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Misreading of consumer dissatisfaction in online product reviews: Writing style as a cause for bias

Author

Listed:
  • Michael Antioco

    (EM - EMLyon Business School)

  • Kristof Coussement

    (LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique)

Abstract

This study improves our understanding of managers' misreading of negative online reviews. Our findings are derived from a sample of 1014 written online reviews and 507 experienced marketing managers. By building on the judgment-bias literature and psychometric language-style analysis, we find several key results that can ultimately contribute to more effective information management for marketing decisions. Managers tend to better interpret negative reviews when consumers use more cognitive language markers in the form of insight and discrepancy words and more third-person pronouns (i.e., undefined social referents) in their reviews. The inverse relationship exists for the use of causality words and future tenses (i.e., behavioral intentions), as managers tend to underestimate the gravity of the situation under these conditions. Expressions of positive and negative emotions in reviews do not significantly affect managers' readings of negative reviews. Furthermore, more experienced managers and female managers are better at identifying negative reviews, and longer consumer reviews make it more difficult for managers to correctly identify negative reviews.

Suggested Citation

  • Michael Antioco & Kristof Coussement, 2018. "Misreading of consumer dissatisfaction in online product reviews: Writing style as a cause for bias," Post-Print hal-02572087, HAL.
    • Handle: RePEc:hal:journl:hal-02572087
    DOI: 10.1016/j.ijinfomgt.2017.10.009
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    Citations

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    Cited by:

    1. Steven Debaere & Floris Devriendt & Johanna Brunneder & Wouter Verbeke & Tom de Ruyck & Kristof Coussement, 2019. "Reducing inferior member community participation using uplift modeling: Evidence from a field experiment," Post-Print hal-02990787, HAL.
    2. Ludovik Coba & Laurens Rook & Markus Zanker, 2020. "Choosing between hotels: impact of bimodal rating summary statistics and maximizing behavioral tendency," Information Technology & Tourism, Springer, vol. 22(1), pages 167-186, March.
    3. Xian Wang & Huixian Li & Qingyi Wang & Alison Noble, 2023. "Consumers’ Concerns Regarding Product Quality: Evidence From Chinese Online Reviews," SAGE Open, , vol. 13(1), pages 21582440231, March.
    4. Kim, Phillip H. & Kotha, Reddi & Fourné, Sebastian P.L. & Coussement, Kristof, 2019. "Taking leaps of faith: Evaluation criteria and resource commitments for early-stage inventions," Research Policy, Elsevier, vol. 48(6), pages 1429-1444.
    5. Ahani, Ali & Nilashi, Mehrbakhsh & Yadegaridehkordi, Elaheh & Sanzogni, Louis & Tarik, A. Rashid & Knox, Kathy & Samad, Sarminah & Ibrahim, Othman, 2019. "Revealing customers’ satisfaction and preferences through online review analysis: The case of Canary Islands hotels," Journal of Retailing and Consumer Services, Elsevier, vol. 51(C), pages 331-343.

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