IDEAS home Printed from https://ideas.repec.org/a/apa/ijbaas/2019p312-320.html
   My bibliography  Save this article

Window Dressing Effects of Online Information: A Content-Analysis of the Post-Purchase Reviews on Amazon.com

Author

Listed:
  • Wan Seop Jung

    (Farmingdale State College, New York, NY)

  • Eun Soo Rhee

    (Towson University, Towson, MD)

Abstract

This study examined the surface characteristics of helpful customer reviews posted on Amazon.com to understand the nature of electronic Word-of-Mouth (eWOM). To investigate the surface characteristics of the helpfulness of customer reviews, and whether the helpfulness and attention-grabbing power of the customer reviews are associated with the surface characteristics, a content analysis of Amazon.com customer reviews was conducted. We found that consumers considered a review helpful if it offered visually prominent cues that made it more convenient to determine the usefulness and helpfulness of the review. The results of this study further demonstrate the mediational effect of attention-grabbing power on the review helpfulness. Our findings suggest that not only what is communicated but also how the information is communicated is crucial to improve credibility and attention-grabbing power in the online environment.

Suggested Citation

  • Wan Seop Jung & Eun Soo Rhee, 2019. "Window Dressing Effects of Online Information: A Content-Analysis of the Post-Purchase Reviews on Amazon.com," International Journal of Business and Administrative Studies, Professor Dr. Bahaudin G. Mujtaba, vol. 5(6), pages 312-320.
  • Handle: RePEc:apa:ijbaas:2019:p:312-320
    DOI: 10.20469/ijbas.5.10001-6
    as

    Download full text from publisher

    File URL: https://kkgpublications.com/business-v5-i6-article-1/
    Download Restriction: no

    File URL: https://kkgpublications.com/wp-content/uploads/2019/12/ijbas.5.10001-6.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.20469/ijbas.5.10001-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Chrysanthos Dellarocas, 2003. "The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms," Management Science, INFORMS, vol. 49(10), pages 1407-1424, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gary E. Bolton & David J. Kusterer & Johannes Mans, 2015. "Inflated reputations: Uncertainty, leniency & moral wiggle room in trader feedback systems," Cologne Graduate School Working Paper Series 06-04, Cologne Graduate School in Management, Economics and Social Sciences, revised 29 Jul 2016.
    2. Xu Guan & Yulan Wang & Zelong Yi & Ying‐Ju Chen, 2020. "Inducing Consumer Online Reviews Via Disclosure," Production and Operations Management, Production and Operations Management Society, vol. 29(8), pages 1956-1971, August.
    3. Fang, Mingyue & Nie, Huihua & Shen, Xinyi, 2023. "Can enterprise digitization improve ESG performance?," Economic Modelling, Elsevier, vol. 118(C).
    4. Yucheng Zhang & Zhiling Wang & Lin Xiao & Lijun Wang & Pei Huang, 2023. "Discovering the evolution of online reviews: A bibliometric review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-22, December.
    5. Hui, Xiang & Klein, Tobias & Stahl, Konrad, 2022. "Learning from Online Ratings," CEPR Discussion Papers 17006, C.E.P.R. Discussion Papers.
    6. Edgardo Arturo Ayala Gaytán, 2009. "Social network externalities and price dispersion in online markets," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 1-28, November.
    7. Chrysanthos Dellarocas & Charles A. Wood, 2008. "The Sound of Silence in Online Feedback: Estimating Trading Risks in the Presence of Reporting Bias," Management Science, INFORMS, vol. 54(3), pages 460-476, March.
    8. Ravi Bapna & Chrysanthos Dellarocas & Sarah Rice, 2010. "Vertically Differentiated Simultaneous Vickrey Auctions: Theory and Experimental Evidence," Management Science, INFORMS, vol. 56(7), pages 1074-1092, July.
    9. Liuan Wang & Lu (Lucy) Yan & Tongxin Zhou & Xitong Guo & Gregory R. Heim, 2020. "Understanding Physicians’ Online-Offline Behavior Dynamics: An Empirical Study," Information Systems Research, INFORMS, vol. 31(2), pages 537-555, June.
    10. Fan, Zhi-Ping & Sun, Minghe, 2015. "Behavior-aware user response modeling in social media: Learning from diverse heterogeneous dataAuthor-Name: Chen, Zhen-Yu," European Journal of Operational Research, Elsevier, vol. 241(2), pages 422-434.
    11. Jifeng Luo & Ying Rong & Huan Zheng, 2020. "Impacts of logistics information on sales: Evidence from Alibaba," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(8), pages 646-669, December.
    12. Tobias Gesche, 2022. "Reference‐price shifts and customer antagonism: Evidence from reviews for online auctions," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 31(3), pages 558-578, August.
    13. Delina, Radoslav & Vajda, Viliam & Bednár, Peter, 2007. "Trusted operational scenarios - Trust building mechanisms and strategies for electronic marketplaces," MPRA Paper 20243, University Library of Munich, Germany.
    14. Nan Yang & Renyu Zhang, 2022. "Dynamic pricing and inventory management in the presence of online reviews," Production and Operations Management, Production and Operations Management Society, vol. 31(8), pages 3180-3197, August.
    15. Massimo G. Colombo & Chiara Franzoni & Cristina Rossi–Lamastra, 2015. "Internal Social Capital and the Attraction of Early Contributions in Crowdfunding," Entrepreneurship Theory and Practice, , vol. 39(1), pages 75-100, January.
    16. He, Wu & Zha, Shenghua & Li, Ling, 2013. "Social media competitive analysis and text mining: A case study in the pizza industry," International Journal of Information Management, Elsevier, vol. 33(3), pages 464-472.
    17. Gary E. Bolton & Elena Katok & Axel Ockenfels, 2004. "How Effective Are Electronic Reputation Mechanisms? An Experimental Investigation," Management Science, INFORMS, vol. 50(11), pages 1587-1602, November.
    18. Rajiv Garg & Rahul Telang, 2018. "To Be or Not to Be Linked: Online Social Networks and Job Search by Unemployed Workforce," Management Science, INFORMS, vol. 64(8), pages 3926-3941, August.
    19. Kenju Kamei & Louis Putterman, 2018. "Reputation Transmission Without Benefit To The Reporter: A Behavioral Underpinning Of Markets In Experimental Focus," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 158-172, January.
    20. S. Cicognani & P. Figini & M. Magnani, 2016. "Social Influence Bias in Online Ratings: A Field Experiment," Working Papers wp1060, Dipartimento Scienze Economiche, Universita' di Bologna.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:apa:ijbaas:2019:p:312-320. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Professor Dr. Bahaudin G. Mujtaba (email available below). General contact details of provider: https://kkgpublications.com/business/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.