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This study employs complexity and signaling theories to explore factors influencing film box office performance. It identifies internal signals (celebrity factors: actors, directors) and external signals (word of mouth: ratings, recommendations; marketing events: material releases, offline events) as key elements. Using fuzzy-set qualitative comparative analysis (fsQCA) on 482 films from the Lighthouse app, this study identifies five configurational paths to box office performance, including two configurations associated with high box office performance and three associated with non-high box office performance. Configuration 1 shows that high box office performance emerges from the combination of strong director reputation, favorable online recommendations, a large number of actor stars, and material releases. Configuration 2 indicates that high box office performance is also achieved through the alignment of strong director reputation, high movie ratings, a large number of material releases, and offline events. In contrast, configuration 3 suggests that non-high box office performance occurs when low movie ratings, low online recommendations, and fewer actor stars are combined with high director reputation and a large number of material releases. Configuration 4 indicates that non-high box office performance also results from the combination of low movie ratings, low online recommendations, low director reputation, fewer material releases, and more offline events. Configuration 5 shows that non-high box office performance is associated with low movie ratings, low online recommendations, low director reputation, fewer offline events, and a large number of material releases. This study contributes to the literature by offering new insights into the relationships among the predictors of box office performance and by advancing understanding of how celebrity factors, word of mouth, and marketing events combine to explain both high and non-high box office performance.
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Feng et al. (2026) studied this question.
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