• Journal of Information Technology Services
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• v.14 no.2
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• pp.177-193
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• 2015

A great number of customers, who want to watch movies usually check out online reviews before choosing what to watch a movie. The most representative online media that customers consult are portal sites and SNS (Social Network Service). Although there have been numerous studies on online eWOM (e-Word of Mouth) and the effects of online media in businesses, it remains a question that which media is best for WOM (Word of Mouth) when selecting movies. This research examines customer's intention for consulting eWOM and for watching movies according to the number and tendency of online replies. We have compared portal sites and SNS about information of movie. The study shows that a large number of positive replies can affect the intention for WOM and choosing movies. Facebook has more influence than portal sites when choosing what to watch when replies consist of large and positive comments. However, there is no difference between the two types of media when they consist of negative comments.

• Asia pacific journal of information systems
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• v.25 no.3
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• pp.563-578
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• 2015

Forecasting daily box-office performance is critical for planning the distribution of marketing resources, and by extension, maximizing profits. For certain movies, the number of viewers increases rapidly at the beginning of their theatrical run, and the increments slow down later. Other movies are not popular in the beginning, but the audience sizes grow rapidly afterward. Thus, the audience attendance of movies grow in different trajectories, which are influenced by various factors including marketing budget, distributors, directors, actors, and word of mouth. In this paper, we propose a method for predicting the daily performance trajectory of running movies based on the hierarchical linear model. More specifically, we focus on the effect of online word of mouth on the shape of the growth curves. We fitted the mean trajectory of the cumulative audience size as a cubic function of time, and allowed the intercept and slope to vary movie-to-movie. Moreover, we fitted the linear slope with a function of online word of mouth predictors to help determine the shape of the trajectories. Finally, we provide performance predictions for individual movies.

• Cartoon and Animation Studies
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• s.16
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• pp.21-32
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• 2009

This study provides an empirical analysis of box office performance for animation movies released in Korea between 2003 and 2008. Two dependent variables are both the number of audiences in the whole country and the number of audiences in Seoul. Such independent variables are employed : power of distributors, the number of screens, release time, sequel/remake, awards, film ratings, nationality, online reviews, and critics' reviews. For the total number of audiences in the whole country, significant variables are the number of screens, the power of USA distributors, Summer release, and online reviews. Since there is no analysis for box office performance for animation movies released in Korean theaters, this study will be considered to be meaningful.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.49-65
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• 2014

Word of Mouth (WOM) is a behavior used by consumers to transfer or communicate their product or service experience to other consumers. Due to the popularity of social media such as Facebook, Twitter, blogs, and online communities, electronic WOM (e-WOM) has become important to the success of products or services. As a result, most enterprises pay close attention to e-WOM for their products or services. This is especially important for movies, as these are experiential products. This paper aims to identify the network factors of an online movie community that impact box office revenue using social network analysis. In addition to traditional WOM factors (volume and valence of WOM), network centrality measures of the online community are included as influential factors in box office revenue. Based on previous research results, we develop five hypotheses on the relationships between potential influential factors (WOM volume, WOM valence, degree centrality, betweenness centrality, closeness centrality) and box office revenue. The first hypothesis is that the accumulated volume of WOM in online product communities is positively related to the total revenue of movies. The second hypothesis is that the accumulated valence of WOM in online product communities is positively related to the total revenue of movies. The third hypothesis is that the average of degree centralities of reviewers in online product communities is positively related to the total revenue of movies. The fourth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. The fifth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. To verify our research model, we collect movie review data from the Internet Movie Database (IMDb), which is a representative online movie community, and movie revenue data from the Box-Office-Mojo website. The movies in this analysis include weekly top-10 movies from September 1, 2012, to September 1, 2013, with in total. We collect movie metadata such as screening periods and user ratings; and community data in IMDb including reviewer identification, review content, review times, responder identification, reply content, reply times, and reply relationships. For the same period, the revenue data from Box-Office-Mojo is collected on a weekly basis. Movie community networks are constructed based on reply relationships between reviewers. Using a social network analysis tool, NodeXL, we calculate the averages of three centralities including degree, betweenness, and closeness centrality for each movie. Correlation analysis of focal variables and the dependent variable (final revenue) shows that three centrality measures are highly correlated, prompting us to perform multiple regressions separately with each centrality measure. Consistent with previous research results, our regression analysis results show that the volume and valence of WOM are positively related to the final box office revenue of movies. Moreover, the averages of betweenness centralities from initial community networks impact the final movie revenues. However, both of the averages of degree centralities and closeness centralities do not influence final movie performance. Based on the regression results, three hypotheses, 1, 2, and 4, are accepted, and two hypotheses, 3 and 5, are rejected. This study tries to link the network structure of e-WOM on online product communities with the product's performance. Based on the analysis of a real online movie community, the results show that online community network structures can work as a predictor of movie performance. The results show that the betweenness centralities of the reviewer community are critical for the prediction of movie performance. However, degree centralities and closeness centralities do not influence movie performance. As future research topics, similar analyses are required for other product categories such as electronic goods and online content to generalize the study results.

• The Journal of the Korea Contents Association
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• v.16 no.3
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• pp.137-148
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• 2016

The purpose of this study is to examine viewers' intentions to watch movies after viewing online banner advertisements of movies, and verify the mediation effect of flow and association to research how the interactivity of movie banner advertisements influences viewers. For the study, trailer and advergame banners for three genres of movies were made, and an online survey was conducted with 146 adults. As a result, based on 5 hypothesis tests, the study enables us to conclude that the interactivity of the advergame banners results in a higher viewer intention of watching movies compared to trailer banners by inducing a flow experience among banner users not an association experience.

• Journal of Platform Technology
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• v.11 no.3
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• pp.45-55
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• 2023

This paper presents a model that supports decision-makers in the Korean film industry to maximize the success of online movies. To achieve this, we collected historical box office movies and clustered them into types to propose a model predicting each type's online box office performance. We considered various features to identify factors contributing to movie success and reduced feature dimensionality for computational efficiency. We systematically classified the movies into types and predicted each type's online box office performance while analyzing the contributing factors. We used automated machine learning (AutoML) techniques to automatically propose and select machine learning algorithms optimized for the problem, allowing for easy experimentation and selection of multiple algorithms. This approach is expected to provide a foundation for informed decision-making and contribute to better performance in the film industry.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.93-104
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• 2021

Most of the existing studies on the volume and valence of the eWOM (electronic word of mouth) about movies and box-office revenues were conducted using online actual data (secondary data) at Yahoo Movies, IMDB.com, Naver Movies, etc. However, it is difficult to grasp psychological variables from online actual data. Therefore, existing studies using online actual data could not identify the causal relationship among volume, valence and psychological variables. This study fills this gap in the literature. This study aims to examine the direct and indirect effects (i.e. mediating effect) of the volume and valence of online reviews about movies on purchase intention through review credibility as a mediator. We conducted a survey on the South Korean consumers and a structural equation modeling. The outcomes show that the total effects of both volume and valence are significant. In addition, volume has an indirect effect only (i.e. full mediating effect) on purchase intention through review credibility, but valence has both direct and indirect effects (i.e. partial mediating effect) on purchase intention through review credibility. The theoretical and practical implications for these results are presented.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.69-78
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• 2021

With technological development including digitization, movie demand and supply in digital online movie market are increasing. This study aims to explore demand concentration of the digital online movie market, which is characterized by product variety compared to cinemas. Major findings of the empirical analysis on the TV VOD data during the recent seven years(2013 ~ 2019) are as follows. First, the analysis on 1,137 titles reveals that movie demand of theatrical market is more concentrated than that of TV VOD. Second, absolute long tail index of TV VOD, measured by the download number of indie & artistic movies(niche product), is increasing as more such movies are released in the market. However, both relative long tail index, measured by the share of indie & artistic movie demand, and top-ranked movies' share do not show consistent increase or decrease trend. Third, regression analysis exhibits that the relationship between demand concentration and market size is insignificant for TV VOD market. This study might have usefulness in that it provides empirical evidence for the nature of the Korean digital online movie market.

• Asia Marketing Journal
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• v.15 no.1
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• pp.155-168
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• 2013

This study describes consumers' movie choices in conjunction with other group members and attempts to reassess the effect of the online word of mouth (WOM) source in a joint decision context. The tendency of many people to go to movies in groups has been mentioned in previous literature but there is no modeling research that studies movie choice from the group decision perspective. We found that ignoring the group movie-going perspective can result in a misunderstanding, especially underestimation of genre preference and the impact of the WOM variables. Most of the studies to measure online WOM effects were done at the aggregate level, and the role of online WOM variables(volume vs valence) is mixed in the literature. We postulate that group-level analysis might offer insight to resolve these mixed understanding of WOM effects in the literature. We implemented the study via a random effect model with group-level heterogeneity. Romance, drama, and action were selected as genre variables; valence and volume were selected as online WOM variables. A choice-based conjoint survey was used for data collection and the models was estimated via Bayesian MCMC method. The empirical results show that (i) both genre and online WOM are important variables when consumers choose movies, especially as group, and (ii) the WOM valence effect are amplified more than the volume effect does as individuals are engaged in group decision. This research contributes to the literature in several ways. First, we investigate movie choice from a group movie-going perspective that is more realistic and consistent with the market behavior. Secondly, the study sheds new light on the WOM effect. At group-level, both valence and volume significantly affect movie choices, which adds to the understanding of the role of online WOM in consumers' movie choice.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.995-1004
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• 2007

In this paper, we analyse online word-of-mouth and Korean box-office sales data based on kernel regression method. To do this, we consider the regression model with mixed-data and apply the least square cross-validation method proposed by Li and Racine (2004) to the model. We found the box-office sales can be explained by volume of online word-of-mouth and the characteristics of the movies.