부산대학교 도서관

This study introduces a novel deep learning-based framework designed to evaluate the impact of localization in online advertising within the film industry. Particularly, the authors consider movie poster images as an advertising tool. Employing an image-based deep learning technique, the study extracts and quantifies visual information to assess poster localization levels. Then, we estimate the effect of poster localization on the movie’s financial performance in a foreign market. The results reveal that the localization effect follows the U-shaped curve, implying that the relevant level of poster localization should be in two ways: either fully non-localized or extremely localized. We expect this research to contribute by proposing the empirical framework to not only explore the effect of online advertising in the service business, but also assess the effect of the international advertising strategy from the perspective of the movie poster localization. Moreover, we posit that this research has managerial implications in the sense that it can contribute to the decision-making process of the relevant level of localization and poster image modification.