[go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2004.13463.html
   My bibliography  Save this paper

How do online consumers review negatively?

Author

Listed:
  • Menghan Sun
  • Jichang Zhao
Abstract
Negative reviews on e-commerce platforms, mainly in the form of texts, are posted by online consumers to express complaints about unsatisfactory experiences, providing a proxy of big data for sellers to consider improvements. However, the exact knowledge that lies beyond the negative reviewing still remains unknown. Aimed at a systemic understanding of how online consumers post negative reviews, using 1, 450, 000 negative reviews from JD.com, the largest B2C platform in China, the behavioral patterns from temporal, perceptional and emotional perspectives are comprehensively explored in the present study. Massive consumers behind these reviews across four sectors in the most recent 10 years are further split into five levels to reveal group discriminations at a fine resolution. Circadian rhythms of negative reviewing after making purchases were found, and the periodic intervals suggest stable habits in online consumption and that consumers tend to negatively review at the same hour of the purchase. Consumers from lower levels express more intensive negative feelings, especially on product pricing and seller attitudes, while those from upper levels demonstrate a stronger momentum of negative emotion. The value of negative reviews from higher-level consumers is thus unexpectedly highlighted because of less emotionalization and less biased narration, while the longer-lasting characteristic of these consumers' negative responses also stresses the need for more attention from sellers. Our results shed light on implementing distinguished proactive strategies in different buyer groups to help mitigate the negative impact due to negative reviews.

Suggested Citation

  • Menghan Sun & Jichang Zhao, 2020. "How do online consumers review negatively?," Papers 2004.13463, arXiv.org.
  • Handle: RePEc:arx:papers:2004.13463
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2004.13463
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Junran Wu & Ke Xu & Jichang Zhao, 2019. "Online reviews can predict long-term returns of individual stocks," Papers 1905.03189, arXiv.org.
    2. Nachiketa Sahoo & Chrysanthos Dellarocas & Shuba Srinivasan, 2018. "The Impact of Online Product Reviews on Product Returns," Information Systems Research, INFORMS, vol. 29(3), pages 723-738, September.
    3. Mochen Yang & Yuqing Ren & Gediminas Adomavicius, 2019. "Understanding User-Generated Content and Customer Engagement on Facebook Business Pages," Information Systems Research, INFORMS, vol. 30(3), pages 839-855, September.
    4. J. Guo & C. Fan & Z. Guo, 2011. "Weblog patterns and human dynamics with decreasing interest," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 81(3), pages 341-344, June.
    5. Dokyun Lee & Kartik Hosanagar & Harikesh S. Nair, 2018. "Advertising Content and Consumer Engagement on Social Media: Evidence from Facebook," Management Science, INFORMS, vol. 64(11), pages 5105-5131, November.
    6. Jonah Berger & Alan T. Sorensen & Scott J. Rasmussen, 2010. "Positive Effects of Negative Publicity: When Negative Reviews Increase Sales," Marketing Science, INFORMS, vol. 29(5), pages 815-827, 09-10.
    7. Herr, Paul M & Kardes, Frank R & Kim, John, 1991. "Effects of Word-of-Mouth and Product-Attribute Information on Persuasion: An Accessibility-Diagnosticity Perspective," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 17(4), pages 454-462, March.
    8. Anindya Ghose & Panagiotis G. Ipeirotis & Beibei Li, 2012. "Designing Ranking Systems for Hotels on Travel Search Engines by Mining User-Generated and Crowdsourced Content," Marketing Science, INFORMS, vol. 31(3), pages 493-520, May.
    9. Berinsky, Adam J. & Huber, Gregory A. & Lenz, Gabriel S., 2012. "Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk," Political Analysis, Cambridge University Press, vol. 20(3), pages 351-368, July.
    10. repec:cup:judgdm:v:5:y:2010:i:5:p:411-419 is not listed on IDEAS
    11. Marios Koufaris, 2002. "Applying the Technology Acceptance Model and Flow Theory to Online Consumer Behavior," Information Systems Research, INFORMS, vol. 13(2), pages 205-223, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Warut Khern-am-nuai & Hossein Ghasemkhani & Dandan Qiao & Karthik Kannan, 2024. "The Impact of Online Q&As on Product Sales: The Case of Amazon Answer," Information Systems Research, INFORMS, vol. 35(2), pages 747-765, June.
    2. Colmekcioglu, Nazan & Marvi, Reza & Foroudi, Pantea & Okumus, Fevzi, 2022. "Generation, susceptibility, and response regarding negativity: An in-depth analysis on negative online reviews," Journal of Business Research, Elsevier, vol. 153(C), pages 235-250.
    3. Jung Ah Han & Elea McDonnell Feit & Shuba Srinivasan, 2020. "Can negative buzz increase awareness and purchase intent?," Marketing Letters, Springer, vol. 31(1), pages 89-104, March.
    4. Kunpeng Zhang & Wendy Moe, 2021. "Measuring Brand Favorability Using Large-Scale Social Media Data," Information Systems Research, INFORMS, vol. 32(4), pages 1128-1139, December.
    5. Myoung-Jin Chae, 2021. "Driving Consumer Engagement through Diverse Calls to Action in Corporate Social Responsibility Messages on Social Media," Sustainability, MDPI, vol. 13(7), pages 1-22, March.
    6. Yang Gao & Wenjing Duan & Huaxia Rui, 2022. "Does Social Media Accelerate Product Recalls? Evidence from the Pharmaceutical Industry," Information Systems Research, INFORMS, vol. 33(3), pages 954-977, September.
    7. Nguyen, Cathy & Romaniuk, Jenni, 2013. "Factors moderating the impact of word of mouth for TV and film broadcasts," Australasian marketing journal, Elsevier, vol. 21(1), pages 25-29.
    8. Carlson, Keith & Kopalle, Praveen K. & Riddell, Allen & Rockmore, Daniel & Vana, Prasad, 2023. "Complementing human effort in online reviews: A deep learning approach to automatic content generation and review synthesis," International Journal of Research in Marketing, Elsevier, vol. 40(1), pages 54-74.
    9. Vasu Unnava & Ashwin Aravindakshan, 2021. "How does consumer engagement evolve when brands post across multiple social media?," Journal of the Academy of Marketing Science, Springer, vol. 49(5), pages 864-881, September.
    10. Heng Tang & Xiaowan Lin, 2019. "Curbing shopping cart abandonment in C2C markets — an uncertainty reduction approach," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(3), pages 533-552, September.
    11. Tata, Sai Vijay & Prashar, Sanjeev & Gupta, Sumeet, 2020. "An examination of the role of review valence and review source in varying consumption contexts on purchase decision," Journal of Retailing and Consumer Services, Elsevier, vol. 52(C).
    12. Bei Yan & Feng Mai & Chaojiang Wu & Rui Chen & Xiaolin Li, 2024. "A Computational Framework for Understanding Firm Communication During Disasters," Information Systems Research, INFORMS, vol. 35(2), pages 590-608, June.
    13. Caiwei Ma & Norman Au & Lianping Ren, 2020. "Biased minds experience improved decision-making speed and confidence on social media: a heuristic approach," Information Technology & Tourism, Springer, vol. 22(4), pages 593-624, December.
    14. Boegershausen, Johannes & Datta, Hannes & Borah, Abhishek & Stephen, Andrew, 2022. "Fields of Gold: Web Scraping and APIs for Impactful Marketing Insights," Other publications TiSEM 5f1ed70a-48c3-422c-bc10-0, Tilburg University, School of Economics and Management.
    15. T. Ravichandran & Chaoqun Deng, 2023. "Effects of Managerial Response to Negative Reviews on Future Review Valence and Complaints," Information Systems Research, INFORMS, vol. 34(1), pages 319-341, March.
    16. Plotkina, Daria & Munzel, Andreas, 2016. "Delight the experts, but never dissatisfy your customers! A multi-category study on the effects of online review source on intention to buy a new product," Journal of Retailing and Consumer Services, Elsevier, vol. 29(C), pages 1-11.
    17. Zhao, Lu & Zhang, Mingli & Ming, Yaxin & Niu, Tao & Wang, Yu, 2023. "The effect of image richness on customer engagement: Evidence from Sina Weibo," Journal of Business Research, Elsevier, vol. 154(C).
    18. Changseung Yoo & Eunae Yoo & Lu (Lucy) Yan & Alfonso Pedraza-Martinez, 2024. "Speak with One Voice? Examining Content Coordination and Social Media Engagement During Disasters," Information Systems Research, INFORMS, vol. 35(2), pages 551-569, June.
    19. Wang, Fei & Xu, Haifeng & Hou, Ronglin & Zhu, Zhen, 2023. "Designing marketing content for social commerce to drive consumer purchase behaviors: A perspective from speech act theory," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
    20. Bitty Balducci & Detelina Marinova, 2018. "Unstructured data in marketing," Journal of the Academy of Marketing Science, Springer, vol. 46(4), pages 557-590, July.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2004.13463. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.