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The Recent versus The Out-Dated: An Experimental Examination of the Time-Variant Effects of Online Consumer Reviews

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  • Jin, Liyin
  • Hu, Bingyan
  • He, Yanqun

Abstract

Conventional wisdom suggests that the most recent online reviews may have a greater impact than out-dated online reviews on consumers’ purchase decisions because of their up-to-date nature. However, building on the theory of temporal distance and construal fit, this study proposes a new perspective, suggesting that the influence of online reviews posted at different times is a function of the timeframe for the consumers’ intended purchase. Four experiments demonstrate that although recent online reviews are more influential in shifting consumer preferences towards near-future consumption decisions, the relative influence of out-dated online reviews in shifting consumer preferences increases when consumers are making distant-future consumption decisions. This effect occurs because of a construal fit between the construal level of the online reviews posted at different times and that of the timeframe of consumers’ purchase decisions. The recent reviews are represented at a relatively lower construal level, with the low-level construal matching the timeframe of the near-future consumption decision. Out-dated reviews, however, are represented at a relatively higher construal level and match the timeframe of the distant-future consumption decision. This construal fit, in turn, enhances consumer engagement and consequently exerts a greater influence on consumer preferences.

Suggested Citation

  • Jin, Liyin & Hu, Bingyan & He, Yanqun, 2014. "The Recent versus The Out-Dated: An Experimental Examination of the Time-Variant Effects of Online Consumer Reviews," Journal of Retailing, Elsevier, vol. 90(4), pages 552-566.
    • Handle: RePEc:eee:jouret:v:90:y:2014:i:4:p:552-566
    DOI: 10.1016/j.jretai.2014.05.002
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    7. Janina Seutter & Kristin Kutzner & Maren Stadtländer & Dennis Kundisch & Ralf Knackstedt, 2023. "“Sorry, too much information”—Designing online review systems that support information search and processing," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-19, December.
    8. Dominik Gutt & Jürgen Neumann & Steffen Zimmermann & Dennis Kundisch & Jianqing Chen, 2018. "Design of Review Systems - A Strategic Instrument to shape Online Review Behavior and Economic Outcomes," Working Papers Dissertations 42, Paderborn University, Faculty of Business Administration and Economics.
    9. Raoofpanah, Iman & Zamudio, César & Groening, Christopher, 2023. "Review reader segmentation based on the heterogeneous impacts of review and reviewer attributes on review helpfulness: A study involving ZIP code data," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
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