Determinants to financial success in the Chinese box-office, Hollywood’s quest to capitalize on the world’s fastest growing film market.
Author: Timothy Sanders Student Number: 11090995
Date: 22-06-2020
Table of Contents
Statement of Originality and Abstract . . . Page 3 List of Abbreviations . . . Page 4 Introduction. . . Page 5 Literature Review. . . Page 5 Methodology. . . Page 9 Results. . . Page 12 Discussion. . . Page 18 Conclusion. . . .Page 23 Appendix. . . Page 26 Bibliography. . . Page 31
Statement of Originality
This document is written by Timothy Sanders who declares to take full responsibility
for the contents of this document.
I declare that the text and the work presented in this document are original and that no
sources other than those mentioned in the text and its references have been used in
creating it.
The Faculty of Economics and Business is responsible solely for the supervision of
completion of the work, not for the contents.
Abstract
Hollywood consists of internationally renowned production companies that have thrived for generations, but as international box office sales continue to outgrow the domestic sales, studios strategies and target audience are changing. China is set to become the largest box office market in the world while Hollywood attempts to keep its dominance in film production
internationally. This research attempts to determine whether determinants of financial success in China can be modeled to gain insight into the market and potentially improve future Hollywood strategy. Similarly to how previous researchers isolated factors that had an effect on domestic box office revenue, this research uses a multiple regression analysis to examine determinants in the Chinese market. Due to yearly quotas on foreign films the sample contained just 134 movies accepted from Hollywood studios from 1994-2019. Nine predictor variables were analyzed in attempt to discover impact on the Chinese box office revenue. Utilizing correlation, linear regression, and model analysis the determinants found to be significant, namely budget and inclusion of Chinese elements, were discussed for their implications on future strategy in a cultural industry such as Hollywood.
List of Abbreviations ANOVA- Analysis of Variance
Df- Degrees of freedom
H1, H2, H3, H4- Hypotheses 1 through 4 IMDb- Internet Movie Database
MPAA- Motion Picture Association of America rating system G- General Audiences
PG- Parental Guidance suggested PG-13- Parents strongly cautioned R-Restricted
N- Number(total) OV- Outcome Variable PV- Predictor Variable
Introduction
According to a PwC(2019) press release, China is on the cusp of surpassing the United States and is projected to become the largest box office in the world by 2023. For the future of
Hollywood’s studios it is thereby critical to adapt to this massive emerging market if they wish to retain dominant position in an increasingly global film market. There has been an increasing frequency of cases of Hollywood movies rejected from the Chinese censors or actually altered for Chinese audiences. China is unlike many western countries in that they place especially high value on increasing their “soft power”(Shan, 2014) in the face of Hollywood’s dominance. Shan points out that the Chinese government invests heavily in film and television to grow it at
accelerated rates. Furthermore China uses a quota system to avoid foreign production companies dominating the market as they do in free markets around the world.
This creates a curious mismatch for the future, in the industry the US dominates film production, and is likely continue to do so, yet within a few years the majority of their box office audience will be Chinese. Furthermore the trend for major Hollywood studios over the last two decades has been to turn the focus on extracting more from box office revenue in the
international markets, as well as domestic. Production studios pride themselves on the quality of their films but audiences market preferences change over time and are not easily predictable. The first man to do a multiple regression analysis on predictors of success in the US Film market was Barry Litman in 1983, in his data the only significant predictors were budget and critic reviews. This study aims to determine whether the Hollywood films have any of the same or differing determinants in the second largest film market, China.
Literature review
From the Chinese side many studies dedicate their research to how domestic film production can be increased and even target international markets. Unfortunately Chinese “film producers remain caught between market demands and state censorship that aims to maintain the Party-state's supremacy”(Su, 2014) making it difficult to continually produce and release
marketable movies internationally. The US producers currently hold this advantage and thereby it is curious to see many researchers historically exploring determinants in domestic box offices, but not nearly as many exploring determinants for international growing markets.
Figure 1: Global Film Market and Production Figure 2: Domestic and International Box Office Sales for Top 6 Hollywood Studios
Boxofficemojo.com StephenFollows
Diving deeper into China’s film industry there are important characteristics about the market that must be taken into account besides their rapid growth, firstly their foreign film quota. The first foreign film was allowed to show in China in 1993, from then western movies outdid their “Chinese counterparts, in both the number of films screened and ticket sales”(Aranburu, 2017). This caused China to protect their domestic film producers as well as promote cultural continuity by implementing a quota of only 10 foreign movies from 1996-2000, this grew by 2012 to 34, 14 of which now must be IMAX or 3D . If a major Hollywood studio is to enter this market they thereby must pass Chinese party censors, official guidelines are available and Escude(2013) also outlined in her study each criteria followed by Chinese government officials when judging Hollywood movies. Interestingly Ho, Rysman, Wang(2019) showed that consumer welfare increased by 10% from the 2012 import increase which shows promise for China’s attitude towards western movie imports in the future. Even though increasing the quota closer towards free trade would benefit both countries film industries further liberalization will continue to be slow for political and cultural reasons.
Through researching this industry it becomes evident from data and studies that
marketization in China, a protection tool “the purpose of which is to control market performance, overseeing what goes to market through “micro-adjustments” (weiguan tiao kong)”(Davis, 2010) is used heavily. Davis showed in some cases, protectionism and preferential handling allocated
market share for domestic pictures over international ones, putting another obstacle in the way of Hollywood studios’ success in China. However research into performance and especially
potential to improve performance of Hollywood studios within China is lacking due to
inaccessible data and few published journals on the topic. An interesting study by Song(2018) did propose relationship-management for Hollywood studios with the Chinese regulators and domestic producers as to assure a long-standing relationship and potentially work towards liberalization of policy over time.
The closest research done to evaluating how Hollywood can make a movie more
successful in China was an empirical study of Chinese box-office performance for foreign films, finding that various factors can play a role in sales such as using a well-known main actor, Chinese elements in the film, release time, genre, and more(Kwak & Zhang, 2011). The purpose of this thesis will thereby attempt to help bridge this gap in literature by asking, what key
determinants are most critical for Hollywood films to achieve high box-office performance in the Chinese market? Further it is interesting to see the implications of pursuing each factor as a key part of strategy for a film. This would impact them financially and, as Hollywood is a cultural industry, creative depreciation or self-censoring is even a potential threat to their future with Chinese censors and increased competition from fast growing state-sponsored production companies. It is also important to mention that when a Hollywood studio succeeds in getting their film to Chinese box-offices, the revenue sharing results in only a 25% return. On average 43-49% of box office income in the US or Europe would go to the production company, though this varies due to negotiations between the studios and distributors as well as differing sales tax by region. China’s split of 25 percent is due to theatrical distribution being dominated by state run China Film Co. and Huaxia, Hollywood has little leverage in negotiation with these parties when discussing revenue sharing proportions. The primary focus of this research is to then determine, what determinants of a Hollywood film significantly affect Chinese box office revenue?
This study will focus on four hypotheses, two shall focus on determining if there is a statistically significant main effect, and the other two will find whether a mediator or moderator affects the relationship between the predictor and outcome variables. The null hypothesis would be that no factors have any significant effect on the outcome variable of Chinese box office revenue. The research will first test this hypothesis: Does a Hollywood production studio’s
budget for a given film have the largest significant effect on box office sales of that film in China? The first hypothesis is similar to what has been proven to be true in many studies(Litman & Ahn, 1998 and Pangarker & Smit, 2013) pertaining to specifically domestic box offices so it would be likely that as in the domestic market, the budget of a Hollywood film has the greatest effect on the box office performance in China as well. There is a potential that, unlike in previous studies and due to the unique market restrictions china has on the film industry, there would be an unusually high importance on including culturally specific elements. If the quota is so low for foreign films in China it could be posited that rather than budget, hypothesis two states the largest effect on financial success in the Chinese box office would be the inclusion of Chinese elements. This second hypothesis stems from the idea that a difference in budget, or making a medium or large budget movie, is irrelevant if Chinese party censors decide the film is not worthy of a quota slot. Though it is not possible with this data to determine whether the Chinese elements directly impact the Chinese party censors admission decisions, but perhaps it will be reflected in sales.
The next two hypothesis focus on possibilities of mediation or moderation. The primary hypothesis posits that budget has the main significant effect on sales in Chinese box office, so in the case that Chinese elements do not outweigh budget an interaction effect can be tested. This would mean the Chinese elements in film moderate the effect of budget on sales and inclusion of them significantly increases likelihood of financial success in Chinese box offices. If this is true, it would effectively depict that making a larger budget movie would bring in more Chinese box office sales, but adding Chinese elements would significantly increase that revenue further and thereby Hollywood should recognize this factor and utilize it in strategy. Lastly if the inclusion of Chinese elements is neither of primary significance nor a true moderating factor, it could be expected that as in previous domestic box office studies(Scott, 2019) the inclusion of a star actor would be significant. Though not directly an actor of high notoriety would actually mediate the effect as the larger budget pays for the star lead which results in higher sales in the box office. Though this is potentially true in the United States box office, the Chinese audience does not have the same familiarity with western celebrities so would having a top 500 celebrity as the lead role positively mediate the effect of budget on Chinese box office revenue?
Methodology
This study will be conducted by taking a sample of 134 Hollywood movies released in China’s theaters since 1994, most of which premiered in the last decade as import quota policy loosened. The data is difficult to gather but through the use of journals and databases such as EntGroup, BoxofficeMojo, TheNumbers, IMDb, and ChinaFilmInsider information was compiled using their various articles, rankings, reports and financial breakdowns. The list includes the first releases to see the Chinese box office but more importantly the top 100 Hollywood box-office films and more rated by Chinese box office performance. For each film there were 15 factors to extract; year of release, title, studio, genre, release date, Chinese elements, director notoriety, actor notoriety, IMDb score, awards, MPAA rating, franchise, budget, sales, and the database source from which the information came. From this complete dataset the experiment will categorize each factor and attempt to discover if any of the factors are significant determinants of box office success in China for a Hollywood studio.
First each of these variables must be individually specified as to what comprises it. The dependent variable or outcome variable, revenue, is most easily defined, for each film the total box office sales within China were either shown in millions of dollars or yuan, all were
converted to dollars using historical conversion rates based on the release date. This information for box office sales in China was sourced from TheNumbers, BoxofficeMojo, and EntGroup databases. Further there are various independent factors to define before determining their potential effect on Chinese box office performance. Budget is the first of these independent variables, it was measured in millions of US dollars and extracted from IMDb and TheNumbers databases. Perhaps the most difficult to understand of the predictor variables is “Chinese
elements”, for this data it is measured as inclusion of any of the following: Chinese production company, filming location in China, using Chinese main actors or directors, Chinese history plot, Chinese martial arts plot, and including extra scenes made for Chinese audiences only. One reason this predictor variable could prove critical is due to the quota, within China only approved movies will be screened so perhaps inclusion of these elements helps secure one of the 34
available slots per year, even if it doesn’t directly affect sales. This study used a different definition than Wang & Ding(2009) who referred to Chinese elements as national symbols, customs or image etc., which are full of Chinese traditional cultural characteristics and spirit. For the purposes of a business study instead of using “Chinese staff” which was an element that
included production company, actors, directors from China as a separate variable, the two were combined to form this Chinese Elements variable. The variables such as year of release, title, studio, and source were not predictor variables and were needed for completion and coherence of the dataset. The studio variable was to indicate which studios produced the film and the source variable is to indicate which database the sales revenue information came from as it was difficult to find.
On the other hand many other predictor variables will be used in attempts to create an effective model, the first being genre; using IMDb each genre was determined and listed as only one of 6, the primary genre label provided by the database out of action, animation, comedy, drama, fantasy, and mystery. With the IMDb database the awards and IMDb score were also extracted, the first of which is coded with a 0 or a 1 for achieving an Oscars win. For the ratings variable a 0-10 scale was used from IMDB which is determined by user and critic reviews. Using IMDb, the MPAA ratings were also factored with G, PG, PG-13, and R being recoded into a 1-4 scale, and the franchise variable was set as 1 if part of a film series, otherwise 0. Franchise is not the same terminology as much of the business world, in the film industry it refers to films that are part of a series, such as “The Avengers”. The last of the predictor variables were director and actor notoriety, for the directors in IMDb’s top 250 a 1 would be coded whereas a 0 was for any other director. The actor notoriety used TheNumbers database which uses a ranking system based on cumulative worldwide box office of all films an actor has had a leading role in
throughout their career, the actor had to be within the top 500 to be coded a 1 otherwise the lead actor variable displays 0. Lastly the Chinese release date was taken from TheNumbers database and IMDb then transformed to have each day represented from 1-365 to see if seasonal trends or holidays are significant.
In order to determine acceptance or rejection of each of the four hypotheses various tests for correlation, regression, and interaction effect will be utilized. A correlation and regression analysis will take the various factors such as inclusion of Chinese elements, budget, genre, director notoriety, lead-actor notoriety, MPAA ratings, critic reviews(IMDb score),
awards(golden globe/academy award), and more into account to determine the effect on box office performance. The outcome variable will be measured as box-office revenue in millions of dollars. This analysis will give insight into which variables have a significant effect and can help
to determine the factors Hollywood studios should focus on in planning a movie for success in China. The primary predictor variable is budget and is measured in millions of dollars, same as box office revenue. Figure 3 also shows the alternative hypothesis to the main effect would place the inclusion of Chinese elements in as the predictor variable. Further the third hypothesis would test the moderating effect of Chinese elements on the relationship between budget and revenue, and the fourth depicts a mediating effect of the actor notoriety. Further analysis from a cultural industry standpoint will also be discussed to assess possible positive or detrimental effects of utilizing the strategies that show to be statistically effective.
This study took two empirical models into account, the first of which included all possible factors in the model and measured every factors significance. The second linear model left out factors that did not contribute to higher validity thereby producing the most reliable model with the best adjusted r-squared given all the factors:
Model 1: Revenue = βo + β1Budgeti + β2Elementsi + β3Actori + β4Releasedatei +
β5Awardsi + β6IMDbScorei + β7Franchisei + β8Genrei + β9Directori +
Model 2: Revenue = βo + β1Budgeti + β2Elementsi + β3Actori + β4Releasedatei +
Results
Descriptive Statistics
Data analysis can first deliver insight into what kind of Hollywood movies are entering the Chinese market over the years simply by observing descriptive statistics and frequencies of variables. For instance the average box office return in China was 107 million dollars while the budget average was 152 million. Though this is a respectable return if the film also succeeds in the US box office it implies Hollywood studios can still find strategies to become more
profitable as the Chinese market grows, even if the film flops in the domestic market. The Chinese market had 71.6% of the movies in the sample belonging to a franchise, as well as 73.9% being in the action genre, 78 out of the 134 or 58.2% of movies were an action franchise. Figure 4 further displays that only 37 films contained Chinese elements, 18 had a director of notoriety and 18 titles had won an Oscar. The average MPAA rating was 2.84 rounding to PG-13, and the IMDb score average was 6.9/10. Lastly this table reveals the average release year was recent, 2015, and the Chinese release date had a median of 166 and mean of 172 making June the most popular month for Hollywood film releases.
Some of the interesting features of this sample were that the range of sales were so broad from just over 3 million to 629 million dollars. This is primarily due to the slow and limited introduction and recent explosive popularity and import of Hollywood films to China over the decades. This is also supported by the large variation yet clustered data towards the last decade in the year of release category as it shows most of the Hollywood films imported into China came recently, opening up a much larger market. Lastly 81 of the 134 films contained a star actor who likely would be recognizable to other cultures due to their notoriety but these actors were primarily action movie actors, comparably there was only a small number of dramatic stars: Leonardo DiCaprio, Matt Damon, Matthew McConaughey, and Will Smith. This would more likely be attributed to the popularity of the genre than the stars themselves with Hollywood dramas accounting for just 8.2% of the sample. Animation was slightly more popular with 13.4% and comedy, fantasy, and mystery all accounted for less than 5% cumulatively.
Figure 5- Frequency for Sales and IMDb score split by Chinese Elements
Figure 6- Density of Release Dates, Day 0 to 365.
Further descriptive analysis found that by splitting variables by Chinese element
inclusion, as seen in figure 5, there are intriguing variations such as lower IMDb score for films with Chinese elements yet a higher density of those films making above 180 million in box office revenue. This could allude to IMDb not appreciating the Chinese elements the same way Chinese audiences do, or simply that despite the movie rating element inclusion increases the audience draw. The release date depicted in figure 6 is also curious as there is one period which is by far the most popular for movies, the summer, followed by a large dip and small spike just before the new year holidays, namely November and December. This could point to holidays playing a role in box office attendance or in families having kids on summer break increasing attendance but specific holidays were not tested for direct effect on sales for the purposes of this research. To investigate to the concept that IMDb ratings are not as important if including
Chinese elements, the awards and franchise variable were also split by Chinese elements. Figures 7 and 8 showed that of the 37 films with Chinese elements 28 were part of a franchise and only one film, which had a Chinese production company cooperate with DreamWorks, the
Greenbook, got an Oscar. Further research would need to be conducted to find a reason for the higher frequency of Chinese elements used in franchises specifically and the low award count.
Correlation Analysis
Figure 9- Correlation Matrix from Appendix D
Figure 9 consists of a correlation matrix that can determine whether the null hypothesis is to be accepted or rejected. If there were no significant factors helping to predict the success in Chinese box offices for Hollywood films there would be no positive correlations with a p-value of less than 0.05. The first variable in the table, budget, has a correlation of .489 with sales forming a moderate strength relationship validated by the p-value of less than 0.001. Already the null hypothesis can be rejected but another variable also shows a positive correlation with the outcome variable, namely Chinese elements with a Pearson’s R of .238 and p-value of 0.003. This indicates a slightly weaker but significant correlation between Chinese elements and box office revenue which demands further analysis to determine its exact relationship. None of the other variables correlate significantly with the dependent variable of revenue but interestingly other variables correlate amongst themselves.
Budget showed a positive correlation and significant p-values with franchise and IMDb score, meaning a franchise has a higher budget than other movies in the sample and higher budget films resulted in higher IMDb scores. MPAA and director were significantly correlated as 16 of 18 were rated PG-13 and 2 rated R, this simply demonstrates that these directors of
IMDb score as well as director with Pearson’s R of .428 and .294 respectively and a p-value below 0.001 for both. This depicts that films with directors of notoriety and/or high ratings are likely to receive awards, these correlations just help to validate the dataset as they are
correlations researchers would expect to discover in the film industry as awards and critic reviews often give directors their notoriety.
Regression Analysis
Figure 10- Model 1 Regression- Appendix E Figure 11- Model 2 Regression- Appendix F
The two linear models discussed at the end of the methodology were tested to determine which accounts for a greater influence on revenue, figure 10 included all elements(model 1) and figure 11 only used those in model 2. Both models had an overall significance with p-values at or below 0.001 however model 1 had a F value of 2.09 whereas model 2 had a much higher F test statistic of 15. There is a larger R value for correlation in model 1 but this is due to inclusion of so many more factors and doesn’t add validity necessarily. Furthermore with the increase of the adjusted R squared from .286 in model 1 to .296 in model 2 it is evident that omitting certain variables actually increased the validity of the model as a predictor for Chinese box office revenue. The variables that contributed as predictors to model 2 were budget, Chinese elements, release date, and actor notoriety. This model then showed in the follow up omnibus ANOVA test that both Chinese elements and budget had a p-value of less than 0.001, but budget is certainly the stronger predictor variable with an F value of 44.28 compared to 11.98 for Chinese elements. This allows for the acceptance of the hypothesis that budget, just as in the domestic market(Del Vecchio, et al. 2020, p.15), was the largest significant determinant for Hollywood films revenue in Chinese box offices. Concurrently the hypothesis that Chinese elements would be the
strongest determinant is rejected though it is important to note it is still a significant determinant to revenue in the Chinese box office for Hollywood films.
Moderation and Mediation Analyses
Figure 12- Moderation analysis from Appendix G
To further analyze the potential interaction between inclusion of Chinese elements and box office revenue for Hollywood films in China, a moderation analysis was utilized. The relationship between film budget and revenue was established previously with a significant correlation and the strongest impact in the validity of Model 2, but was the relationship moderated? The analysis in figure 12 demonstrates that budget and element both showed significant effect on the outcome variable Chinese box office sales, however the interaction variable budget*element was not significant with a p-value of .288. This results in the rejection of the hypothesis that inclusion of Chinese elements moderates the budget and sales relationship to result in significantly higher revenue. Lastly there was an analysis to determine if any
mediating effects were significant on the relationship between Hollywood film budget and Chinese box office sales. The mediating variable chosen was actor notoriety as a large budget allows for the salary of star actors, which could potentially increase the revenue for box office sales in China. The actor notoriety variable was also shown to be the only potential mediator in Model 2 to test an indirect effect for, despite not having a significant correlation with sales in the previous analysis. Figure 13 on the next page demonstrates the results of the test, finding that the direct effect was significant and accounted for over 99% of the effect in the relationship, whereas the actor variable had an insignificant interaction effect with a p value of .72. This results in the rejection of the final hypothesis that having a star actor would positively mediate the interaction between the Hollywood film budget and the Chinese box office sales.
Discussion
Budget
After looking at both models only model 2 for box office sales will be discussed further as it was an overall stronger model, the predictor variables included budget, Chinese elements, release date, and actor notoriety. The first of those, budget, was the most significant with correlation to sales and largest impact on the model. The moderately weak relationship does show that budget is a key determinant to a Hollywood studio being able to make higher revenue in the Chinese box office. As seen in figure 14 each variable for model 2 is broken down into the separate predictor variables, budget has a significant p value and the highest t-test statistic. As a strategy Hollywood should assure they have a sufficiently large budget to achieve the qualities the Chinese market desires. The mean of 152 and median of 150 for the budget within the sample indicates studios should expect to raise 150 million dollars or more for film
production if they desire financial success in Chinese box offices. Amazingly the two most expensive movies to produce also outperformed immensely, the most recent instalments of “The Avengers” costed 677 million to produce but generated around 989 million in Chinese box office sales alone. As budget was shown to have a positive significant correlation with the franchise variable as well, it would be advised for Hollywood studios to further investigate whether a strategy for export of not just large budget films, but large budget franchise films is more appropriate.
Budget also had a significant positive correlation with IMDb score meaning a large budget would not only attract Chinese box office revenue abroad but also appeal to the western film critics and audiences. This is optimal as increasing the budget would allow Hollywood studios to get a larger foreign market return as well as increasing potential for awards as a significant correlation was shown with IMDb score and awards as well. When searching further for a potential strategy it is important to note that of the 37 films including Chinese elements 20 were produced or co-produced with a Chinese studio. Co-production could be a beneficial
strategy to employ for Hollywood studios as it could increase the chances for a film to gain entry considering the foreign film quota, and as will be discussed next, also increase box office sales.
Chinese Elements
Production company was the most popular way of including Chinese elements in a Hollywood film’s production, the next being the casting of a recognizable Chinese star. The Chinese elements, as seen in figure 14, have a significant effect in model 2 and held a significant correlation in figure 9 with Chinese box office revenue. Effectively the Chinese elements
variable, like the budget, should thereby be taken into account as a determinant to success for Hollywood films attempting to enter the Chinese market. Though it had a smaller effect it nevertheless impacts the Chinese box office financial performance of the Hollywood studio. Taking into account the trend of the inclusion of these elements being clustered in the last 5 years, it is likely that the importance of these elements will grow in the future. Furthermore due to the “Chinese state's selective and conditional opening-up of space, global Hollywood can only operate within the parameters set by the Party-state”(Su, W., 2014, p113). If the trend continues for inclusion of these elements, primarily co-production, it would be unwise for a Hollywood
studio to exclude them from their film production process as the competitors would have an advantage and films could be rejected.
The test to determine if Chinese elements in fact moderated the relationship between budget and sales was not significant. This meant that the inclusion of these elements would not change the relationship between budget and sales, it only added to the revenue as a separate predictor variable. One change that would drastically alter the significance of the inclusion of elements would be if the Chinese party officials lifted the quota of foreign films altogether, but this is an unlikely decision. Currently the Chinese officials plan to grow their domestic film industry so it can one day rival larger worldwide industries, thus co-production is most beneficial for swapping production skills and sharing sales revenue with established international studios. An important query is the reason for the inclusion of these elements, one option could be to gain appeal to the Chinese general audiences while another could be to appease party censors and influence the decision for inclusion within the 34 film quota. Due to the elements inclusion being correlated and positively influencing sales it is likeliest the first of the two options. The inclusion of Chinese elements seems to be popular as they sell more tickets, but perhaps the reason is a mix of both unfortunately this cannot be feasibly tested.
Significance of Other Factors
The next factors in model 2 did not have a significant correlation with the outcome variable but some insight into each variable was gained. The release date and actor notoriety helped to increase the models validity but are not key determinants for the Chinese box office performance of Hollywood films. The release date did however show interesting features with peaks and drops during summer to winter seasons, further study into why the summer and November timeframe are most popular for Hollywood cinema releases in China could help to optimize marketing for the Chinese audience. No strategic change should be extrapolated from this variable but knowing the peaks of releases is important for understanding the patterns of the competitors within the Hollywood studios in the future. The last variable in the model was actor notoriety which mirrored Litman’s (1983) research as it had no impact on the box office revenue of the domestic market either. Actor notoriety was also tested to determine if it was a positive mediating effect between budget and sales but was discovered to have no significant indirect
effect. Effectively including a star actor does not increase the Hollywood film’s Chinese box office revenue directly or indirectly. It could be posited that, since the top 500 actors of this database are dominated by westerners, it is not culturally transferrable thus reducing the impact of the actor notoriety on sales in a different country. If using a ranking system that qualified by popularity of actors using a Chinese audience, it would be much more likely to find a correlation and a significant impact on sales. If a database compiles this somehow further research could be done into actor notoriety’s significance with this sample.
Though only two predictor variables had significant impact on Chinese box office revenue there were correlations amongst other variables worth discussing. The IMDb score was significantly correlated with budget thus adding to the validity of a strategy for a Hollywood studio to focus on film budgets over 150 million to capitalize in Chinese and seemingly appeal to the United States audiences simultaneously. The IMDb score was also correlated with awards, most likely because the academy judges reviews are taken into account in IMDb’s rating scale. The Awards were treated as a dummy variable indicated a 1 for winning an academy award otherwise a 0, and it correlated with the director notoriety variable as well. Though the IMDb score and awards correlation is likely from the result of the same judges influencing both variables, the director notoriety is interesting as it shows how highly the judges value the top directors’ films. Though it is not necessary for Hollywood films sales within the Chinese market it would seem a good domestic strategy would be to not only have a high budget but also a star director to lead to both higher IMDb scores and awards. The last correlation was between the director notoriety and MPAA rating, this is due to the fact that all the directors chose to avoid children’s content, all fell in the PG-13 to R category. This requires no strategic changes as Hollywood studios already know they must take into account that star directors are unlikely to want to make children’s films.
Figure 16-Frequencies of Franchise split by Chinese Elements
Some descriptive statistics in figure 15 gave insight into the dataset which warrant further discussion, such as the 99 of 134 Hollywood films being action in the Chinese market, begging the question as to the reason for its overwhelming popularity. It could be theorized that comedy and drama are less culturally translatable, whereas action scenes of fighting, running, flying, etc, are universally understandable. If this is the case for the popularity of Hollywood action films in China a study into whether special effects play a major role would be worth investigation as Hollywood has the most cutting edge CGI technology for action films. Another theory is that action movies would be less controversial with Chinese party censors thus increasing their proportion of the quota as they often steer clear of sensitive topics, criticisms, satire, and political or religious undertones. Information on how and which movies are chosen or excluded for the quota and for what specific reasons is not made available to the public so any information helping Hollywood to increase their likelihood of financial success in China is critical to strategy.
The frequency table in figure 16 also displays 28 of the 37 franchise films including Chinese elements, and if accounting for the earlier franchise films and only looking at 2015 and later, an even higher proportion of Hollywood franchise films included Chinese elements. This indicates the growing popularity as a trend with Hollywood studios. For these reasons the suggested Hollywood strategy is a coproduction with a Chinese studio, a budget of over 150 million, and, to increase the likelihood of success, export an action franchise film. The first two parts of the recommendation are shown to be significant determinants to Chinese revenue whereas the action franchise is a popular current trend despite unproven impact on sales. All of these recommendations are attempting to take into account that a given Hollywood studio may only be able to submit a few of their movies to party censors every year due to the quota. Therefore increasing the chance of the Hollywood film being accepted is arguably more
important than maximizing Chinese box office sales. Unfortunately the decision process behind the quota admittance is not available currently so cannot be effectively studied.
There were limitations to this research as the dataset created has a highly inconsistent amount of movies per year due to the quota and subsequent loosening. Furthermore the sample itself is not as large and thereby reliable as many domestic film studies as so few Hollywood films have been admitted to Chinese box offices over the last few decades. Another limitation is the lack of breakdown by genre, perhaps assigning multiple labels to one film if it is an
action/comedy or drama/mystery would be more representative of the impact of each genre than just assigning one primary genre label. It could also be argued that greater insight could have been gained by splitting Chinese elements into staff and elements like Wang & Ding(2009) to discern co-production significance but with the limited sample size it may have been insufficient for analysis. Future researchers should focus on gathering as much accurate data within the Chinese market as possible as there is growing competition and influential factors arising from the growth of the Chinese film industry and market. Another study in the future with a larger dataset should attempt to focus on the potentially most important factor, Chinese party censor admission decisions and what elements are key to omit or include within the Hollywood film production process. This is difficult to research as decisions may be based on politics or culture but it may be the most critical element for financial success and thereby requires further
investigation.
Conclusion
To recap some information discussed on the Chinese film industry and market, the quota was changed in 2012 to increase the foreign film import to 34 which created a much larger market for Hollywood to target. The Chinese market took on significantly more Hollywood films since 2014 when just 10 were included, by 2019 it was 18 films. This trend can only grow if the quota is loosened, but with the current situation certain determinants can be focused on in order to maximize the revenue from the sales of those movies that are accepted. The purpose of this study was to determine, what determinants of a Hollywood film significantly affect Chinese box office revenue? The determinants deemed significant could thereby potentially be utilized for Hollywood studios revenue maximization strategies in China. Two determinants were found to
be significant, the budget is the first of the two and holds the strongest effect on Chinese box office sales while Chinese elements was weaker but significant. Budget impacted not only sales but also correlated positively with franchise films and IMDb score indicating that a larger budget is beneficial for Chinese sales but likely also for domestic. The franchise correlation also
indicates a strategic opportunity for Hollywood studios as larger budgets tend to be given to franchise films if the previous film is successful. Given this fact it would be a logical choice to follow the popular trend of large budget action franchise films when looking to capitalize on the Chinese market. Significantly more research should be done into the reasoning for action and franchise film popularity in China in order to determine if this strategy is sound, however trends indicate the strategy to be popular In Hollywood, be it scientifically successful or not.
The second variable which showed a significant effect on the outcome variable of Chinese box office sales was inclusion of Chinese elements. The most popular way of inclusion was through co-production with a Chinese studio, this results in profit and cost sharing but could also influence the likelihood of admission into the 34 film cut. Despite the conclusion that Chinese elements in the production process for Hollywood films does in fact result in higher revenue it could not be determined with this sample what role they play in the Chinese party admission decisions. In the future, when more public knowledge is available about the decision making process of Chinese censors, a study into what Hollywood film qualities or content resulted in rejection would be far more useful strategically. Admission is usually the most
important aspect when discussing a market with quotas as otherwise no revenue will be extracted by some parties. Unfortunately with no identifiable strategy for guaranteeing admission current data allows only to make a strategy for increasing revenue if admitted.
There is still a very large gap in research for the Chinese film market due to sheer lack of data and precise information on admission requirements as many Hollywood studios had films rejected. It is difficult developing strategies for Hollywood’s future due to uncertainty of quota restrictions and government stimulated growth of Chinese studios with additional help of co-production. This poses a potential risk for Hollywood as China will surpass the United States as the largest box office market while attempting to grow a Chinese film industry powerhouse. In the future it could result in the quota tightening rather than loosening once Chinese producers gain experience, investment, and popularity in order to dominate their own market. It would be most advisable for a Hollywood studio to thereby use a budget over 150 million, include Chinese
elements especially co-production, and take note of the popularity of action franchises in the Chinese market if the studios wish to stay dominant. There is risk however in forcing production quotas by genre as a production studio since creativity can drop and drive away directors or stars due to set limitations. Realistically due to the quota each studio can only hope to release a few films to China a year so this should not threaten the production studio or overall cultural industry of Hollywood significantly due to their sheer output. In five years there will likely be a
significantly larger sample size and this study could be revisited with new and updated data. This would help future strategy and determine whether any of these factors discussed became
Appendices:
Appendix B: Frequencies split by Chinese Elements
Appendix D: Correlation Matrix
Appendix F: Linear regression analysis Model 2
Appendix G: Moderation Analysis
Moderation Estimates
95% Confidence Interval
Estimate SE Lower Upper Z p
Budget 0.776 0.114 0.554 0.999 6.84 < .001 transformElements 50.828 14.476 22.455 79.201 3.51 < .001 Budget ✻ transformElements 0.320 0.301 -0.270 0.910 1.06 0.288
Appendix H: Mediation Analysis
Mediation Estimates
Effect Label Estimate SE Z p % Mediation
Indirect a × b 0.00932 0.0141 0.661 0.509 1.28 Direct c 0.71700 0.1115 6.432 < .001 98.72 Total c + a × b 0.72632 0.1119 6.493 < .001 100.00
Path Estimates- Mediation
95% Confidence Interval
Label Estimate SE Lower Upper Z p
Budget → trasformActor a 2.71e-4
6.96e-4 -0.00109 0.00164 0.389 0.697 trasformActor → Gross sales(millions of USD) b 12.714 13.835 -14.40266 39.82999 0.919 0.358 Budget → Gross sales(millions of USD) c 0.723 0.112 0.50419 0.94156 6.479 < .001
References
Aranburu, A. M. (2017). The Film Industry in China: Past and Present. Journal of Evolutionary Studies in Business-JESB, (1). doi: 10.1344/jesb2017.1.j021
Chen, G., Wang, L., Zhang, L., Li, Q., & Qi, Z. (2017). The Analysis of Chinese Elements in Hollywoods Movies. Proceedings of the 2017 2nd International Conference on Education, Sports, Arts and Management Engineering (ICESAME 2017). doi:10.2991/icesame-17.2017.15 Davis, D. W. (2010). Market and Marketization in the China Film Business. Cinema Journal, 49(3), 121–125. doi: 10.1353/cj.0.0206
Davis, D. (2014). Marketization, Hollywood, Global China. Modern Chinese Literature and Culture, 26(1), 191-241. Retrieved March 23, 2020, from www.jstor.org/stable/42940476 Del Vecchio, M., Kharlamov A., Parry, G., & Pogrebna, G. (2020) Improving productivity in Hollywood with data science: Using emotional arcs of movies to drive product and service innovation in entertainment industries, Journal of the Operational Research
Society, doi: 10.1080/01605682.2019.1705194
Elberse, A. (2007). The Power of Stars: Do Star Actors Drive the Success of Movies? Journal of Marketing, 71(4), 102-120. doi:10.1509/jmkg.71.4.102
Forns, M. (2013). Hollywood Films in the Non-Western World: What are the Criteria Followed by the Chinese Government When Choosing Hollywood Film Imports? SSRN Electronic Journal. doi: 10.2139/ssrn.2509892
Hennig-Thurau, T., Houston, M. B., & Walsh, G. (2007). Determinants of motion picture box office and profitability: An interrelationship approach. Review of Managerial Science, 1(1), 65-92. doi:10.1007/s11846-007-0003-9
Ho, C., Rysman, L., & Wang, Y. (2019) Demand for Performance Goods: Import Quotas in the Chinese Movie Market. Retrieved from:
https://economics.princeton.edu/wp-content/uploads/2019/08/Demand-for-Performance-Goods-Import-Quotas-1.pdf
Kwak, J., & Zhang, L. (2011). Does China Love Hollywood? An Empirical Study on the Determinants of the Box-Office Performance of the Foreign Films in China. International Area Studies Review, 14(2), 115–140. doi: 10.1177/223386591101400205
Litman, B. R. (1983). Predicting Success of Theatrical Movies: An Empirical Study. The Journal of Popular Culture, 16(4), 159-175. doi:10.1111/j.0022-3840.1983.1604_159.x
Litman, B. R., & Ahn, H. (1998). Predicting financial success of motion pictures. In B. R. Litman (Ed.), The motion picture mega-industry. Boston, MA: Allyn & Bacon Publishing, Inc..
Pangarker, N. A., & Smit, E. (2013). The determinants of box office performance in the film industry revisited. South African Journal of Business Management, 44(3), 47–58. doi: 10.4102/sajbm.v44i3.162
PricewaterhouseCoopers. (2019, June 17). Strong revenue growth continues in China's cinema market. Retrieved March 17, 2020, from
https://www.pwccn.com/en/press-room/press-releases/pr-170619.html
Scott, Griffin (2019) "Determinants of Box Office Performance: Return of the Regressions," Major Themes in Economics, 21, 71-83.
Shan, S.-L. (2014). Chinese cultural policy and the cultural industries. City, Culture and Society, 5(3), 115–121. doi: 10.1016/j.ccs.2014.07.004
Song, X. (2018). Hollywood movies and China: Analysis of Hollywood globalization and relationship management in China’s cinema market. Global Media and China, 3(3), 177–194. doi: 10.1177/2059436418805538
Stephen Follows. How important is international box office to Hollywood? (2018, November 21). Retrieved from https://stephenfollows.com/important-international-box-office-hollywood/ Su, W. (2014). Cultural Policy and Film Industry as Negotiation of Power: The Chinese States Role and Strategies in its Engagement with Global Hollywood 1994–2012. Pacific Affairs, 87(1), 93–114. doi: 10.5509/201487193
Wang, H. M., & Ding, N. (2009, January). Tactfully use Chinese elements. Enterprise Management, 74-76.
Zhou, M. (2019, December 20). Blockbuster or bust: China's film industry is in a bind. Retrieved from https://asia.nikkei.com/Business/Industry-in-focus/Blockbuster-or-bust-China-s-film-industry-is-in-a-bind
