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中国管理科学 ›› 2016, Vol. 24 ›› Issue (9): 106-114.doi: 10.16381/j.cnki.issn1003-207x.2016.09.013

• 论文 • 上一篇    下一篇

基于社会学习理论的在线评论信息对购买决策的影响研究

冯娇, 姚忠   

  1. 北京航空航天大学经济管理学院, 北京 100191
  • 收稿日期:2014-11-26 修回日期:2015-11-22 出版日期:2016-09-20 发布日期:2016-09-30
  • 通讯作者: 姚忠(1964-),男(汉族),河北人,北京航空航天大学经济管理学院,教授,研究方向:电子商务与数据挖掘,E-mail:iszhyao@buaa.edu.cn. E-mail:iszhyao@buaa.edu.cn
  • 基金资助:

    国家自然科学基金资助重点项目(71332003);国家自然科学基金资助项目(71271012,71671011)

Consumer-Generated Reviews Based on Social Learning Theory: Implications for Purchase Decision

FENG Jiao, YAO Zhong   

  1. Department of Economics and Management, Beihang University, Beijing 100191, China
  • Received:2014-11-26 Revised:2015-11-22 Online:2016-09-20 Published:2016-09-30

摘要: 消费者在线商品评论对电商企业提高销售业绩,消费者制定购买决策等都有重要作用。本文基于社会学习理论,运用贝叶斯和高斯更新公式构建社会学习模型,分析消费者通过社会学习评论数量和等级对其购买决策的差异性影响,并深入探析评论数量和等级的内在关系,运用数值试验和电子商务网站获取的真实数据,验证了模型和结论的有效性。结果表明评论等级与评论数量存在负相关关系,评论等级随销售量和评论数量增加而下降; 但当评论数量达到某值后,评论等级受评论数量影响不大,评论等级对销售量有积极作用,评论数量对高质量产品销售量有积极作用,对低质量产品销售量没有积极影响。本文结果说明评论数量和等级在不同销售期对不同产品的购买决策有差异性影响,从而有利于电商企业在不同销售期制定相应的营销策略。

关键词: 电子商务, 社会学习, 在线评论, 评论数量, 评论等级

Abstract: Consumer-generated reviews play an important role in improving sales, and making purchase decisions, so it has become a hot topic of academic study. Based on social learning theory, Bayesian and Gaussian updated formula, mathematic models are established to analyze different influence of volume of consumer-generated reviews and rating of consumer-generated reviews on consumers' purchase decisions, and then the relationship between volume of consumer-generated reviews and rating of consumer-generated reviews is deeply discussed, and numerical experiments and practical data from Taobao.com and Amazon.com are also used to verify the effectiveness of the models and results. The results show that, the rating of consumer-generated reviews is decreasing as the growth of the volume of consumer-generated reviews, and the decline of the rating of consumer-generated reviews gradually slows down. But when the rating of consumer-generated reviews is (almost) converged into the real quality, the volume of consumer-generated reviews has little impact on the rating of consumer-generated reviews. When the volume of consumer-generated reviews is independent of the rating of consumer-generated reviews, the rating of consumer-generated reviews has a positive effect on purchase decision, and the volume of consumer-generated reviews has a positive effect on purchase decision of high-quality product, but not has a positive effect on purchase decision of low-quality product. The volume of consumer-generated reviews and the rating of consumer-generated reviews play different roles in purchase decisions of different products in different selling periods, and the research findings help online retailers adopt suitable marketing strategies.

Key words: electronic commerce, social learning, consumer-generated reviews, volume of consumer-generated reviews, rating of consumer-generated reviews

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