An Empirical Analysis of the Impact of Pre-Release Movie Piracy on Box Office Revenue

被引:45
|
作者
Ma, Liye [1 ]
Montgomery, Alan L. [2 ,3 ]
Singh, Param Vir [2 ,3 ]
Smith, Michael D. [2 ,3 ]
机构
[1] Univ Maryland, Robert H Smith Sch Business, College Pk, MD 20742 USA
[2] Carnegie Mellon Univ, Tepper Sch Business, Pittsburgh, PA 15213 USA
[3] Carnegie Mellon Univ, Heinz Coll, Pittsburgh, PA 15213 USA
关键词
movies; box office revenue; piracy; forecasting; MOTION-PICTURES; INTERNET PIRACY; SALES; REVIEWS; MODEL;
D O I
10.1287/isre.2014.0530
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
Digital distribution channels raise many new challenges for managers in the media industry. This is particularly true for movie studios where high-value content can be stolen and released through illegitimate digital channels, even prior to the release of the movie in legal channels. In response to this potential threat, movie studios have spent millions of dollars to protect their content from unauthorized distribution throughout the lifecycle of films. They have focused their efforts on the pre-release period under the assumption that pre-release piracy could be particularly harmful for a movie's success. However, surprisingly, there has been little rigorous research to analyze whether, and how much, pre-release movie piracy diminishes legitimate sales. In this paper, we analyze this question using data collected from a unique Internet file-sharing site. We find that, on average, pre-release piracy causes a 19.1% decrease in revenue compared to piracy that occurs post-release. Our study contributes to the growing literature on piracy and digital media consumption by presenting evidence of the impact of Internet-based movie piracy on sales and by analyzing pre-release piracy, a setting that is distinct from much of the existing literature.
引用
收藏
页码:590 / 603
页数:14
相关论文
共 50 条
  • [21] A movie box office revenue prediction model based on deep multimodal features
    Madongo, Canaan Tinotenda
    Zhongjun, Tang
    MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 82 (21) : 31981 - 32009
  • [22] The Dynamics of eWOM and Business Outcomes: An Empirical Investigation of the Impact of Social Media on Box Office Revenue
    Kim, Kacy K.
    Yoon, Sukki
    CELEBRATING AMERICA'S PASTIMES: BASEBALL, HOT DOGS, APPLE PIE AND MARKETING?, 2016, : 441 - 441
  • [23] Using Movie Posters for Prediction of Box-Office Revenue with Deep Learning Approach
    Ozkan, Kemal
    Atak, Osman Nuri
    Isik, Sahin
    2018 26TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2018,
  • [24] Prediction of Gross Movie Revenue in the Turkish Box Office Using Machine Learning Techniques
    Gurbuz, Anil
    Bicer, Ezgi
    Kaya, Tolga
    INTELLIGENT AND FUZZY SYSTEMS: DIGITAL ACCELERATION AND THE NEW NORMAL, INFUS 2022, VOL 2, 2022, 505 : 86 - 92
  • [25] Review of the Impact of Prepaid App Platforms on Movie Box Office
    Li, Jinlei
    2017 4TH ICMIBI INTERNATIONAL CONFERENCE ON TRAINING, EDUCATION, AND MANAGEMENT (ICMIBI-TEM 2017), 2017, 83 : 217 - 222
  • [26] A Gaussian Copula Regression Model for Movie Box-office Revenue Prediction with Social Media
    Duan, Junwen
    Ding, Xiao
    Liu, Ting
    SOCIAL MEDIA PROCESSING, SMP 2015, 2015, 568 : 28 - 37
  • [27] The Differential Effects of Online Word-of-Mouth and Critics' Reviews on Pre-release Movie Evaluation
    Chakravarty, Anindita
    Liu, Yong
    Mazumdar, Tridib
    JOURNAL OF INTERACTIVE MARKETING, 2010, 24 (03) : 185 - 197
  • [28] The Impact of Movie Reviews on Box Office: Media Portfolios and the Intermediation of Genre
    Koschat, Martin A.
    JOURNAL OF MEDIA ECONOMICS, 2012, 25 (01) : 35 - 53
  • [29] Analysis and Comparision of Influence Factors of Movie Box Office In China
    Feng, Xi
    Wang, Xinran
    PROCEEDINGS OF 2018 IEEE 3RD ADVANCED INFORMATION TECHNOLOGY, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (IAEAC 2018), 2018, : 1273 - 1276
  • [30] Research on Movie Box Office Prediction Model With Conjoint Analysis
    Lu, Wei
    Xing, Ruben
    INTERNATIONAL JOURNAL OF INFORMATION SYSTEMS AND SUPPLY CHAIN MANAGEMENT, 2019, 12 (03) : 72 - 84