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02-04-2021

Box-office forecasting in Korea using search trend data: a modified generalized Bass diffusion model

Author: Daekook Kang

Published in: Electronic Commerce Research | Issue 1/2021

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Abstract

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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Title: Box-office forecasting in Korea using search trend data: a modified generalized Bass diffusion model
Author: Daekook Kang
Publication date: 02-04-2021
Publisher: Springer US
Published in: Electronic Commerce Research / Issue 1/2021
Print ISSN: 1389-5753
Electronic ISSN: 1572-9362
DOI: https://doi.org/10.1007/s10660-020-09456-7

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