East Asian films in the European market: the roles of cultural distance and cultural specificity
Bibliographic record
Abstract
Purpose This study investigates the impact of cultural distance on foreign box office performance of East Asian cinematic production in European markets. Predicated on two dimensions of a film's cultural specificity, namely content- and aesthetics-based components, this research advances current knowledge on the moderating effects of cultural specificity. Design/methodology/approach The authors compile a data set of 515 East Asian films released in European countries during the 2010–2018 period. Data are analyzed by hierarchical linear modeling. Findings Results show that cultural distance plays a negative role in affecting foreign box office performance and that aesthetics specificity of films weakens such a relationship, while content specificity of films can further strengthen the relationship. Practical implications The findings suggest that cultural specificity is a crucial element and a relevant marketing tool in the cross-country film trade. Film producers and distributors need to consider both distribution strategy and intercultural context in order to align effectively with differing cultural distance and specificity. Originality/value This study proposes a new categorization framework of cultural specificity and demonstrates the moderating roles of content and aesthetics specificity on the relationship between cultural distance and films' foreign box office performance. It offers implications for both theory and practice in global film marketing and trade.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".