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Revealed word-of-mouth demand and adaptive supply: survival of motion pictures at the Australian box office

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Abstract

This study considers a frailty duration approach to modelling the life-length of a sample of 360 films that went into wide release at the Australian box office from 1 January 2000 to 31 December 2005. The analysis extends previous research by considering a range of film-specific covariates relating to distribution, production, consumer signals, and weekly performance. In particular, it is shown that film success (defined in a duration context) responds to previewing, advertising, critical reviews, and US box office—but not to production budget, star power or opening-week screens. The study also reveals that it is appropriate to account for unobservable heterogeneity between films in the choice of empirical methodology.

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Notes

  1. See, for example, Smith and Smith (1986), Prag and Casavant (1994), Eliashberg and Shugan (1997), Albert (1998), Ravid (1999), Hand (2001), Collins et al. (2002), Basuroy et al. (2003), Elberse and Eliashberg (2003), Reinstein and Snyder (2005), Goettler and Leslie (2005), Jansen (2005), Ravid et al. (2006), Gemser et al. (2007), Einav (2007), Moul (2007), McKenzie (2008). De Vany and Walls have contributed significantly to this area with the research collated in De Vany (2004) that also provides a useful survey of the literature. See, in particular, De Vany and Walls (1996, 1999, 2004). See also Walls (1997, 2005a, b, c).

  2. Filson et al. (2005) analyse the exhibition contracts for 13 theatres in the St. Louis area over a 2-year period.

  3. In Australia, films are licensed individually and stipulate a division of revenues during the weeks of the run shifting in favour of the exhibitor in later weeks. Contracts typically also specify session requirements for each week and a minimum run period. Common industry perception is that distributors generally retain between 35 and 40% of revenue for most titles.

  4. A far-sighted distributor might even share a desire for a long-lasting film if they view the life-length as promotion for ancillary markets.

  5. The dynamics of week-to-week demand and supply decisions have received attention from marketing scholars. See, for example, Elberse and Eliashberg (2003) and Krider et al. (2005).

  6. See De Vany and Lee (2001).

  7. Walls (1998) considers life-length as time spent in the top 10, as reported by Variety.

  8. In particular, seasonality tends to peak dramatically around school and Christmas/new-year holiday periods, and it is around these times that distributors tend to release their big titles. See Einav (2007) for an analysis of the underlying seasonality in the US motion picture industry.

  9. Nelson et al. (2001) also utilise a model with unobserved heterogeneity and provide evidence that this is appropriate for their sample.

  10. Other candidate distributions include the exponential, log-logistic, Gompertz and generalised gamma.

  11. See Hougaard (1986) for discussion of frailty models.

  12. Another candidate distribution is the inverse-Gaussian. It can be shown that \( \lim_{\theta \to 0} S_{\theta } \left( t \right) = S\left( t \right) \) implying that both models reduce to S(t) when there is no heterogeneity.

  13. The MPDAA is made up of the six US-based studio distributors operating in the Australian market. These are 20th Century Fox, Universal Pictures, Paramount Pictures, Warner Bros., Buena Vista International and Sony Pictures Releasing.

  14. It should be noted that some films disappeared from the charts and then reappeared later. In these situations, life-length is defined as the number of weeks for which the MPDAA has recorded data.

  15. As data are reported by the distributor, there are unavoidable data omissions primarily from small independent distribution companies of art-house and foreign films. While the MPDAA makes an effort to report an opening week figure, often revenue is only reported for 1 or 2 weeks at the most.

  16. Assessing the direction of potential bias is non-trivial. Whilst it likely that high budget films are over represented due to reporting sources, it seems that mid-budget films are under represented with respect to reviews. The network television shows used in this study do not report all films each week, but seem to focus on the ‘block-busters’ and the ‘art-house’ end of the spectrum. The non-linear way in which covariates enter the survival function, therefore, makes speculation about bias direction extremely difficult.

  17. Contractual terms for previews vary but are generally at or below a second week level—implying less income for distributors.

  18. Although several studies have examined the role of advertising on financial box office success—see Prag and Casavant (1994), Vanderhart and Wiggins (2004), Elberse and Eliashberg (2003), Elberse and Anard (2006), Elliot and Simmons (2007)—all have used third party data sourced from companies that track media expenditures such as AC Nielsen or Variety.

  19. There may be an endogeneity issue with this variable as a successful run might very well encourage more advertising. However, this is assumed to be negligible, and it is known that most advertising expenditure occurs prior to a film’s official release—with distributors reporting as much as 90% spent before (and to coincide with) the release of most titles. Such endogenous behaviour on the part of distributors is also more likely to be observed for art-house titles that launch advertising campaigns in response to strong early demand. Given this study is concerned only with wide-release titles, such concerns are minimised.

  20. Unlike the Nielsen EDI and Variety standard for reporting US and UK box office, this variable refers to actual screen (engagement) counts, rather than theatre (location) counts.

  21. Additional theatres added after a given national release date are most likely to be suburban/rural theatres who may be offered more favourable contractual terms.

  22. The only study known to have considered the release gap between international markets is that of Elberse and Eliashberg (2003) who find longer time lags are associated with weaker relations between domestic (US) and foreign film revenues.

  23. Films are typically released on Thursdays in Australia and Fridays in the US. Therefore release gaps of −2, −1 and 0 days are defined to be simultaneous releases. Restricting the sample to only include films released firstly in the US omits only 12 films from the conditioned sample.

  24. Recall that Chisholm and Norman (2006) analysed life data for films at specific theatres.

  25. See De Vany and Walls (1996), McKenzie (2008) for analysis of weekly revenue patterns and skewed distributions using U.S. and Australian data, respectively.

  26. Australian production budget data was converted to US dollars at the average January 1997 bilateral exchange rate.

  27. Margaret Pomeranz and David Statton have been two leading Australian film critics for over 20 years. Up until 2004, they jointly hosted SBSs The Movie Show, and whilst the show continues on SBS with new reviewers (Fanella Kernebone, Megan Spencer and Jamie Leonarder), David and Margaret now host a similar show on ABC called At The Movies.

  28. A$5 m was chosen as it represents a film that achieves a good level of success represented at approximately the 85th percentile of the cumulative revenue distribution. Other definitions of this variable were examined but all were found to give similar results.

  29. All estimation is done relative to the genre of drama which defined 69 films of the conditional sub-sample. The other genre categories (and respective frequencies) include action (76), adventure (18), animated (19), black comedy (4), comedy (79), crime (2), fantasy (5), horror (10), musical (3), romance (3), romantic comedy (22), science-fiction (17), suspense (25) and thriller (8).

  30. As defined by the Office of Film and Literature (OFLC). All estimation is done relative to the rating M which defined 203 films of the full sample. The other rating categories (and respective frequencies) include G (25), PG (60), MA15+ (67) and R18+ (5). See De Vany and Walls (2002), and Ravid and Basuroy (2004) for discussion of film classification and the ‘R-rating puzzle’.

  31. The set of 52 dummy variables are all relative to a ‘week 53’ dummy variable that was used twice in the sample to avoid losing days due to the fact there are 365 days in a year and that every fourth year is a leap year. This allowed ‘week 52’ of the sample to always include Boxing Day (December 26)—the biggest single day of the year for Australian box office takings. The inclusion of week dummy variables controls for exogenous shifts of demand throughout a calendar year as used by De Vany and Walls (1997).

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Acknowledgements

The author acknowledges the support received from the Motion Picture Distributor Association of Australia (MPDAA) in this research, and is also grateful to the suggestions of two anonymous referees. The usual disclaimer applies.

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  1. Discipline of Economics, University of Sydney, Merewether Building H04, Sydney, NSW, 2006, Australia

    Jordi McKenzie

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McKenzie, J. Revealed word-of-mouth demand and adaptive supply: survival of motion pictures at the Australian box office. J Cult Econ 33, 279–299 (2009). https://doi.org/10.1007/s10824-009-9104-4

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