Korean Management Science Review (경영과학)

The Korean Operations Research and Management Science Society (한국경영과학회)
권호 표지
DOI QR코드

DOI QR Code

Comparative Analysis of Box-office Related Statistics and Diffusion in Korea and US Film Markets

한국과 미국에 있어 영화 수익관련 통계량과 확산 현상의 비교분석

  • Kim, Taegu (Simnet Co. Ltd.) ;
  • Hong, Jungsik (Department of Industrial and Systems Engineering, Seoul National University of Science and Technology)
  • 김태구 ((주)심네트) ;
  • 홍정식 (서울과학기술대학교 글로벌융합산업공학과)
  • Received : 2014.11.27
  • Accepted : 2015.03.24
  • Published : 2015.03.31
Download PDF
⟨ Previous Next ⟩

Abstract

Motion picture industry in Korea has been growing constantly and aroused various kinds of research attention. Particularly, the introduction of official box-office database service brought quantitative studies. However, approaches based on diffusion models have been rarely found with domestic film markets. In addition to the fundamental statistical review on Korea and US film markets, we applied a diffusion model to daily box-office revenue. Unlike conventional preference of Gamma distribution on the film markets, estimation results proved that BMIC can also explain the trend of daily revenue successfully. The comparison with BMIC showed that there is a distinctive difference in diffusion patterns of Korea and US film markets. Generally, word-of-mouth effect appeared more significant in Korea.

Keywords

References

  1. 권선주, "영화 흥행성과의 분석과 예측 : 뉴스와 웹사이트 데이터 이용", 문화경제연구, 제17권, 제1호(2014), pp.35-55.
  2. 김병도, 표태형, "개봉 전 영화의 수요예측모형", 경영논집, 제36권, 제1호(2002), pp.1-23.
  3. 김태구, 홍정식, "개봉 규모와 수익성에 따른 영화의 분류와 확산 패턴 분석", 대한산업공학회지, 제39권, 제5호(2013), pp.412-421. https://doi.org/10.7232/JKIIE.2013.39.5.412
  4. 김태상, "영화 <올드보이>의 서사미학 연구 : 포스트모더니즘 영화의 서사구조를 중심으로", 영화, 제6권, 제1호(2013), pp.93-111.
  5. 나지영, "영화 <늑대아이>와 이물교혼설화의 상호비교를 통한 서사의 보완", 문학치료연구, 제25집(2012), pp.313-339.
  6. 영화진흥위원회 정책연구부, 2013 한국 영화산업 결산 보고서, in, 2013.
  7. 이양환, 장병희, 박경우, "국가 간 영화흥행요인 비교를 위한 탐색적 연구 : 한국과 미국 영화시장에서 미국 영화의 흥행요인 비교를 중심으로", 언론과학연구, 제7권, 제1호(2007), pp.185-222.
  8. 이윤정, 신형덕, "원작의 유무와 형태가 영화 흥행에 미치는 영향", 한국콘텐츠학회논문지, 제13권, 제6호(2013), pp.108-115. https://doi.org/10.5392/JKCA.2013.13.06.108
  9. 최병호, 최성희, "한국 영화시장에서 영화 성과의 결정요인에 관한 연구 : 생존분석을 중심으로", 經濟硏究, 제29권, 제3호(2011), pp.139-160.
  10. 학술연구정보서비스, in, 한국교육학술정보원.
  11. Bass, F.M., "A new product growth model for consumer durables," Marketing Science, Vol.15, No.5(1969), pp.215-227.
  12. Bulte, C.V. and S. Stremersch, "Social Contagion and Income Heterogeneity in New Product Diffusion : A Meta-Analytic Test," Marketing Science, Vol.23, No.4(2004), pp.530 -544. https://doi.org/10.1287/mksc.1040.0054
  13. Elberse, A. and J. Eliashberg, "Demand and Supply Dynamics for Sequentially Released Products in International Markets : The Case of Motion Pictures," Marketing Science, Vol.22, No.3(2003), pp.329-354. https://doi.org/10.1287/mksc.22.3.329.17740
  14. Hogg, R.V., J. McKean, and A.T. Craig, Introduction to mathematical statistics, Pearson Education, 2005.
  15. Jedidi, K., R. Krider, and C. Weinberg, "Clustering at the Movies," Marketing Letters, Vol.9, No.4 (1998), pp.393-405. https://doi.org/10.1023/A:1008097702571
  16. Kim, T. and J. Hong, "Bass model with integration constant and its applications on initial demand and left-truncated data," Technological Forecasting and Social Change(2015), Forthcoming.
  17. Kim, T., J. Hong, and H. Koo, "Forecasting diffusion of innovative technology at prelaunch : A survey-based method," Industrial Managment and Data System, Vol.113, No.6 (2013), pp.800-816. https://doi.org/10.1108/IMDS-11-2012-0414
  18. Kim, T., J. Hong, and P. Kang, "Forecasting Box Office using Machine Learning Algorithms based on SNS Data, International Journal of Forecasting(2015), Forthcoming.
  19. Litman, B.R., "Predicting success of theatrical movies : An empirical study," The Journal of Popular Culture, Vol.16, No.4(1983), pp.159-175. https://doi.org/10.1111/j.0022-3840.1983.1604_159.x
  20. Mansfield, E., "Technical change and the rate of imitation," Econometrica, Vol.29, No.4(1961), pp.741-766. https://doi.org/10.2307/1911817
  21. Marshall, P., M. Dockendorff, and S. Ibanez, "A forecasting system for movie attendance," Journal of Business Research, Vol.66, No. 10 (2013), pp.1800-1806. https://doi.org/10.1016/j.jbusres.2013.01.013
  22. Marx, M.L. and R.J. Larsen, Introduction to mathematical statistics and its applications, Pearson/Prentice Hall, 2006.
  23. Ozkaya, E., Demand management in global supply chains, in, Georgia Institute of Technology, 2008.
  24. Qin, L., "Word-of-Blog for Movies : A Predictor and an Outcome of Box Office Revenue?," Journal of Electronic Commerce Research, Vol.12, No.3(2011), pp.187-198.
  25. Ravid, S.A., "Information, Blockbusters, and Stars : A Study of the Film Industry," The Journal of Business, Vol.72, No.4(1999), pp.463-492. https://doi.org/10.1086/209624
  26. Wang, F., Y. Zhang, X. Li, and H. Zhu, "Why Do Moviegoers Go to the Theater? The Role of Prerelease Media Publicity and Online Word of Mouth in Driving Moviegoing Behavior," Journal of Interactive Advertising, Vol.11, No.1(2010), pp.50-62. https://doi.org/10.1080/15252019.2010.10722177