期刊
ELECTRONIC COMMERCE RESEARCH
卷 21, 期 1, 页码 41-72出版社
SPRINGER
DOI: 10.1007/s10660-020-09456-7
关键词
Box-office forecasting; Modified generalized Bass diffusion model; Search trend data; Korean film market; NAVER search trend
资金
- National Research Foundation of Korea (NRF) - Korean government (MSIT) [2019R1G1A1006073]
- National Research Foundation of Korea [2019R1G1A1006073] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
By modifying the generalized Bass diffusion model and incorporating search trend data and historical movie-audience data, this study developed a new diffusion model for box-office forecasting. The empirical case study on the Korean film market demonstrated the significance of NAVER search trend data in post-release box-office forecasting, and the proposed model showed superior prediction power compared to two other representative diffusion models.
This study aimed to develop a new diffusion model for box-office forecasting by modifying the generalized Bass diffusion model with incorporation of search trend data and historical movie-audience data. To that end, first, movie-audience data (i.e., the number of moviegoers) and NAVER search trend data for each of the top 30 movies released in Korea in 2018 were collected by day. Then, the modified generalized Bass diffusion model, newly proposed in this paper, was applied in order to estimate the diffusion parameters. The results of our empirical case study on the Korean film market show that NAVER search trend data plays an important role in box-office forecasting after a movie is released. This study contributes to the extant literature by proposing a new diffusion model, which is a novel online big-data-driven methodology of box-office forecasting. In addition, comparison analysis with two other representative diffusion models was conducted, and the proposed model showed superior prediction power.
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