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

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Dapeng Liu
Dapeng Liu
Dapeng Liu
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Pascal Courty at University of Victoria
Pascal Courty
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Abstract and Figures

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.
Theater scale (a, s) density. Note: Bubble scatterplot for all 24K observations, using a grid of 10 seats and 2 auditoria
Theater scale (a, s) density. Note: Bubble scatterplot for all 24K observations, using a grid of 10 seats and 2 auditoria
… 
Normalized auditorium revenue elasticities. Note: The figure plots ηaR=βa+1-βaln(a+1)-ln(a)-1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\eta ^R_a=\frac{\beta _{a +1}-\beta _{a }}{ln(a+1)-ln(a)}-1$$\end{document}, for a=1∼15\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$a=1 \sim 15$$\end{document}, with 95% confidence intervals
Normalized auditorium revenue elasticities. Note: The figure plots ηaR=βa+1-βaln(a+1)-ln(a)-1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\eta ^R_a=\frac{\beta _{a +1}-\beta _{a }}{ln(a+1)-ln(a)}-1$$\end{document}, for a=1∼15\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$a=1 \sim 15$$\end{document}, with 95% confidence intervals
… 
Impact of seat count on revenue (log-log scale). Note: The red curve plots the semi-parametric estimate, the black curve a cubic parametric fit with 95% confidence interval, and the dotted line a 45% line
Impact of seat count on revenue (log-log scale). Note: The red curve plots the semi-parametric estimate, the black curve a cubic parametric fit with 95% confidence interval, and the dotted line a 45% line
… 
Seat count revenue elasticity ηsR\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\eta ^R_s$$\end{document}. Note: The black curve plots the derivative of the cubic parametric fit from Fig. 3 with 95% confidence intervals
Seat count revenue elasticity ηsR\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\eta ^R_s$$\end{document}. Note: The black curve plots the derivative of the cubic parametric fit from Fig. 3 with 95% confidence intervals
… 
Decompositions of normalized auditorium elasticities. Note: Decompositions presented in equation 3, applied to the 6 theater subgroups, and using coefficients from Table 4
+5
Decompositions of normalized auditorium elasticities. Note: Decompositions presented in equation 3, applied to the 6 theater subgroups, and using coefficients from Table 4
… 
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Journal of Cultural Economics (2022) 46:597–634
https://doi.org/10.1007/s10824-021-09425-4
1 3
ORIGINAL ARTICLE
Some economics ofmovie exhibition: increasing returns
andImax revenue premium
DapengLiu1· PascalCourty2
Received: 3 May 2021 / Accepted: 20 June 2021 / Published online: 1 July 2021
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature
2021
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 frac-
tion 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 maximiza-
tion are likely explained by the long-term, irreversible, and risky nature of theater
design choices.
Keywords Theater· Movie exhibition· Increasing returns· Imax premium· China·
Theater design· Screening intensity· Seat utilization rate· Spillovers
JEL Classification D2· L1· L82· Z11
1 Introduction
Delivering cultural goods often requires significant long-term investments in infra-
structure, which are subsequently used to share content: museums manage large
spaces for exhibitions, festivals venues build stages where concerts are performed,
and in our application, movie theaters build auditoria to screen movies. The choice
* Pascal Courty
pcourty@uvic.ca
1 College ofBusiness, Shanghai University ofFinance andEconomics, Shanghai, China
2 University ofVictoria, 3800 Finnerty Road, Victoria, BCV8P5C2, Canada
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
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