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The influx of skeptics: an investigation of the diffusion cycle effect on online review

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  • Rae Yule Kim

    (Rutgers University, Rutgers Business School)

Abstract

Can online review ratings be lower for more popular products? Ironically, it might be inevitable. We utilize diffusion theory and predict that the influx of skeptic users into online reviews might be prevalent as products gain in popularity. We examined 6776 apps with more than one hundred installs and review counts on Google Playstore about the trends in their user ratings by the number of installs. We visualize how the diffusion cycle might affect this phenomenon and examine anomaly in the trend of review ratings by the number of installs to detect the significant influx of skeptic users. Interestingly, most of the apps in the early diffusion stage received significantly high ratings, and clustering results indicated a significant skeptics loop in the review ratings past the early diffusion stage. We suggest that businesses can keep skeptics satisfied by connecting experiences and creating newness.

Suggested Citation

  • Rae Yule Kim, 2020. "The influx of skeptics: an investigation of the diffusion cycle effect on online review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 30(4), pages 821-835, December.
    • Handle: RePEc:spr:elmark:v:30:y:2020:i:4:d:10.1007_s12525-020-00417-4
    DOI: 10.1007/s12525-020-00417-4
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    1. King, Robert Allen & Racherla, Pradeep & Bush, Victoria D., 2014. "What We Know and Don't Know About Online Word-of-Mouth: A Review and Synthesis of the Literature," Journal of Interactive Marketing, Elsevier, vol. 28(3), pages 167-183.
    2. Berman, Barry, 2016. "Referral marketing: Harnessing the power of your customers," Business Horizons, Elsevier, vol. 59(1), pages 19-28.
    3. Shen, George Chung-Chi, 2015. "Users' adoption of mobile applications: Product type and message framing's moderating effect," Journal of Business Research, Elsevier, vol. 68(11), pages 2317-2321.
    4. Hu, Hai-hua & Lin, Jun & Qian, Yanjun & Sun, Jian, 2018. "Strategies for new product diffusion: Whom and how to target?," Journal of Business Research, Elsevier, vol. 83(C), pages 111-119.
    5. Mangold, W. Glynn & Smith, Katherine Taken, 2012. "Selling to Millennials with online reviews," Business Horizons, Elsevier, vol. 55(2), pages 141-153.
    6. Avlonitis, George J. & Salavou, Helen E., 2007. "Entrepreneurial orientation of SMEs, product innovativeness, and performance," Journal of Business Research, Elsevier, vol. 60(5), pages 566-575, May.
    7. Yilmaz, Cengiz & Varnali, Kaan & Kasnakoglu, Berna Tari, 2016. "How do firms benefit from customer complaints?," Journal of Business Research, Elsevier, vol. 69(2), pages 944-955.
    8. Bambauer-Sachse, Silke & Mangold, Sabrina, 2011. "Brand equity dilution through negative online word-of-mouth communication," Journal of Retailing and Consumer Services, Elsevier, vol. 18(1), pages 38-45.
    9. Yi, Jisu & Lee, Youseok & Kim, Sang-Hoon, 2019. "Determinants of growth and decline in mobile game diffusion," Journal of Business Research, Elsevier, vol. 99(C), pages 363-372.
    10. Christophe Van den Bulte & Yogesh V. Joshi, 2007. "New Product Diffusion with Influentials and Imitators," Marketing Science, INFORMS, vol. 26(3), pages 400-421, 05-06.
    11. Yany Grégoire & Fateme Ghadami & Sandra Laporte & Sylvain Sénécal & Denis Larocque, 2018. "How can firms stop customer revenge? The effects of direct and indirect revenge on post-complaint responses," Journal of the Academy of Marketing Science, Springer, vol. 46(6), pages 1052-1071, November.
    12. Rogers, Everett M, 1976. "New Product Adoption and Diffusion," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 2(4), pages 290-301, March.
    13. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    14. Petrescu, Maria & O’Leary, Kathleen & Goldring, Deborah & Ben Mrad, Selima, 2018. "Incentivized reviews: Promising the moon for a few stars," Journal of Retailing and Consumer Services, Elsevier, vol. 41(C), pages 288-295.
    15. Pradeep K. Chintagunta & Shyam Gopinath & Sriram Venkataraman, 2010. "The Effects of Online User Reviews on Movie Box Office Performance: Accounting for Sequential Rollout and Aggregation Across Local Markets," Marketing Science, INFORMS, vol. 29(5), pages 944-957, 09-10.
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    Cited by:

    1. Emmanuel H. Yindi & Immaculate Maumoh & Prisillah L. Mahavile, 2021. "Exploring the role of Awareness, Government Policy, and Infrastructure in adapting B2C E-Commerce to East African Countries," Papers 2102.11729, arXiv.org.
    2. Prashanth Ravula, 2023. "Impact of delivery performance on online review ratings: the role of temporal distance of ratings," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(2), pages 149-159, June.

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    More about this item

    Keywords

    Online review; Negative review; Mobile app adoption; Product adoption; Innovation diffusion; Mobile app market;
    All these keywords.

    JEL classification:

    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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