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Online Review Updating: Prevalence and Implications for Platforms and Businesses

Author

Listed:
  • Martina Pocchiari
  • Verena Schoenmueller
  • Yaniv Dover

Abstract

This study documents the existence and prevalence of the “review updating” phenomenon, where consumers change the ratings and content of their existing reviews, and examines its implications for platforms and businesses. Using both primary and secondary data, a dataset comprising 3 million reviews of 50,000 companies from a large global online review platform, text analysis methods, and staggered adoption design models, the research shows that consumers update between 5% and 30% of their existing reviews across various platforms. Consumers are motivated by the desire to provide more accurate and updated information, and are especially likely to update existing reviews with extreme and/or negative ratings. The updates tend to mitigate the extremity of the review ratings and content: 77.2% of extremely negative ratings increase by an average of 1.83 stars post-update, and the content of updated reviews becomes less emotionally extreme, overall more net positive, and richer in cognitive content. Consumers also rate the same reviews as more helpful post-update. Importantly, the research shows that low-cost, unincentivized platform solicitations can directly increase the likelihood of review updating, suggesting a novel managerial tool to mitigate the undesirable impacts of extreme and negative reviews. The findings contribute to the literature on online reviews by challenging the implicit assumption that reviews remain static in content and ratings post-creation and propose that review updates can benefit consumers, businesses, and platforms.

Suggested Citation

  • Martina Pocchiari & Verena Schoenmueller & Yaniv Dover, 2024. "Online Review Updating: Prevalence and Implications for Platforms and Businesses," CESifo Working Paper Series 11513, CESifo.
  • Handle: RePEc:ces:ceswps:_11513
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    More about this item

    Keywords

    online reviews; online review updating; online review dynamics; online review extremity; user-generated content; e-word of mouth;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • F32 - International Economics - - International Finance - - - Current Account Adjustment; Short-term Capital Movements
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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