这被称为产品审核反映消费者自己的产品评估的精度。扩展了贝叶斯学习框架，该模型在产品质量和评论信誉方面为消费者学习建模。提议的模型已应用于面板数据集，该数据集包含243个消费者在大型产品评论网站上购买的1919本书。讨论了三个独特发现的实证分析。

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  • 来源
    《Operations Research》 |2014年第2期|67-69|共3页
  • 作者

    Yi Zhao; Sha Yang; Vishal Narayan; Ying Zhao;

  • 作者单位

    J. Mack Robinson College of Business, Georgia State University,Atlanta, GA 30303;

    Marshall School of Business, University of Southern California,Los Angeles, CA 90089;

    Samuel Curtis Johnson Graduate School of Management,Cornell University, Ithaca, NY 14853;

    Hong Kong University of Science and Technology,Clearwater Bay, Kowloon, Hong Kong;

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