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A Meta-Analysis on the Determinants of Online Product Reviews with Moderating Effect of Product Type

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  • Kavita Rawat
  • Sunita Kumar

Abstract

The technological advances in digital space have provided a renewed impetus for business to expand their footprint across digital modes. The growth of the internet and the ease of its access to the masses has encouraged many businesses to go online. Online e-commerce platforms make it easy to search, locate and place orders. Technology-assisted supply chains and fast delivery mechanisms ensure that users don't have to go elsewhere to fulfill their needs. To earn loyalty and customer satisfaction, e-commerce platforms have evolved into a sophisticated recommender system. It has evolved from just an informational source to a participative mode where users can share their experiences about their purchases. Customer values other user experiences more than the information provided by the seller. The presence of many conflicting and contradicting reviews can make the task of making rational decisions difficult for many users. Many studies were performed to understand what constitutes a review helpful and came up with different or mixed outcomes. The present study reviews the factors that influence online customer reviews helpful. Meta-analysis was performed to reconcile the mixed findings of different factors of online review helpfulness. The meta-analysis found that with the moderating effect of product type, factors like review length, readability, rating, reputation, and expertise positively correlate with helpfulness. Further, the customer finds moderate reviews more helpful in terms of polarity. Meta-analysis has a mix of findings for the selected data points in the study. The mixed findings include product type (search, experience, or other) and helpfulness measurement criteria.

Suggested Citation

  • Kavita Rawat & Sunita Kumar, 2022. "A Meta-Analysis on the Determinants of Online Product Reviews with Moderating Effect of Product Type," Academic Journal of Interdisciplinary Studies, Richtmann Publishing Ltd, vol. 11, November.
    • Handle: RePEc:bjz:ajisjr:2331
    DOI: https://doi.org/10.36941/ajis-2022-0170
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    References listed on IDEAS

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    1. Alton Y.K. Chua & Snehasish Banerjee, 2015. "Understanding review helpfulness as a function of reviewer reputation, review rating, and review depth," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(2), pages 354-362, February.
    2. Xinxin Li & Lorin M. Hitt, 2008. "Self-Selection and Information Role of Online Product Reviews," Information Systems Research, INFORMS, vol. 19(4), pages 456-474, December.
    3. Elvira Ismagilova & Emma L. Slade & Nripendra P. Rana & Yogesh K. Dwivedi, 2020. "The Effect of Electronic Word of Mouth Communications on Intention to Buy: A Meta-Analysis," Information Systems Frontiers, Springer, vol. 22(5), pages 1203-1226, October.
    4. Simon Trang & Benedikt Brendel, 2019. "A Meta-Analysis of Deterrence Theory in Information Security Policy Compliance Research," Information Systems Frontiers, Springer, vol. 21(6), pages 1265-1284, December.
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