본 연구는 박스오피스 실적, 즉 매출만 분석했던 기존 연구와 달리, 비용을 고려한 매출 성과, 즉 수익과 수익률의 관점 에서 영화성과의 영향요인을 분석하고자 2005~2006년 사이에 개봉된 한국영화를 대상으로 베이지안 네트워크 분석을 실시하였다. 본 연구는 기존 연구에서 다루지 못한 변수였던 영화의 수익성(profitability) 자료를 활용함으로써 가장 현 실적인 영화수익 모형을 검증했으며, 영화 성과에 영향을 미치는 변수들이 각각 독립적으로만 성과에 영향을 미친다고 가 정한 기존 연구와 달리 영향요인들 간의 관계를 밝히는데 성공하였다. 분석 결과 한국영화의 수익에는 마케팅비와 스크린 수가 가장 직접적인 영향을 미치며 제작비는 마케팅비를 통해 간접적인 영향을 주는 것으로 나타났다. 수익률의 경우에는 세 변수가 모두 수익률에 직접적인 영향을 미쳤다. 제작비는 배우, 마케팅비, 극장비중 등에 영향을 미쳤고, 배우는 감독, 배급자, 극장비중 등의 간접경로를 통해 수익에 영향을 미치는 것으로 나타났다. 마케팅비와 제작비가 수익 및 수익률에 어떠한 영향을 미치는지 알아보기 위해 조건부확률 등을 추가적으로 분석하였으며 그 결과 동일한 제작비 수준에서 마케 팅비의 증가는 수익에 매우 큰 영향을 미치는 것을 알아낼 수 있었다. 이 논문은 영화산업에 대한 학문적 이해를 높일 뿐 아니라, 제한된 자원으로 최적의 결과를 얻고자 하는 영화 마케터와 투자자에게 유용한 실무적 시사점을 제공해준다.
This study investigates how various factors influence the profitability of Korean movies. The current study is distinguished from previous studies by examining on the “profitability” of the movies instead of “sales revenue” or “box office results.” Based on the data from 192 films released in South Korea between 2005 and 2006, this study also tries to find meaningful inter-relationships among factors affecting the profitability of movies via a method called Bayesian networks. The most significant contribution of this research is to validate the most realistic and objective “movie performance model” by taking advantage of the profitability data. Most of the existing studies used theater attendance (box-office revenue) or video/DVD sales as the key performance of movies. However, such measurements don’t reflect all the costs of making and distributing movies, and therefore fail to give correct insights for making profits. For the analyses, the authors used Bayesian networks approach by utilizing the Genie program. Unlike the most popular regression analysis that assumes independence among “independent” variables, Bayesian networks is useful in exploring the causal inter-relationships among many variables. It allows not only to cross-examine the association between variables but also to determine the optimal allocation and combination of resources to increase the key dependent variable, which is profitability. Some of the key findings include the following. First, marketing expense (known as P&A) and the number of screens have direct influences on the net profit. Production cost only has an indirect impact on the profit via marketing expense. After the inter-relationships among variables were found, a series of sensitivity analyses were performed to see how the factors can best combined to yield desirable results. For example, when the level of marketing expense gradually increases at a certain fixed level of production cost, the chances of profitability dramatically increases. However, when the level of production cost gradually increases at a certain level of marketing expense, the changes in the profitability are relatively small. It means that the marketing expense has a greater impact on the net profit than the production cost has. Production cost only has an indirect impact on the profit via marketing expense. As for another profitability measure, the ROI(return on investment), both production cost and marketing expense have direct influences. The number of screens also have a direct influence on ROI. Some simulation runs gave us insights such as the following. The more aggressive marketing activity of low-budget film, the better the performance is likely to be. In case of the production cost of a huge blockbuster film, increasing marketing expense can worsen the performance. Therefore, focused investment in the production cost and marketing expense is a way to improve performance. Besides, the impacts of production cost on actors, marketing expense, proportion of theatrical revenue were confirmed. Actors turned out to influence the profitability, only by influencing the film director, distributor, etc. Despite a couple of limitations of this study, the analysis results of this research would not only help researchers develop a better understanding of how the film industry makes profts, but also aid practitioners in deriving an optimal strategy of allocating money into various aspects of filmmaking.