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Some economics of movie exhibition: increasing returns and Imax revenue premium

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Abstract

We strongly reject the hypothesis of theater design revenue neutrality using a large dataset of Chinese theaters. Instead, we find large increasing returns in revenue from adding auditoria up to 9 auditoria, close to constant returns from adding seats up to an intermediate seating capacity of about 120 seats, beyond which decreasing returns prevail, and a large revenue premium to having an Imax auditorium. These revenue gains are largely due to differences in capacity utilization rates, and to a lower extent to differences in screening intensity (more showings per screen), while price differences play a negligible role. We discuss various mechanisms that may rationalize deviations from theater design neutrality. We conclude that a large fraction of Chinese theaters have too few auditoria and too many seats per auditorium, although this is less so for recently built ones. These violations of profit maximization are likely explained by the long-term, irreversible, and risky nature of theater design choices.

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Notes

  1. According to Hanson (2019), the first multiscreen theater was opened in 1969 in Omaha, Nebraska.

  2. Innovations include changes in sound and image quality (e.g., dolby, THX), and more recently, the move to digital cinematography and the growth in Imax screens.

  3. With the exception of studies of spatial differentiation (Davis 2006a), the movie industry literature has paid surprisingly little attention to the role of outlet characteristics in the movie exhibition sector (McKenzie 2012; Kumb et al. 2017).

  4. Studying the impact of scale on revenue has been done in other industries (e.g., Wheelock and Wilson (2018)).

  5. To make this point clear, assume that firm i’s revenues are \(R(a_i,s_i|X)\), where \(X=\sum _i a_is_i\) is the total market capacity. We obtain that the total impact of adding an auditorium on firm i’s revenue, \({\tilde{\eta }}_a=\frac{a_i}{R}\frac{dR}{da_i}\), is \({\tilde{\eta }}_a=\eta _a + \alpha _i\eta _{X}\), where \(\eta _a\) is the design effect defined in the text, \(\alpha _i\) is firm i’s share of total capacity, and \(\eta _{X}=\frac{XR_X}{R}\) is the competitive effect of increasing capacity. In practice, \({\tilde{\eta }}_a\) and \(\eta _a\) are similar because both \(\alpha _i\) and \(\eta _X \le 1\) are small (see Sect. 4.3.1).

  6. The same holds if consumers come in groups that split in subgroups to watch (different) movies.

  7. The literature has also studied uniform pricing, revenue sharing contracts, and programming and scheduling decisions (playing time, release date, movie run) and whether these decisions depend on vertical integration (Filson et al. 2005; Moul 2008; Gil 2009; Corts 2001).

  8. Movie success also depends on the strategic release of movie titles within a season (Einav 2007), movie availability (Leung et al. 2019) and advertising (Moul 2008), among other determinants...

  9. Li Ruigang, https://hzdaily.hangzhou.com.cn/hzrb/html

  10. We have \(R=a*s*i*\frac{Tickets \; Sold}{a*s*i}*\frac{R}{Tickets \; Sold}\) with \(u=\frac{Tickets \; Sold}{a*s*i}\) and \(p=\frac{R}{Tickets \;Sold}\).

  11. This is a compromise we have to make to estimate interaction effects. While it takes an additional \(A+S-2\) auditorium and seat counts dummy variables to estimate nonlinearities in returns, allowing a general functional form with interaction effects requires an additional \(A*S-1\) coefficients which is numerically impractical.

  12. Chinese theaters must source movies from a single chain, independently of ownership status. A theater may not be owned by the chain it sources its movies from.

  13. VIP seats typically include (a) access to private and comfortable lounges; (b) comfortable seats; and (c) complementary snacks and drinks.

  14. We tried different clustering options (no cluster, market, theater) with no significant changes in the results.

  15. In Figure 3, the semi-parametric and parametric curves cross at 5.502, corresponding to a capacity of 245 seats, and only 6.63% of the observations are located to the right of that point, beyond which the two curves start to diverge.

  16. The upper bound of the 95% confidence interval crosses the horizontal line \(y= 1\) at the value 4.82, which corresponds to 124 seats.

  17. These values solve the linear system that sets the two elasticities equal to one.

  18. We reject \(1.185 = 1.739\) and \(0.058 = 0.510\).

  19. We reject \(2.151 = 2.3984\) and \(1.456 = 0.904\).

  20. Note that these values of \(\eta ^i_a\) still imply that total theater screenings increase with complex size, since the elasticity of theater screening to auditorium count is \(1-\eta ^i_a \ge 0\).

  21. The average viewer’s experience is what determines demand, if consumers do not know which seat they get when they purchase a ticket (free admission).

  22. A classic theaters that is within 3 miles of 2 or more Imax, for example, is matched to the Imax that it is closest to. This addresses the concern that the initial sample is not balanced because Imax theaters within a city may not have the same number of classic theaters nearby (see Table 12 in Appendix 2.5).

  23. We also tried Davis’ approach and obtained slightly larger results and this is probably due to a bias caused by new entrants having more auditoria.

  24. Although the changes in coefficient are small in column 1-2 relative to Table 2 column 3, we reject the joint hypothesis that the six coefficients are equal in both cases (p-value 0.000).

  25. The terms on the right-hand side of equation 8 weakly increase with a or s, and when the revenue elasticities are decreasing with auditorium and seat, as is the case in our application, the optimization problem has a single optimum.

  26. As explained in Sect. 4.3.1, \({\tilde{\eta }}_x^R \approx \eta _x^R\) for \(x=a,s\) (see equation 7).

  27. Even in the case of palace megaplex , we have \({\tilde{\eta }}_a^R=1\) with the surprising implication that the fixed theater cost is zero (\(p_N=0\)).

  28. Entgroup report entitled “Research Report on China Film Industry 2015-2016.”

  29. The fraction of newly build theaters that include an Imax auditorium has decreased up to 2011, after which it has sharply increased, to reach 6% in 2016.

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Liu, D., Courty, P. Some economics of movie exhibition: increasing returns and Imax revenue premium. J Cult Econ 46, 597–634 (2022). https://doi.org/10.1007/s10824-021-09425-4

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