Pros vs. buzz- How Relevant Are Experts In The Internet Age? Evidence from the Motion Pictures Industry

Chintagunta, Gopinath and Venkatraman (2010, henceforth, CGV) show that once endogeneity correction is applied, the volume of user reviews, widely believed to have a significant impact on weekly revenues of movies, is not important but rather it is the average user rating, that affects box office revenues. In this paper, we extend the work by CGV by incorporating and examining the relative effects of expert reviews and user reviews. Using novel instruments for both expert reviews and user reviews, we show the following results: (1) In the absence of expert reviews, the valence of user reviews is significant while the volume of user reviews is not, thus confirming prior research. (2) When expert reviews are taken into account, they are more important user reviews. (3) In the presence of expert reviews, the valence of user reviews matters only when the volume of user reviews is high. (4) Expert reviews help platform releases, but user reviews do not. All in all, this paper demonstrates the essential effect of professional critical reviews even in the presence of ubiquitous user generated content.

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

[2]  M. Holbrook.  Popular Appeal versus Expert Judgments of Motion Pictures , 1999 .

[3]  L. J. Harrison‐Walker.  The Measurement of Word-of-Mouth Communication and an Investigation of Service Quality and Customer Commitment As Potential Antecedents , 2001 .

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

[5]  Kate Corby,et al.  Eldridge, Deborah B. (1997). Teacher Talk: Multicultural Lesson Plans for the Elementary Classroom. Needham Heights, MA : Allyn & Bacon. , 1998 .

[6]  Scott A. Neslin,et al.  The Development and Impact of Consumer Word of Mouth in New Product Diffusion , 2009 .

[7]  Mark B. Houston,et al.  Conceptualizing and Measuring the Monetary Value of Brand Extensions: The Case of Motion Pictures , 2009 .

[8]  V. Rao,et al.  What is Advertising Content Worth? Evidence from the Motion Pictures Industry , 2011 .

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

[10]  Diego Rinallo,et al.  Does Advertising Spending Influence Media Coverage of the Advertiser? , 2009 .

[11]  W. Walls,et al.  Does Hollywood Make Too Many R-Rated Movies?: Risk, Stochastic Dominance, and the Illusion of Expectation , 2000 .

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

[13]  Dina Mayzlin,et al.  Promotional Reviews: An Empirical Investigation of Online Review Manipulation , 2012 .

[14]  L. Ederington,et al.  Is a bond rating downgrade bad news, good news, or no news for stockholders? , 1993 .

[15]  S. Ravid,et al.  Choosing to Co-Finance - an Analysis of Project Specific Alliances in the Film Industry , 2005 .

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

[17]  W. Walls,et al.  Uncertainty in the Movie Industry: Does Star Power Reduce the Terror of the Box Office? , 1999 .

[18]  Harold L. Vogel.  Entertainment Industry Economics , 2020 .

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

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

[21]  Alexander W. Butler,et al.  Don't Believe the Hype: Local Media Slant, Local Advertising, and Firm Value , 2011 .

[22]  H. Denis Wu,et al.  Web Site Use and News Topic and Type , 2002 .

[23]  X. Zhang,et al.  Impact of Online Consumer Reviews on Sales: The Moderating Role of Product and Consumer Characteristics , 2010 .

[24]  W. Newey,et al.  Automatic Lag Selection in Covariance Matrix Estimation , 1994 .

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

[26]  C. Weinberg,et al.  Playoff payoff: Super Bowl advertising for movies , 2009 .

[27]  S. Abraham Ravid,et al.  Choosing to Cofinance: Analysis of Project-Specific Alliances in the Movie Industry , 2008 .

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

[29]  Edward B. Royzman,et al.  Negativity Bias, Negativity Dominance, and Contagion , 2001 .

[30]  Albert N. Greco.  The book publishing industry , 1996 .

[31]  Balachander Krishnamurthy,et al.  Flash crowds and denial of service attacks: characterization and implications for CDNs and web sites , 2002, WWW.

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

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

[34]  Pradeep Chintagunta,et al.  The Effects of Online User Reviews on Movie Box Office Performance: Accounting for Sequential Rollout and Aggregation Across Local Markets , 2010, Mark. Sci..

[35]  K. Bagwell.  The Economic Analysis of Advertising , 2005 .

[36]  Gianfranco Walsh,et al.  The differing roles of success drivers across sequential channels: An application to the motion picture industry , 2006 .

[37]  Suman Basuroy,et al.  Distributors and film critics: does it take two to Tango? , 2006 .

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

[39]  Richard E. Caves,et al.  Book Review , 2001 .

[40]  E. Rogers,et al.  Diffusion of innovations , 1964, Encyclopedia of Sport Management.