Influence of Movie Success Factors Including Holdbacks in Box Office and VOD Market

2021 ◽  
Vol 38 (2) ◽  
pp. 47-61
Author(s):  
Hoon-Young Koo ◽  
Heejung Lee ◽  
Geun-Cheol Lee
Keyword(s):  
Success Factors ◽  
Box Office ◽  
Movie Success

scholarly journals Conquering the Box Office: Factors Influencing Success of International Movies in Russia

2018 ◽  
Vol 17 (4) ◽  
pp. 245-266 ◽  
Author(s):  
Sophia Gaenssle ◽  
Oliver Budzinski ◽  
Daria Astakhova
Keyword(s):  
Success Factors ◽  
Positive Influence ◽  
Negative Effects ◽  
Box Office ◽  
Factors Influencing ◽  
The Us ◽  
Specific Factors ◽  
Different Cultures ◽  
Local Release ◽  
Movie Success

Abstract This paper empirically examines factors influencing box office success of international movies in Russia between 2012 and 2016. It adds to existing research on national movie markets, by highlighting the relevance of differences in culture, institutions, language, and consumption habits for movie success. Three groups of success factors are distinguished: distribution related (e.g. budget, franchise), brand and star effects (e.g. top actors or directors), and evaluation sources (e.g. critics and audience rating). We add novel region-specific variables like seasonality, time span between the world and local release, attendance of international stars at Russian movie premieres, and title adaptation to Russian culture. The results indicate that budget, franchise, employment of popular actors and directors, electronic word of mouth and audience ratings exert a significantly positive influence on Russian box office success. However, we find significantly negative effects for international critics and, interestingly, the adaption of movie titles. The main contributions of our study are (i) success factors vary between countries with different cultures, (ii) region-specific factors matter, and consequently (iii) results from one market (e.g. the US) cannot easily be generalised.

The role of place and identity as core contributing success factors in Jayan Moodley’s Keeping up with the Kandasamys and Kandasamys: The Wedding

2020 ◽  
Vol 12 (2-3) ◽  
pp. 229-246
Author(s):  
Sogen Moodley ◽  
Arushani Govender
Keyword(s):  
South African ◽  
Critical Analysis ◽  
Success Factors ◽  
Place Identity ◽  
Community Members ◽  
African Identity ◽  
South Africans ◽  
Box Office ◽  
Place And Identity

Keeping up with the Kandasamys (Moodley 2017), a family comedy co-written and directed by Jayan Moodley, was the first cinematic feature to be set in the post-apartheid Indian township of Chatsworth, Durban and generated R16.3 million at the box office. The film delves into the matriarchal rivalry of neighbouring families while showcasing the unique Chatsworth subculture. This box office success prompted the release of the sequel Kandasamys: The Wedding (Moodley 2019), which broke its own sales record, earning R18.9 million. As filmmakers who were intimately involved in the production of the sequel, and who engaged with viewers and community members, we provide a critical analysis, reflecting on why the films attracted large audiences and galvanized an outburst of fandom. This article postulates that Indian South African audiences identified with the authentic portrayal of the nuances of every-day life in Chatsworth, resulting in feelings of visibility and nostalgia. In attempting to explain the phenomenal support from these audiences, the authors examine theories of place identity and literature on Indian South African identity, inferring that the intersection of place, and the representation of Indian South Africans in the features, is significant to the films’ success.

scholarly journals Movie Success Rate Prediction Using Robust Classifier

2019 ◽  
Vol 8 (6) ◽  
pp. 3517-3522
Keyword(s):  
Machine Learning ◽  
Success Rate ◽  
Film Industry ◽  
Machine Learning Algorithms ◽  
Running Time ◽  
Box Office ◽  
Knn Classifier ◽  
Nearest Neighbours ◽  
Adaboost Classifier ◽  
Movie Success

Film industry is a multi-billion-dollar industry where each movie earns over billions of dollar. Predicting the success of the movie is a difficult task because the success rate is influenced by various factors like running time, actor, actress, genre etc. In this paper a detailed study of machine learning algorithms such as Adaboost, SVM, and K-Nearest Neighbours (KNN) were done and was implemented on IMDB dataset for predicting box office. Based on the results, Adaboost classifier gives better performance compared to SVM and KNN classifier algorithms

Investigating the Effect of eWOM in Movie Box Office Success Through an Aspect-Based Approach

2018 ◽  
Vol 5 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Saurav Mohanty ◽  
Nicolle Clements ◽  
Vipul Gupta
Keyword(s):  
Sentiment Analysis ◽  
Word Of Mouth ◽  
Strong Dependence ◽  
Domestic Market ◽  
User Reviews ◽  
Box Office ◽  
Sentiment Score ◽  
Negative Sentiment ◽  
Movie Success ◽  
The U.S

This study examines the influence of Electronic Word of Mouth (eWOM) on the box office revenue generation of movies in the U.S domestic market using the technique of Aspect-Based Sentiment Analysis (ABSA) and aspect identification. The analysis was conducted on the sentiment score and frequency of five movie aspects from the user reviews collected from high grossing 2014 movies. This study revealed a significant dependence on the aspect-based sentiment frequency of the movie's Story aspect. Surprisingly, the data also showed a strong dependence of movie success on the negative sentiment frequency on the Casting aspect. The findings of the study suggest that the eWOM present in online movie reviews can be used to predict the performance of a movie at the box office by monitoring the aspect's frequency of sentiment, which can be referred to as a metric of the online “buzz” of the movie.

Is There a Method to Madness? Predicting Success of Bollywood Movies

2021 ◽  
Vol 15 (2) ◽  
Author(s):  
Sumod S D ◽  
Prashant Premkumar ◽  
Krishnan Jeesha ◽  
Shovan Chowdhury Chowdhury
Keyword(s):  
Logistic Regression ◽  
Multiple Regression ◽  
Predictive Models ◽  
Success Factors ◽  
Original Data ◽  
Data Set ◽  
Box Office ◽  
Indian Context ◽  
Predicting Success ◽  
Parsimonious Model

The objective of the study is to develop a parsimonious model to predict the box office success of a Bollywood movie before its release. A movie is considered successful if the revenue generated is greater than its budget, in other words, a Revenue to Budget Ratio (RBR) greater than 1. An original data set of 1698 Hindi movies released across a period of 13 years is used to identify the success factors of a movie in the Indian context. Predictive models are developed using traditional methodologies like multiple regression and logistic regression, as well as, contemporary approaches like regression trees and classification trees. The results highlight a unique mix of elements that a producer should consider to ensure the success of a movie in the highly competitive Indian movie market.

scholarly journals Movie Success Prediction Using Data Mining

2021 ◽  
Vol 4 (2) ◽  
pp. 22-30
Author(s):  
Olubukola D.A. ◽  
Stephen O.M. ◽  
Funmilayo A.K. ◽  
Ayokunle O. ◽  
Oyebola A. ◽  
...  
Keyword(s):  
Data Mining ◽  
Machine Learning Algorithms ◽  
Success Prediction ◽  
Movie Industry ◽  
Release Date ◽  
Data Mining Techniques ◽  
Box Office ◽  
Public Consumption ◽  
Using Data ◽  
Movie Success

The movie industry is arguably one of the biggest entertainment sectors. Nollywood, the Nigerian movie industry produces tons of movies for public consumption, but only a few make it to box-office or end up becoming blockbusters. The introduction of movie success prediction can play an important role in the industry not only to predict movie success but to help directors and producers make better decisions for the purpose of profit. This study proposes a movie prediction model that applies data mining techniques and machine learning algorithms to predict the success or failure of an upcoming movie (based on predefined parameters). The parameters needed for predicting the success or failure of a movie include dataset needed for the process of data mining such as the historical data of actors, actresses, writers, directors, marketing and production budget, audience, location, release date, and competing movies on same release date. This model also helps movie consumers to determine a blockbuster, hit, success rating and quality of upcoming movies before deciding on a movie ticket. The data mining techniques was applied to Internet Movie Database MetaData which was initially passed through cleaning and integration process.

scholarly journals Analyzing and Predicting The Success of Box Office Collection of a Movie Using Machine Learning

2021 ◽  
pp. 325-331
Author(s):  
Sanyam Jatale ◽  
Rohan Moze ◽  
Varsha Khandekar ◽  
Shubham Jain ◽  
Sanket Mokate
Keyword(s):  
Machine Learning ◽  
Social Networking ◽  
Motion Picture Industry ◽  
Learning Tools ◽  
Social Bookmarking ◽  
Business Decisions ◽  
Box Office ◽  
The World ◽  
Increased Activity ◽  
Movie Success

Our day-to-day life has always been influenced by what people think. Ideas and opinions of others have always affected our own opinions. The explosion of Web 2.0 has led to increased activity in Podcasting, Blogging, Tagging, Contributing to RSS, Social Bookmarking, and Social Networking. The motion picture industry is a multi-billion-dollar business, and there is a massive amount of data related to movies are available over the internet. The framework will foresee an estimated achievement pace of a film dependent on its productivity by dissecting verifiable information from various sources like IMDB, Rotten Tomato, Box Office Mojo and Metacritic. Utilizing distinctive AI calculations, Machine Learning Tools, and different procedures the framework will foresee a film box office benefits depending on certain highlights like caste, genre, budget, actors, and many more features. The number of movies produced in the world is growing at an exponential rate and success rate of movie is of utmost importance since billions of dollars are invested in the making of each of these movies. In such a scenario, prior knowledge about the success or failure of a particular movie and what factor affect the movie success will benefit the production houses since these predictions will give them a fair idea of how to go about with the advertising and campaigning, which itself is an expensive affair altogether. Thus, predicting the box-office will help this growing industry experts to imply some important business decisions in order to make the upcoming movie more successful.

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