Impact of Star and Movie Buzz on Motion Picture Distribution and Box Office Revenue

This study contributes to research on the impact that consumer buzz has on movie distribution and box office success by examining the impact of buzz generated about the individual stars and about the movie itself. The results indicate that movie buzz is instrumental in boosting box office revenue throughout the theatrical release, not just in the later run, as has been suggested in previous studies. Star buzz can enhance box office receipts during the opening week and can contribute to the public's anticipation of the movie pre-release. However, early buzz can have a negative impact on revenue during subsequent weeks if the movie fails to resonate with the audiences. Model simulations reveal that, even for poorly received films, the overall impact of star buzz is positive because the initial revenue boost normally outweighs the later decline. Thus, this study empirically demonstrates the positive impact of star buzz on revenue, which helps shed light on the long-standing debate regarding the importance of star participation in the success of a movie.

[1]  Christopher M. Snyder,et al.  The Influence of Expert Reviews on Consumer Demand for Experience Goods: A Case Study of Movie Critics , 2005 .

[2]  David Godes,et al.  Using Online Conversations to Study Word-of-Mouth Communication , 2004 .

[3]  Yong Liu.  Word-of-Mouth for Movies: Its Dynamics and Impact on Box Office Revenue , 2006 .

[4]  S. Ravid.  Information, Blockbusters and Stars? A Study of the Film Industry , 1997 .

[5]  J. Eliashberg,et al.  MOVIEMOD: An Implementable Decision-Support System for Prerelease Market Evaluation of Motion Pictures , 2000 .

[6]  Tomás Bayón,et al.  The effect of word of mouth on services switching , 2004 .

[7]  Matthew K. O. Lee,et al.  The impact of electronic word-of-mouth: The adoption of online opinions in online customer communities , 2008, Internet Res..

[8]  Ekaterina V. Karniouchina.  Are Virtual Markets Efficient Predictors of New Product Success? The Case of the Hollywood Stock Exchange* , 2011 .

[9]  Chrysanthos Dellarocas,et al.  A Statistical Measure of a Population’s Propensity to Engage in Post-Purchase Online Word-of-Mouth , 2006 .

[10]  Chrysanthos Dellarocas,et al.  Exploring the value of online product reviews in forecasting sales: The case of motion pictures , 2007 .

[11]  J. Langlois,et al.  Effects of the "beauty is good" stereotype on children's information processing. , 2002, Journal of experimental child psychology.

[12]  D. Boorstin.  The image : a guide to pseudo-events in America , 1992 .

[13]  T. Hennig-Thurau,et al.  The Last Picture Show? Timing and Order of Movie Distribution Channels , 2007 .

[14]  De-Min Wu,et al.  Alternative Tests of Independence between Stochastic Regressors and Disturbances , 1973 .

[15]  Pradeep K. Chintagunta,et al.  A Bayesian Model to Forecast New Product Performance in Domestic and International Markets , 1999 .

[16]  Steven M. Shugan,et al.  Film Critics: Influencers or Predictors? , 1997 .

[17]  Gordon L. Patzer,et al.  The Power and Paradox of Physical Attractiveness , 2006 .

[18]  J. Eliashberg,et al.  Demand and Supply Dynamics for Sequentially Released Products in International Markets: The Case of Motion Pictures , 2003 .

[19]  Katherine N. Lemon,et al.  Customer Engagement Behavior: Theoretical Foundations and Research Directions , 2010 .

[20]  Steven Albert.  Movie Stars and the Distribution of Financially Successful Films in the Motion Picture Industry , 1998 .

[21]  C. McGinn.  The Power of Movies: How Screen and Mind Interact , 2005 .

[22]  Debabrata Talukdar,et al.  An Empirical Investigation of Signaling in the Motion Picture Industry , 2006 .

[23]  Emanuel Rosen,et al.  The Anatomy of Buzz: How to Create Word of Mouth Marketing , 2000 .

[24]  J. Eliashberg,et al.  A Parsimonious Model for Forecasting Gross Box-Office Revenues of Motion Pictures , 1996 .

[25]  Dennis Huisman,et al.  Demand-Driven Scheduling of Movies in a Multiplex , 2007 .

[26]  Greg Thomas.  Building the buzz in the hive mind , 2004 .

[27]  Barry Litman.  Predicting Success of Theatrical Movies: An Empirical Study , 1983 .

[28]  Liran Einav,et al.  Seasonality in the U.S. motion picture industry , 2007 .

[29]  E. Rosen.  The Anatomy of Buzz , 2000 .

[30]  B. Austin.  Critics’ and Consumers’ Evaluations of Motion Pictures , 1983 .

[31]  J. Eliashberg,et al.  The Motion Picture Industry: Critical Issues in Practice, Current Research, and New Research Directions , 2006 .

[32]  Jehoshua Eliashberg,et al.  The consumers' rent vs. buy decision in the rentailer , 2009 .

[33]  Morris B. Holbrook,et al.  The Role of Ordinary Evaluations in the Market for Popular Culture: Do Consumers Have “Good Taste”? , 2005 .

[34]  Mark B. Houston,et al.  Can good marketing carry a bad product? Evidence from the motion picture industry , 2006 .

[35]  Suman Basuroy,et al.  How Critical are Critical Reviews? The Box Office Effects of Film Critics, Star Power, and Budgets , 2003 .

[36]  C. Edward Fee,et al.  The Costs of Outside Equity Control: Evidence from Motion Picture Financing Decisions , 1998 .

[37]  Suman Basuroy,et al.  Managerial Objectives, the R-Rating Puzzle and the Production of Violent Films , 2003 .

[38]  R. Frank,et al.  The Winner-Take-All Society , 1995 .

[39]  Andrew Whinston,et al.  The Dynamics of Online Word-of-Mouth and Product Sales: An Empirical Investigation of the Movie Industry , 2008 .

[40]  Xavier Drèze,et al.  Modeling Movie Life Cycles and Market Share , 2005 .

[41]  R. Streitmatter.  Sex Sells!: The Media's Journey From Repression To Obsession , 2004 .