IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v187y2025ics0148296324005721.html
   My bibliography  Save this article

Content dissimilarity and online review helpfulness: Contextual insights

Author

Listed:
  • Wang, Shan
  • Karmakar, Shubhashis
  • Wang, Fang
  • Pei, Yanli

Abstract

As consumers navigate through online product reviews, they read and assess individual reviews within a broader context of product information, including product descriptions and preceding reviews. This research incorporates this information context to better understand online review helpfulness. Specifically, it studies the influence of content dissimilarity in online reviews, including topic and lexical dissimilarities compared to product descriptions and preceding reviews, respectively, on their perceived helpfulness to potential customers. An empirical analysis of approximately 1.6 million Amazon reviews reveals that readers prefer online product reviews that align with topics but differ in lexicon from product descriptions and preceding reviews. Moreover, the topic and lexical dissimilarities interact in affecting review helpfulness, and the impact of content dissimilarity varies across reviews for products of differing price levels. This research underscores the significance of assessing information utility within its contextual framework and highlights the importance of evaluating content at both the topical and lexical levels. It offers fresh insights for both scholars and practitioners in understanding and curating beneficial online information.

Suggested Citation

  • Wang, Shan & Karmakar, Shubhashis & Wang, Fang & Pei, Yanli, 2025. "Content dissimilarity and online review helpfulness: Contextual insights," Journal of Business Research, Elsevier, vol. 187(C).
    • Handle: RePEc:eee:jbrese:v:187:y:2025:i:c:s0148296324005721
    DOI: 10.1016/j.jbusres.2024.115068
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296324005721
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbusres.2024.115068?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:eee:jbrese:v:187:y:2025:i:c:s0148296324005721. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    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.