 From visuals to value: leveraging generative AI to explore the economic implications of movie posterYoungjun Kim, Hye-Jin Kim and Keeyeon Ki-cheon Park Journal of Business Research, 2025, vol. 198, issue C Abstract: This study introduces a novel exploration into the impact of visual elements on consumer behavior in the film industry, utilizing generative AI. By employing expectancy violations theory, this study examines how the mood and tone suggested by movie posters—a key visual advertising tool—contrast with the actual content of the films, revealing a significant influence on consumer decisions. Through feature extraction from movie posters using generative AI and regression model analysis, this study demonstrates that deviations from audience expectations, as suggested by movie posters, positively affect box office performance. However, this impact varies depending on whether the movie is produced by major or non-major studios, with major studio productions benefiting more from mood and tone congruence. This study extends existing literature by highlighting the role of visual cues in movie posters and offers practical insights for movie marketers using expectancy violations to enhance audience engagement and box office performance. Keywords: Movie poster; Mood; Generative artificial intelligence; Film industry; Expectancy violations theory (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:198:y:2025:i:c:s0148296325003212 DOI: 10.1016/j.jbusres.2025.115498 Access Statistics for this article Journal of Business Research is currently edited by A. G. Woodside More articles in Journal of Business Research from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.