“Winner-Takes-All”: Influencing Factors of the Post-Theatrical Supply and Demand in Motion Picture Exhibition

Kumb, Florian and Kunz, Reinhard E. “Winner-Takes-All”: Influencing Factors of the Post-Theatrical Supply and Demand in Motion Picture Exhibition. Journal of Creative Industries and Cultural Studies - JOCIS, 2022, n. 8, pp. 77-117. [Journal article (Paginated)]

[thumbnail of Research article]
Preview
Text (Research article)
Winner_Takes_All.pdf - Published version
Available under License Creative Commons Attribution.

Download (543kB) | Preview
Alternative locations: https://doi.org/10.56140/JOCIS-v8-4

English abstract

The post-theatrical exhibition has become essential for motion pictures to break even. Nevertheless, besides the first attempts to study TV broadcasters and streaming providers as release windows, academic research in marketing has concentrated primarily on the initial theatrical release. This article examines factors influencing supply and demand during the sequential release process of the motion picture industry. The authors build a modelling framework to analyze the drivers resulting in comprehensive supply and strong demand in major exhibition windows (i.e., during the home video, video-on-demand, and free-to-air TV exhibition). They estimate the conceptual model of regressions using market data from Germany, including all 5 200 theater-released motion pictures between 2005 and 2014. The authors expand the existing success-breeds-success theory and use a winner-takes all theory to explain market supply and demand in sequential distribution. The results reveal a limited set of influencing factors (e.g., word-of-mouth communication or certain genres) that increase the probability of comprehensive exhibition and strong demand. Other influencing factors depend on the exhibition window (e.g., age ratings). The results add to existing theories of sequential distribution and can help research-ers and managers improve movie-specific exhibition strategies.

Item type: Journal article (Paginated)
Keywords: Motion pictures, theatre, video-on-demand, exhibition window.
Subjects: B. Information use and sociology of information > BC. Information in society.
F. Management. > FB. Marketing.
L. Information technology and library technology > LA. Telecommunications.
L. Information technology and library technology > LC. Internet, including WWW.
Depositing user: Dr. Nicoleta-Roxana Dinu
Date deposited: 07 Feb 2023 07:47
Last modified: 07 Feb 2023 07:47
URI: http://hdl.handle.net/10760/44081

References

Ahmed, S., & Sinha, A. (2016). When it pays to wait: Optimizing release timing decisions for secondary channels in the film industry. Journal of Marketing, 80 (4), 20–38.

https://doi.org/10.1509/jm.15.0484

Basuroy, S., Chatterjee, S., & Ravid, S.A. (2003). How critical are critical reviews? The Box Office Effects of Film Critics, Star Power, and Budget. Journal of Marketing, 67 (4), 103–117.

https://doi.org/10.1509/ jmkg.67.4.103.18692

Basuroy, S., Ravid, S.A., Gretz, R.T., & Allen, B.J. (2020). Is everybody an expert? An investigation into the impact of professional versus user reviews on movie revenues. Journal of Cultural Economics, 44 (1), 57–96.

https://doi.org/10.1007/s10824-019-09350-7

Behrens, R., Zhang Foutz, N., Franklin, M., Funk, J., Gutierrez-Navratil, F., Hofmann, J., & Leibfried, U. (2021). Leveraging analytics to produce compelling and profitable film content. Journal of Cultural Economics, 45 (2), 171–211.

https://doi.org/10.1007/s10824-019-09372-1

Bi, G., & Giles, D.E. (2009). Modelling the financial risk associated with U.S. movie box office earnings. Mathematics and Computers in Simulation, 79(9), 2759-2766. https://doi.org/10.1016/j.matcom.2008.04.014

Boatwright, P., Basuroy, S., & Kamakura, W. (2007). Reviewing the reviewers: The impact of individual film critics on box office performance. Quantitative Marketing and Economics, 5 (4), 401–425.

https:// doi.org/10.1007/s11129-007-9029-1

Brewer, S.M., Kelley, J.M.; & Jozefowicz, J.J. (2009). A blueprint for success in the US film industry. Applied Economics 41(5): 589–606.

https:// doi.org/10.1080/00036840601007351

Bruce, N.I., Foutz, N.Z., & Ceren Kolsarici, C. (2012). Dynamic Effectiveness of Advertising and Word of Mouth in Sequential Distribution of New Products. Journal of Marketing Research, Vol. XLIX (August 2012), 469–486. https://doi.org/10.1509/jmr.07.0441

Chang, B-H, & Ki, E-J. (2005). Devising a practical model for predicting theatrical movie success: Focusing on the experience good property, Journal of Media Economics, 18 (4), 247–269.

https://doi.org/10.1207/ s15327736me1804_2

Chiou, L. (2008). The timing of movie releases: Evidence from the home video industry. International Journal of Industrial Organization, 26(5), 1059– 1073. https://doi.org/10.1016/j.ijindorg.2007.11.005

Chisholm, D.C., Fernandez-Blanco, V., Ravid, S.A., & Walls, W.D. (2015). Economics of motion pictures: the state of the art, Journal of Cultural Economics, 39 (1), 1–13.

https://doi.org/10.1007/s10824-014-9234-1

Clement, M., Wu, S., & Fischer, M. (2014). Empirical generalizations of demand and supply dynamics for movies. International Journal of Research in Marketing, 31 (2), 207–223.

https://doi.org/10.2139/ssrn.2359966

Daripa, A., & Kapur, S. (2001). Pricing on the internet. Oxford Review of Economic Policy, 17 (2), 202-216.

https://doi.org/10.1093/oxrep/17.2.202

De Vany, A., & Walls, W.D. (2002). Does Hollywood make too many R-rated movies? Risk, Stochastic Dominance, and the Illusion of Expectation. Journal of Business, 75 (3), 425–451.

https://doi.org/10.1086/339890

Ding, M., & Eliashberg, J. (2002). Structuring the new product development pipeline. Management Science, 48(3), 343–363.

https://doi.org/10.1287/ mnsc.48.3.343.7727

Elberse, A. (2007). The power of stars: Do star actors drive the success of movies?. Journal of Marketing, 71(4), 102–120.

https://doi. org/10.1509/jmkg.71.4.102

Elberse, A., & Eliashberg, J. (2003). Demand and supply dynamics for sequentially released products in international markets: The case of motion pictures, Marketing Science, 22 (3), 329–354.

https://doi. org/10.1287/mksc.22.3.329.17740

Eliashberg, J., Elberse, A., & Leenders, M.A.A.M. (2006). The Motion picture industry: Critical issues in practice, current research, and new research directions. Marketing Science, 25(6), 639–661.

https://doi.org/10.1287/ mksc.1050.0177

Eliashberg, J., & Shugan, S.M. (1997). Film critics: Influencers or predictors?. Journal of Marketing, 61(2), 68–78.

https://doi.org/10.1177/002224299706100205

Ginsburgh, V. (2003). Awards, success and aesthetic quality in the arts. Journal of Economic Perspectives, 17(2), 99–111.

https://doi. org/10.1257/089533003765888458

Gong, J.J., Van der Stede, W.A., & Young, S.M. (2011). Real Options in the Motion Picture Industry: Evidence from Film Marketing and Sequels. Contemporary Accounting Research, 28(5), 1438–1466.

https://doi. org/10.1111/j.1911-3846.2011.01086.x Gopinath, S., Chintagunta, P.K., & Venkataraman, S. (2013). Blogs, advertising, and local-market movie box office performance. Management Science, 59(12), 2635–2654. https://doi.org/10.1287/mnsc.2013.1732

Graham, J.W., Olchowski, A.E., & Gilreath, T.D. (2007). How many imputations are really needed? Some practical clarifications of multiple imputation theory, Prevention Science, 8(3), 206–213.

https://doi.org/10.1007/ s11121-007-0070-9 Hadida, A.L. (2009). Motion picture performance: A review and research agenda. International Journal of Management Review, 11(3), 297–335.

https://doi.org/10.1111/j.1468-2370.2008.00240.x

Hadida, A.L. (2010). Commercial success and artistic recognition of motion picture projects, Journal of Cultural Economics, 34(1), 45–80.

https://doi.org/10.1007/s10824-009-9109-z

Hadida, A.L., Lampel, J., Walls, W.D., & Joshi, A. (2021). Hollywood studio filmmaking in the age of Netflix: a tale of two institutional logics. Journal of Cultural Economics, 45 (2), 213–238.

https://doi.org/10.1007/ s10824-020-09379-z

Hair Jr., J.H., Black, W.C., Babin, B.J., & Anderson, R.E. (2010). Multivariate Data Analysis, Seventh Edition. Prentice Hall: New Jersey.

Hennig-Thurau, T., Henning, V., Sattler, H., Eggers, F., & Houston, M.B. (2007a). The last picture show? Timing and order of movie distribution channels. Journal of Marketing, 71(4), 63–83.

https://doi.org/10.1509/ jmkg.71.4.063

Hennig-Thurau, T., Houston, M.B., & Heitjans, T. (2009). Conceptualizing and measuring the monetary value of brand extensions: The case of motion pictures. Journal of Marketing, 73(6), 167–183.

https://doi. org/10.1509/jmkg.73.6.167

Hennig-Thurau, T., Houston, M.B., & Walsh, G. (2006). The differing roles of success drivers across sequential channels: An application to the motion picture industry. Journal of the Academy of Marketing Science, 34 (4), 559–575. http://www.jstor.org/stable/43549828

Hennig-Thurau, T., Houston, M.B., & Walsh, G. (2007b). Determinants of motion picture box office and profitability: an interrelationship approach. Review of Managerial Science, 1(1), 65–92.

https://doi. org/10.1007/s11846-007-0003-9

Hennig-Thurau, T., & Houston, M.B. (2019). Entertainment Science. Data Analytics and Practical Theory for Movies, Games, Books, and Music. Cham: Springer Nature.

Hennig-Thurau, T., Marchand, A., & Hiller, B. (2012). The relationship between reviewer judgments and motion picture success: re-analysis and extension. Journal of Cultural Economics, 36 (3), 249–283.

https://doi.org/10.1007/s10824-012-9172-8

Hennig-Thurau, T., Ravid, S.A. & Sorenson, O. (2021). The Economics of Filmed Entertainment in the Digital Era. Journal of Cultural Economics, 45, 157–170. https://doi.org/10.1007/s10824-021-09407-6

Hennig-Thurau, T., Völckner, F., Clement, M., & Hofmann, J. (2013). An ingredient branding approach to determine the financial value of stars: The case of motion pictures. Social Science Research Network.

http://doi.org/10.2139/ssrn.1763547

Hiller, R.S. (2017). Profitably Bundling Information Goods: Evidence From the Evolving Video Library of Netflix. Journal of Media Economics, 30(2), 65–81. 10.1080/08997764.2017.1375507

Hitt, L.M., & Chen, P. (2005). Bundling with customer self-selection: A simple approach to bundling low-marginal-cost goods. Management Science, 51 (10), 1481–1493. https://doi.org/10.1287/mnsc.1050.0403

Hofmann, J., Clement, M., Völckner, F. & Hennig-Thurau, T. (2016). Empirical generalizations on the impact of stars on the economic success of movies. International Journal of Research in Marketing, 34 (2), 442–461. https://doi.org/10.1016/j.ijresmar.2016.08.006

Hofmann-Stölting, C., Clement, M., Wu, S., & Albers, S. (2017). Sales Forecasting of New Entertainment Media Products. Journal of Media Economics, 30(3), 143–171. https://doi.org/10.1080/08997764.2018.1452746

Hosmer Jr., D.W., Lemeshow, S., & Sturdivant, R.X. (2013). Applied Logistic Regression. 3rd Edition. Hoboken: John Wiley & Sons. Joshi, A., & Mao, H. (2012). Adapting to succeed? Leveraging the brand equity of best sellers to succeed at the box office. Journal of the Academy of Marketing Science, 40 (4), 558–571. https://doi.org/10.1007/ s11747-010-0241-2

Koschat, M.A. (2012). The impact of movie reviews on box office: Media portfolios and the intermediation of genre. Journal of Media Economics, 25 (1), 35–53. https://doi.org/10.1080/08997764.2012.651063

Krider, R.E., & Weinberg, C.B. (1998). Competitive dynamics and the introduction of new products: The motion picture timing game. Journal of Marketing Research, 35 (1), 1–15.

https://doi.org/10.2307/3151926

Kübler, R., Seifert, R., & Kandziora, M. (2021). Content valuation strategies for digital subscription platforms. Journal of Cultural Economics, 45 (2), 295–326. https://doi.org/10.1007/s10824-020-09391-3

Kumb, F. (2018). Local Movie Supply in the German Motion Picture Industry: An Industrial Organization Perspective. Springer VS, Wiesbaden. https://doi.org/10.1007/978-3-658-20685-7

Kumb, F., & Kunz, R. (2017). Influencing factors of movie supply in Germany, Working Paper No. 01-17. University of Bayreuth, Faculty of Law, Business & Economics. Bayreuth. Lang, D.M., Switzer, D.M., & Swartz, B.J. (2011). DVD sales and the R-rating puzzle. Journal of Cultural Economics, 35 (4), 267–286.

https://doi. org/10.1007/s10824-011-9149-z

Leenders, M.A.A.M., & Eliashberg, J. (2011). The antecedents and consequences of restrictive age-based ratings in the global motion picture industry. International Journal of Research in Marketing, 28 (4), 36–377.

https://doi.org/10.1016/j.ijresmar.2011.06.001 Little, R.J.A. (1988). A Test of Missing Completely at Random for Multivariate Data with Missing Values. Journal of the American Statistical Association, 83 (404), 1198–1202.

https://doi.org/10.2307/2290157

Liu, Y. (2006). Word of mouth for movies: Its dynamics and impact on box office revenue. Journal of Marketing 70(3), 74–89.

https://doi. org/10.1509/jmkg.70.3.074

Luan, J.Y., & Sudhir K. (2010). Forecasting Marketing-Mix Responsiveness for New Products. Journal of Marketing Research, 47 (3), 444–457. https://doi.org/10.1509/jmkr.47.3.444

Marchand, A., Hennig-Thurau, T., & Wiertz, C. (2017). Not all digital word of mouth is created equal: Understanding the respective impact of consumer reviews and microblogs on new product success. International Journal of Research in Marketing, 34(2), 336–354. https://10.1016/j. ijresmar.2016.09.003

MPA (2021) THEME Report 2020. The Motion Picture Association, Inc. (MPA). 22/10/2021. Retrieved from https://www.motionpictures.org/wp-content/uploads/2021/03/MPA-2020-THEME-Report.pdf.

MPAA (2015). Theatrical Market Statistics 2015. Washington, D.C.: Motion Picture Association of America. McKenzie, J. (2010). How do theatrical box office revenues affect DVD retail sales? Australian empirical evidence. Journal of Cultural Economics, 34 (3), 159–179.

http://doi.org/10.1007/s10824-010-9119-x

McKenzie, J., Crosby, P., Cox, J., & Collins, A. (2019). Experimental evidence on demand for “on-demand” entertainment. Journal of Economic Behavior and Organization, 161 (March), 98–113.

http://10.1016/j. jebo.2019.03.017

Mortimer, J.H. (2007). Price discrimination, copyright law, and technological innovation, Evidence from the introduction of DVDs. Quarterly Journal of Economics, 122 (3), 1307–1350.

http://doi.org/10.3386/w11676

Mukherjee, A., & Kadiyali, V. (2011). Modeling multichannel home video demand in the U.S. motion picture industry. Journal of Marketing Research, 48 (6), 985–995. https://doi.org/10.1509/jmr.07.0359

Nam, S., Manchanda, P., & Chintagunta, P.K. (2010). The effect of signal quality and contiguous word of mouth on customer acquisition for a video on-demand service. Marketing Science, 29 (4), 690–700.

https:// doi.org/10.1287/mksc.1090.0550

Natividad, G. (2013). Multidivisional strategy and investment returns. Journal of Economics and Management Strategy, 22 (3), 594–616.

https:// doi.org/10.1111/jems.12018 Nelson, R.A., & Glotfelty, R. (2012). Movie stars and box office revenues: an empirical analysis. Journal of Cultural Economics, 36 (2), 141–166.

https://doi.org/10.1007/s10824-012-9159-5

Podsakoff, P.M., MacKenzie, S.B., Lee, J-Y., & Podsakoff, N.P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of Applied Psychology, 88 (5), 879– 903.

https://doi.org/10.1037/0021-9010.88.5.879

Prieto-Rodriguez, J., Gutierrez-Navratil, F., & Ateca-Amestoy, V. (2015). Theatre allocation as a distributor’s strategic variable over movie runs. Journal of Cultural Economics, 39 (1), 65–83.

https://doi.org/10.1007/ s10824-014-9220-7

Prasada, A., Mahajanb, V., & Bronnenberg, B. (2003). Advertising versus pay-per view in electronic media. International Journal of Research in Marketing, 20 (1), 13–30. https://doi.org/10.1016/S0167-8116(02)00119-2

Radas, S., & Shugan, S.M. (1998). Seasonal marketing and timing new product introductions. Journal of Marketing Research, 35(3), 296–315. https://doi.org/10.2307/3152029

Ravid, S.A. (1999). Information, blockbusters and stars: A study of the film industry. Journal of Business 72(4): 463–492.

https://doi. org/10.1086/209624

Ravid, S.A., & Basuroy, S. (2004). Managerial objectives, the R-rating puzzle, and the production of violent films. Journal of Business, 77 (2), 155–192.

https://doi.org/10.1086/381638

Ravid, S.A., Wald, J.K. and Basuroy, S. (2006). Distributors and film critics: Does it take two to tango? Journal of Cultural Economics 30(3): 201–218. https://doi.org/10.1007/s10824-006-9019-2

Sawheny, M.S., & Eliashberg, J. (1996). A Paramonious Model for Forecasting Gross Box-Office Revenues of Motion Pictures, Marketing Science, 15 (2), 113–131. https://doi.org/10.1287/mksc.15.2.113

Spann, M., & Skiera, B. (2003). Internet-based virtual stock market for business forecasting. Management Science, 49 (10), 1310–1326.

https://doi. org/10.1287/mnsc.49.10.1310.17314

Schauerte, R., Feiereisen, S., & Malter, A.J. (2021). What does it take to survive in a digital world? Resource-based theory and strategic change in the TV industry. Journal of Cultural Economics, 45 (2), 263–293.

https://10.1007/s10824-020-09389-x

Wallenstein, A. (2016). Why 2015 home entertainment figures should worry studios. Variety. January 6, 2016. Los Angeles: Penske Media Corporation.

https://variety.com/2016/digital/news/ home-entertainment-spending-2015-studios-1201673329/.

Walls, W.D. (2005). Modelling heavy tails and skewness in film returns. Applied Financial Economics, 15 (17), 1181–1188.

https://doi. org/10.1080/0960310050391040

Walls, W.D. (2009). Robust Analysis of Movie Earnings. Journal of Media Economics, 22 (1), 20–35.

https://doi.org/10.1080/08997760902724662

Walls, W.D. (2010). Superstars and heavy tails in recorded entertainment: Empirical analysis of the market for DVDs. Journal of Cultural Economics, 34 (4), 261–279. https://doi.org/10.1007/s10824-010-9125-z

Xing, X. (2010). Can price dispersion be persistent in the Internet markets?, Applied Economics, 42 (15), 1927–1940.

https://doi. org/10.1080/00036840701748987


Downloads

Downloads per month over past year

Actions (login required)

View Item View Item