JOURNAL ARTICLE

Investigating binge‐watching and its effect on paid subscription: A mixed‐method study based on SOR theory.

  • Published In: Journal of Consumer Behaviour, 2025, v. 24, n. 1. P. 20 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Song, Lianlian; Yao, Shanji; Liu, Lili; Tso, Geoffrey 3 of 3

Abstract

Video‐on‐demand platforms encourage binge‐watching (BW) to stimulate consumers' paid subscription. Despite decades of research, prior studies have yet to reach a consensus on the definition of BW, which results in inconsistent findings regarding its effect on paid subscription behavior. Drawing on stimuli‐organism‐response theory and parasocial interaction studies, we develop a conceptual model to explore the causal mechanism that links BW, the consumer organism (attractiveness, identification, involvement, and parasocial interaction), and responses (impulsive paid subscription). We also investigate how the boundary condition of BW (number of episodes watched) affects this causal mechanism. We conducted an online survey and two quasi‐field experiments to collect data and verify the hypotheses. Our findings confirm that, compared with non‐BW, BW offers enhanced attractiveness, identification, involvement, and parasocial interaction, which results in more impulsive paid subscription behavior. Moreover, it is valid to define BW as watching at least three episodes of a program, which reveals significant differences in viewers' impulsive paid subscription behavior. Implications for future BW research and marketing strategies for video‐on‐demand platforms are discussed. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Consumer Behaviour. 2025/01, Vol. 24, Issue 1, p20
  • Document Type:Article
  • Subject Area:Communication and Mass Media
  • Publication Date:2025
  • ISSN:1472-0817
  • DOI:10.1002/cb.2402
  • Accession Number:183926260
  • Copyright Statement:Copyright of Journal of Consumer Behaviour is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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