The Impact of Fake Reviews of Online Goods on Consumers

Author:

Cao Chuhua

Abstract

The fake product reviews on the Internet have brought great obstacles to consumers to make the right purchase decision. Fake reviews reduce the goodwill of e-commerce platforms and harm the interests of most merchants on the platforms. The appearance of fake reviews is easy to mislead consumers to make wrong decisions. Therefore, the research and identification of fake comments are urgent and significant. This paper will detailed discussion and analyze the impact of fake reviews on consumers from the perspective of the formation of consumers' purchase decisions. The four dimensions are demand cognition, looking for alternative plans, purchase decisions, and purchase behavior. Fake reviews may stimulate consumers' purchase desire by changing their demand perception. When evaluating alternative plans, they are affected by the reputation of merchants, etc., and fake reviews significantly affect the purchase decision. Consumers may make positive or negative comments after a purchase. When reviewers do not have expectations for the goods they receive, they become distrustful of the business and the platform, and they give emotionally negative reviews. If satisfied, positive publicity feedback will be given. This paper conducts literature and case studies on the impact of poor information on consumers caused by artificial evaluations and the prevention and control of fake reviews. The author will analyze the reasons for the occurrence of false comments and discuss how to prevent the occurrence of false information to the maximum extent, including the establishment of reward and punishment mechanisms, innovating the detection technology of fake commodity reviews to avoid unfair competition, and strengthening the control of real-name information on the Internet.

Publisher

Boya Century Publishing

Reference10 articles.

1. Miao R, Xu J. The impact of rating inconsistency on online review helpfulness: A perspective on attribution theory. Chinese Journal of Management Science, 2018, 26 (5): 178 - 186.

2. Zhang W, Du Y, Yoshida T, et al. DRIRCNN: An approach to deceptive review identification using recurrent convolutional neural network. Information Processing Management, 2018, 54 (4): 576 – 592.

3. Xing L. Legal regulation of online shopping credit hyping behavior. Law and Society, 2016, (15): 79 - 80.

4. Cui Xiangmei, Huang Jinghua. An empirical study on the impact of credit evaluation system and related factors on the online trading of flat price. Journal of Management, 2010, 7 (1): 50 - 56.

5. Wu W.Y., Huang P.C., Fu C. S. The influence of an online auction’s product price and e-retailer reputation on consumer’s perception, attitude, and behavioral intention. Scandi- Navian Journal of Psychology, 2011, 52 (3): 290 - 302.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Application of a Posteriori Estimates for Multifactor Ranking of Transport Companies;2024 XXVII International Conference on Soft Computing and Measurements (SCM);2024-05-22

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3