Information disclosing strategy and additional online customer reviews

被引：0
作者：
Dong, Shaozeng [1 ]
Yang, Liu [2 ]
Wu, Hsin-Te [3 ]
Shi, Baozhen [2 ]
Ng, Chi. To. [4 ]
Wang, Yifei [5 ]
机构：
[1] Jiangsu Ocean Univ, Sch Business, Lianyungang, Peoples R China
[2] Univ Int Business & Econ, Business Sch, 10 Huixin East St, Beijing 100029, Peoples R China
[3] Natl Taitung Univ, Dept Comp Sci & Informat Engn, Taitung, Taiwan
[4] Hong Kong Polytech Univ, Logist Res Ctr, Dept Logist & Maritime Studies, Hong Kong, Peoples R China
[5] Univ Sydney, Sch Arts & Social Sci, Sydney, NSW, Australia
来源：
ENTERPRISE INFORMATION SYSTEMS | 2024年 / 18卷 / 12期
基金：
中国国家自然科学基金;
关键词：
Additional online reviews; online customer reviews; product information asymmetry; big data analytics; AI-driven application; CONSUMER PERCEPTIONS; HELPFULNESS; DETERMINANTS; ENGAGEMENT;
D O I：
10.1080/17517575.2024.2420693
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Product information asymmetry exists between firms and online customers. Online customer reviews offer product quality information and reduce information asymmetry. Many customers review products online upon receipt and again after use. Initial and additional reviews can be consistent or conflicting, which affects other customers' perceived product value. Firms use different strategies for disclosing product featured quality information, such as exaggerating or depreciating product quality. Different strategies can lead to different customer perceptions, which can affect additional reviews. In addition, even with the same strategy, differences in the degree of information quality can affect the perceived value of customers.
引用
收藏
页数：21
相关论文
共 51 条
  • [1] A Tangled Web: Should Online Review Portals Display Fraudulent Reviews?
    Ananthakrishnan, Uttara M.
    Li, Beibei
    Smith, Michael D.
    [J]. INFORMATION SYSTEMS RESEARCH, 2020, 31 (03) : 950 - 971
  • [2] [Anonymous], 2023, Consumer News and Business Channel
  • [3] Helpfulness of Online Consumer Reviews: Readers' Objectives and Review Cues
    Baek, Hyunmi
    Ahn, JoongHo
    Choi, Youngseok
    [J]. INTERNATIONAL JOURNAL OF ELECTRONIC COMMERCE, 2012, 17 (02) : 99 - 126
  • [4] Machine Talk: How Verbal Embodiment in Conversational AI Shapes Consumer-Brand Relationships
    Bergner, Anouk S.
    Hildebrand, Christian
    Haubl, Gerald
    [J]. JOURNAL OF CONSUMER RESEARCH, 2023, 50 (04) : 742 - 764
  • [5] Stimulating Online Reviews by Combining Financial Incentives and Social Norms
    Burtch, Gordon
    Hong, Yili
    Bapna, Ravi
    Griskevicius, Vladas
    [J]. MANAGEMENT SCIENCE, 2018, 64 (05) : 2065 - 2082
  • [6] Exploring determinants of voting for the "helpfulness" of online user reviews: A text mining approach
    Cao, Qing
    Duan, Wenjing
    Gan, Qiwei
    [J]. DECISION SUPPORT SYSTEMS, 2011, 50 (02) : 511 - 521
  • [7] The Sequence Effect of Supplementary Online Comments in Book Sales
    Chen, Hejie
    Yan, Qiang
    Xie, Mengjiao
    Zhang, Duo
    Chen, Yepeng
    [J]. IEEE ACCESS, 2019, 7 : 155650 - 155658
  • [8] How social influence through information adoption from online review sites affects collective decision making
    Cho, Vincent
    Chan, Desmond
    [J]. ENTERPRISE INFORMATION SYSTEMS, 2021, 15 (10) : 1562 - 1586
  • [9] "When Is Short, Sweet?" Selection Uncertainty and Online Review Presentations
    Church, E. Mitchell
    Iyer, Lakshmi
    [J]. JOURNAL OF COMPUTER INFORMATION SYSTEMS, 2017, 57 (02) : 179 - 189
  • [10] CNNIC, 2024, The 53rd statistical report on Chinas internet development
123456