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Exploring Determinants of Attraction and Helpfulness of Online Product Review: A Consumer Behaviour Perspective

Author

Listed:
  • Xu Chen
  • Jie Sheng
  • Xiaojun Wang
  • Jiangshan Deng

Abstract

To assist filtering and sorting massive review messages, this paper attempts to examine the determinants of review attraction and helpfulness. Our analysis divides consumers’ reading process into “notice stage” and “comprehend stage” and considers the impact of “explicit information” and “implicit information” of review attraction and review helpfulness. 633 online product reviews were collected from Amazon China. A mixed-method approach is employed to test the conceptual model proposed for examining the influencing factors of review attraction and helpfulness. The empirical results show that reviews with negative extremity, more words, and higher reviewer rank easily gain more attraction and reviews with negative extremity, higher reviewer rank, mixed subjective property, and mixed sentiment seem to be more helpful. The research findings provide some important insights, which will help online businesses to encourage consumers to write good quality reviews and take more active actions to maximise the value of online reviews.

Suggested Citation

  • Xu Chen & Jie Sheng & Xiaojun Wang & Jiangshan Deng, 2016. "Exploring Determinants of Attraction and Helpfulness of Online Product Review: A Consumer Behaviour Perspective," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-19, November.
    • Handle: RePEc:hin:jnddns:9354519
    DOI: 10.1155/2016/9354519
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    Cited by:

    1. Safiyeh Tayebi & Seyed Ali Alavi & Saeed Esfandi & Leyla Meshkani & Aliakbar Shamsipour, 2023. "Evaluation of Land Use Efficiency in Tehran’s Expansion between 1986 and 2021: Developing an Assessment Framework Using DEMATEL and Interpretive Structural Modeling Methods," Sustainability, MDPI, vol. 15(4), pages 1-26, February.

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