JOURNAL ARTICLE

Been there, streaming that: Media substitution, brand equity, and moviegoer attitudes towards streaming blockbuster films.

  • Published In: Convergence: The Journal of Research into New Media Technologies, 2025, v. 31, n. 5. P. 1591 1 of 3

  • Database: Communication Source 2 of 3

  • Authored By: DeFelice, Chris 3 of 3

Abstract

This study examines how major film studios’ decision to release blockbuster movies on streaming services during the COVID-19 pandemic influenced moviegoers’ perceptions of the theatrical experience. Using qualitative textual analysis of Twitter/X conversations, the research applies media substitution theory to explore how brand equity and social word-of-mouth (sWOM) shaped audience attitudes toward streaming as a substitute for traditional moviegoing. Findings reveal that while initial excitement for streaming blockbusters evolved into an expectation for at-home viewing, many moviegoers associate streaming releases with lower quality and reduced brand value, impacting franchise prestige. Additionally, sWOM remains a critical factor in deciding not only whether to watch a film but also where to watch it, with some consumers using spoilers as heuristics for these decisions. The study highlights ongoing challenges for studios in balancing theatrical exclusivity and streaming distribution to maintain brand equity and audience engagement post-pandemic.

Additional Information

  • Source:Convergence: The Journal of Research into New Media Technologies. 2025/10, Vol. 31, Issue 5, p1591
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2025
  • ISSN:1354-8565
  • DOI:10.1177/13548565251331476
  • Accession Number:188761117
  • Copyright Statement:Copyright of Convergence: The Journal of Research into New Media Technologies is the property of Sage Publications Inc. 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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