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Aggregate bandwagon effect on online videos' viewership: Value uncertainty, popularity cues, and heuristics

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  • W. Wayne Fu
  • Clarice C. Sim

Abstract

This study examines the aggregate bandwagon effect of popularity cues on the viewership of online user‐generated videos. Cognitive and behavioral theories of information processing suggest that Web users, overwhelmed by information and quality uncertainty, will gravitate toward the popular choices made by earlier decision makers, which appear via indicators such as hit counts to forge quality impressions. Building on the theories, we hypothesize that how much viewer exposure videos will attract at any future time depends on their viewership accumulated individually; furthermore, this viewership cascade is moderated by pictorial and verbal preview because such information reduces quality uncertainty for content shoppers. Our longitudinal model tests these hypotheses using an extensive real‐life dataset on video clips retrieved from a video‐sharing site.

Suggested Citation

  • W. Wayne Fu & Clarice C. Sim, 2011. "Aggregate bandwagon effect on online videos' viewership: Value uncertainty, popularity cues, and heuristics," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(12), pages 2382-2395, December.
    • Handle: RePEc:bla:jamist:v:62:y:2011:i:12:p:2382-2395
    DOI: 10.1002/asi.21641
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    Cited by:

    1. Jingjing Zhang & Nan Jiang & Jason James Turner & Saeed Pahlevan Sharif, 2021. "The Impact of Scarcity of Medical Protective Products on Chinese Consumers’ Impulsive Purchasing during the COVID-19 Epidemic in China," Sustainability, MDPI, vol. 13(17), pages 1-14, August.
    2. Melby Karina Zuniga Huertas & Tarcisio Duarte Coelho, 2019. "The Interaction Effect of Type of Message X YouTuber’s Media Metrics on Customers’ Responses and the Moderation of Conformity Intention," Future Internet, MDPI, vol. 11(6), pages 1-17, June.
    3. Sang-Hyeak Yoon & Hee-Woong Kim, 2019. "What content and context factors lead to selection of a video clip? The heuristic route perspective," Electronic Commerce Research, Springer, vol. 19(3), pages 603-627, September.
    4. Chan, Ho Fai & Bodiuzzman, Sohel Md & Torgler, Benno, 2020. "The power of social cues in the battle for attention: Evidence from an online platform for scholarly commentary," Journal of Informetrics, Elsevier, vol. 14(4).
    5. Ali, Mazhar & Amir, Dr.Huma & Shamsi, Dr.Aamir, 2021. "Consumer Herding Behavior in Online Buying: A Literature Review," MPRA Paper 107435, University Library of Munich, Germany.
    6. KyuJin Shim & Klive (Soo-Kwang) Oh, 2019. "Does Fear of Isolation Disappear Online? Attention-Seeking Motivators in Online Political Engagement," Media and Communication, Cogitatio Press, vol. 7(1), pages 128-138.
    7. Parsons, Andrew G. & Ballantine, Paul W. & Ali, Ashleigh & Grey, Hannah, 2014. "Deal is on! Why people buy from daily deal websites," Journal of Retailing and Consumer Services, Elsevier, vol. 21(1), pages 37-42.
    8. Jordi McKenzie, 2023. "The economics of movies (revisited): A survey of recent literature," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 480-525, April.
    9. Xiangyu Wang & Min Zhang & Weiguo Fan & Kang Zhao, 2022. "Understanding the spread of COVID‐19 misinformation on social media: The effects of topics and a political leader's nudge," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(5), pages 726-737, May.
    10. Haris Krijestorac & Rajiv Garg & Vijay Mahajan, 2020. "Cross-Platform Spillover Effects in Consumption of Viral Content: A Quasi-Experimental Analysis Using Synthetic Controls," Information Systems Research, INFORMS, vol. 31(2), pages 449-472, June.

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