The Power of Negative Reviews on a Freemium Platform: An Event Study of Pay-for-Negative Regulation

The perceived value of online negative reviews is increasingly outweighing those of positive reviews. Negative information is treated as more diagnostic and persuasive than positive information of similar intensity (i.e. negativity bias). This raises regulatory challenges how to balance the effects of positive and negative reviews. Few studies have explored the effects of regulatory interventions that mobilize the power of negative reviews beyond detection and penalize fake reviews. This study examines a unique regulatory measure—pay-for-negative—in the context of a user-generated content platform. Specifically, we focus on whether the voluntary contributions of an online books platform can benefit from regulating negative reviews. Our findings suggest that when pay-for-negative regulation occurs, negative review valence has a surprisingly positive effect on voluntary contributions. Applying accessibility-diagnosticity theory, we conclude that pay-for-negative regulations lead to increases in voluntary contributions in both volume and likelihood as they increase the diagnosticity and awareness of negative reviews.

[1]  P. K. Kannan,et al.  Selling the Premium in Freemium , 2018, Journal of Marketing.

[2]  Brian I. Spaid,et al.  Tell it like it is: The effects of differing responses to negative online reviews , 2018, Psychology & Marketing.

[3]  Sinan Aral,et al.  The spread of true and false news online , 2018, Science.

[4]  Alina Sorescu,et al.  Event study methodology in the marketing literature: an overview , 2017 .

[5]  George Valkanas,et al.  The Impact of Fake Reviews on Online Visibility: A Vulnerability Assessment of the Hotel Industry , 2016, Inf. Syst. Res..

[6]  Patrick De Pelsmacker,et al.  A Meta-analytic Investigation of the Role of Valence in Online Reviews , 2015 .

[7]  David C. Yen,et al.  A study of factors that contribute to online review helpfulness , 2015, Comput. Hum. Behav..

[8]  Saad A. Alhoqail,et al.  How Online Product Reviews Affect Retail Sales: A Meta-analysis , 2014 .

[9]  Beibei Li,et al.  Examining the Impact of Ranking on Consumer Behavior and Search Engine Revenue , 2013, Manag. Sci..

[10]  Jianqing Chen,et al.  Product Reviews : Implications for Retailers and Competing Manufacturers , 2013 .

[11]  Philip Fei Wu In Search of Negativity Bias: An Empirical Study of Perceived Helpfulness of Online Reviews , 2013 .

[12]  Breathe investigators Rationale and design: BREATHE registry--I Brazilian Registry of Heart Failure. , 2013, Arquivos brasileiros de cardiologia.

[13]  Arjun Mukherjee,et al.  Fake Review Detection: Classification and Analysis of Real and Pseudo Reviews , 2013 .

[14]  John G. Lynch,et al.  Spotlights, Floodlights, and the Magic Number Zero: Simple Effects Tests in Moderated Regression , 2012 .

[15]  Arjun Mukherjee,et al.  Spotting fake reviewer groups in consumer reviews , 2012, WWW.

[16]  Baba Shiv,et al.  When Blemishing Leads to Blossoming: The Positive Effect of Negative Information , 2012 .

[17]  Jun Yang,et al.  Experiential goods with network externalities effects: An empirical study of online rating system , 2010 .

[18]  Jonah Berger,et al.  Positive Effects of Negative Publicity: When Negative Reviews Increase Sales , 2009, Mark. Sci..

[19]  David Schuff,et al.  What Makes a Helpful Review? A Study of Customer Reviews on Amazon.com , 2010 .

[20]  Mira Lee,et al.  Effects of Valence and Extremity of eWOM on Attitude toward the Brand and Website , 2009 .

[21]  C. Anderson,et al.  Free: The Future of a Radical Price , 2009 .

[22]  Michael Workman,et al.  Cognitive Load Research and Semantic Apprehension of Graphical Linguistics , 2007, USAB.

[23]  Dwayne D. Gremler,et al.  Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulate themselves on the Internet? , 2004 .

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

[25]  J. Chiou,et al.  Should a company have message boards on its Web sites? , 2003 .

[26]  P. Chatterjee,et al.  Online Reviews: Do Consumers Use Them? , 2006 .

[27]  Rohini Ahluwalia,et al.  The Effects of Extensions on the Family Brand Name: An Accessibility‐Diagnosticity Perspective , 2000 .

[28]  F. Buttle Word of mouth: understanding and managing referral marketing , 1998 .

[29]  R. Petty,et al.  The gradual threshold model of ambivalence: relating the positive and negative bases of attitudes to subjective ambivalence. , 1996, Journal of personality and social psychology.

[30]  Jagdip Singh,et al.  Exploring the Effects of Consumers′ Dissatisfaction Level on Complaint Behaviours , 1991 .

[31]  P. Herr,et al.  Effects of Word-of-Mouth and Product-Attribute Information on Persuasion: An Accessibility-Diagnosticity Perspective , 1991 .

[32]  Donal E. Carlston,et al.  Negativity and extremity biases in impression formation: A review of explanations. , 1989 .

[33]  Jack M. Feldman,et al.  Self-generated validity and other effects of measurement on belief, attitude, intention, and behavior. , 1988 .

[34]  E. E. Jones Attribution: Perceiving the Causes of Behavior , 1987 .

[35]  Alice M. Tybout,et al.  Using Information Processing Theory to Design Marketing Strategies , 1981 .

[36]  Susan T. Fiske,et al.  Attention and weight in person perception: The impact of negative and extreme behavior. , 1980 .

[37]  J. Arndt Role of Product-Related Conversations in the Diffusion of a New Product , 1967 .