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A picture is worth a thousand words: how images influence information quality and information load in online reviews

Author

Listed:
  • Robert Zinko

    (Texas A&M University-Central Texas)

  • Paul Stolk

    (University Dr)

  • Zhan Furner

    (East Carolina University)

  • Brad Almond

    (Texas A&M University-Central Texas)

Abstract

Decision science researchers have studied the influence of information overload extensively. Current electronic word of mouth (eWOM) research suggests that too much or too little information in a review can lead to decreased trust and purchase intent. This study adds to that paradigm by exploring the effects of images on uncertainty reduction in eWOM. More specifically, this study analyzes how images may influence trust and purchase intent based on an online review when there is too little or too much textual information. Findings indicate that when there is too little textual information, adding images increases trust and purchase intention, as information load increases. Likewise, when there is too much textual information, research suggests that consumers tend to skip over parts of the text. As such, images are still valuable, as they offer information that might have been missed in the text. These results suggest that when an improper amount of text is provided in a review, images may moderate the potential negative effects of that text length on trust and purchase intent.

Suggested Citation

  • Robert Zinko & Paul Stolk & Zhan Furner & Brad Almond, 2020. "A picture is worth a thousand words: how images influence information quality and information load in online reviews," Electronic Markets, Springer;IIM University of St. Gallen, vol. 30(4), pages 775-789, December.
  • Handle: RePEc:spr:elmark:v:30:y:2020:i:4:d:10.1007_s12525-019-00345-y
    DOI: 10.1007/s12525-019-00345-y
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    References listed on IDEAS

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    Cited by:

    1. Andreas J. Steur & Fabian Fritzsche & Mischa Seiter, 2022. "It’s all about the text: An experimental investigation of inconsistent reviews on restaurant booking platforms," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1187-1220, September.
    2. 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.
    3. Hui-Ju Wang, 2022. "Understanding reviewer characteristics in online reviews via network structural positions," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1311-1325, September.
    4. Yue Guan & Yong Tan & Qiang Wei & Guoqing Chen, 2023. "When Images Backfire: The Effect of Customer-Generated Images on Product Rating Dynamics," Information Systems Research, INFORMS, vol. 34(4), pages 1641-1663, December.
    5. Luis Filipe Lages & Nuno Catarino & Emanuel Gomes & Peter Toh & Carlos Reis-Marques & Mario Mohr & Sebastian Max Borde & Omid Asgari & Ronnie Figueiredo & Nuno Grosso & David Perez & Ana Ponte & Sílvi, 2023. "Solutions for the commercialization challenges of Horizon Europe and earth observation consortia: co-creation, innovation, decision-making, tech-transfer, and sustainability actions," Electronic Commerce Research, Springer, vol. 23(3), pages 1621-1663, September.
    6. Tim Kollmer & Andreas Eckhardt & Victoria Reibenspiess, 2022. "Explaining consumer suspicion: insights of a vignette study on online product reviews," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1221-1238, September.
    7. Benedikt M. Brand & Cristopher Siegfried Kopplin & Theresa Maria Rausch, 2022. "Cultural differences in processing online customer reviews: holistic versus analytic thinkers," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1039-1060, September.

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    More about this item

    Keywords

    Electronic word of mouth; Information overload; Information quality; Images;
    All these keywords.

    JEL classification:

    • M3 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising

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