ANALYZING THE SUCCESS FACTORS OF MOVIE BOX-OFFICE USING CUSTOMER REVIEWS WITH TOPIC ANALYSIS

2020 ◽  
pp. 65-70
Author(s):  
Zeng Jing ◽  
Ho-Yeon Park ◽  
Dong-Ho Kim ◽  
Kyoung-Jae Kim
2019 ◽  
Vol 11 (1) ◽  
pp. 87-101 ◽  
Author(s):  
Shuai Yang ◽  
Tao Li ◽  
Sixing Chen ◽  
Bin Li

Purpose People generally believe that business with negative word-of-mouth, such as negative customer reviews can hardly have good sales. But a number of intriguing examples seem to contradict such beliefs. Academic has so far begun to explore the possible positive effect of negative customer reviews, but without unfolding its underlying mechanism. This paper proposes a mechanism through which the variance of customer reviews moderates the effect of negative reviews on sales. Design/methodology/approach This study takes a multi-method approach in explaining the phenomenon, including an empirical analysis using secondary data from a movie review website and a movie box office website and a subsequent experimental study in a controlled experiment. Findings The findings of the study show that the effect of negative customer reviews on product sales is positive when the variance of customer reviews is large. Moreover, customers’ motivation to learn fully mediates the moderating effect of review variance on valence. Practical implications The findings provide vital managerial implications and suggest that managers should realize the important role of the review distribution. Originality/value This study mainly contributes to research on the negativity bias by identifying an important unexplored moderator and mediator and thus explains why negative customer review increases movie sales.


2020 ◽  
Vol 12 (2-3) ◽  
pp. 229-246
Author(s):  
Sogen Moodley ◽  
Arushani Govender

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.


2021 ◽  
Vol 15 (2) ◽  
Author(s):  
Sumod S D ◽  
Prashant Premkumar ◽  
Krishnan Jeesha ◽  
Shovan Chowdhury Chowdhury

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.


Author(s):  
Xiaozhong Lyu ◽  
Cuiqing Jiang ◽  
Yong Ding ◽  
Zhao Wang ◽  
Yao Liu

The accuracy of sales prediction models based on the big data of online word-of-mouth (eWOM) is still not satisfied. We argue that eWOM contains heat and sentiments of different product dimensions, which can improve the accuracy of these models. In this paper, we propose a dynamic topic analysis (DTA) framework in order to extract heat and sentiments of product dimensions from the big data of eWOM. Finally, we propose an autoregressive-heat-sentiment (ARHS) model, which integrates heat and sentiments of dimensions into the baseline predictive model. The empirical study in movie industry confirms that heat and sentiments of dimensions can improve the accuracy of sales prediction model. ARHS model is better for movie box-office revenue prediction than other models.


2018 ◽  
Vol 17 (4) ◽  
pp. 245-266 ◽  
Author(s):  
Sophia Gaenssle ◽  
Oliver Budzinski ◽  
Daria Astakhova

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.


2021 ◽  
Vol 38 (2) ◽  
pp. 47-61
Author(s):  
Hoon-Young Koo ◽  
Heejung Lee ◽  
Geun-Cheol Lee

Author(s):  
Young-mee Hwang ◽  
Jin-tae Park ◽  
Il-young Moon ◽  
Kwang-sun Kim ◽  
Oh-young Kwon
Keyword(s):  
Big Data ◽  

Author(s):  
Xiaozhong Lyu ◽  
Cuiqing Jiang ◽  
Yong Ding ◽  
Zhao Wang ◽  
Yao Liu

The accuracy of sales prediction models based on the big data of online word-of-mouth (eWOM) is still not satisfied. We argue that eWOM contains heat and sentiments of different product dimensions, which can improve the accuracy of these models. In this paper, we propose a dynamic topic analysis (DTA) framework in order to extract heat and sentiments of product dimensions from the big data of eWOM. Finally, we propose an autoregressive-heat-sentiment (ARHS) model, which integrates heat and sentiments of dimensions into the baseline predictive model. The empirical study in movie industry confirms that heat and sentiments of dimensions can improve the accuracy of sales prediction model. ARHS model is better for movie box-office revenue prediction than other models.


2012 ◽  
Vol 2 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Michaela Heese

Members of the Civil Air Navigation Services Organisation have committed themselves to measure and improve safety culture within their organizations by 2013 ( CANSO, 2010 ). This paper attempts to offer support to air navigation service providers that have already implemented a standardized safety culture survey approach, in the process of transforming their safety culture based on existing survey results. First, an overview of the state of the art with respect to safety culture is presented. Then the application of the CANSO safety culture model from theory into practice is demonstrated based on four selected case studies. Finally, a summary of practical examples for driving safety culture change is provided, and critical success factors supporting the safety culture transformation process are discussed.


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