The paradox of (dis)trust in sponsorship disclosure: The characteristics and effects of sponsored online consumer reviews

Abstract Online consumer reviews (OCRs) have become one of the most influential persuasive messages with respect to purchase decisions. Knowing this, marketers have started incentivizing consumers to write reviews, hoping that they can increase the volume of positive reviews. However, little research exists on the content characteristics and effects of sponsored OCRs. This paper examines the different characteristics and effects of sponsored and organic OCRs, and the mechanisms by which consumers recognize and process these two types of reviews, using mixed methods in two studies. The findings of a text mining analysis (Study 1) suggest that sponsored reviews provide more elaborate and evaluative content; however, they are perceived as less helpful than organic reviews. The findings of a randomized experiment (Study 2) suggest that sponsorship disclosure increases suspicions about the reviewer's ulterior motives and decreases consumers' attitudes and purchase intentions when a review is positive. Sponsorship disclosure does not hurt attitudes or purchase intentions when a review is negative.

[1]  J. Rossiter,et al.  Tailor-made single-item measures of doubly concrete constructs , 2009 .

[2]  Y. Trope,et al.  Construal-level theory of psychological distance. , 2010, Psychological review.

[3]  J. Colliander,et al.  The blog and the bountiful: Exploring the effects of disguised product placement on blogs that are revealed by a third party , 2015 .

[4]  Peeter W. J. Verlegh,et al.  Receiver responses to rewarded referrals: the motive inferences framework , 2013 .

[5]  Maria Petrescu,et al.  Incentivized reviews: Promising the moon for a few stars , 2017 .

[6]  Yoori Hwang,et al.  "This is a sponsored blog post, but all opinions are my own": The effects of sponsorship disclosure on responses to sponsored blog posts , 2016, Comput. Hum. Behav..

[7]  Van Rooyen G-J,et al.  The review credibility of electronic word-of-mouth communication on e-commerce platforms , 2013 .

[8]  Elena García Barriocanal,et al.  Evaluating content quality and helpfulness of online product reviews: The interplay of review helpfulness vs. review content , 2012, Electron. Commer. Res. Appl..

[9]  I. Simonson,et al.  Mission (Largely) Accomplished: What's Next for Consumer BDT-JDM Researchers? , 2014 .

[10]  Jing Wang,et al.  Bonus, Disclosure, and Choice: What Motivates the Creation of High-Quality Paid Reviews? , 2012, ICIS.

[11]  Robert W. Shoemaker,et al.  The Effects of Free Sample Promotions on Incremental Brand Sales , 2004 .

[12]  C. Carr,et al.  The Effect of Disclosure of Third-Party Influence on an Opinion Leader's Credibility and Electronic Word of Mouth in Two-Step Flow , 2014 .

[13]  Eric R. Spangenberg,et al.  An exploratory study of word‐of‐mouth communication in a hierarchy of effects context , 1997 .

[14]  Shimi Naurin Ahmad.  Uncovering the paths to helpful reviews using fuzzy-set qualitative comparative analysis , 2017 .

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

[16]  R. Gunning.  The Fog Index After Twenty Years , 1969 .

[17]  H. Kelley.  Causal schemata and the attribution process , 1972 .

[18]  J. Kennett,et al.  What's the buzz? Undercover marketing and the corruption of friendship , 2008 .

[19]  Theodore L. Harris,et al.  The Literacy Dictionary: The Vocabulary of Reading and Writing , 1995 .

[20]  A. Gouldner.  THE NORM OF RECIPROCITY: A PRELIMINARY STATEMENT * , 1960 .

[21]  D. Toher,et al.  Why Welch’s test is Type I error robust , 2016 .

[22]  Snehasish Banerjee,et al.  Analyzing review efficacy on Amazon.com: Does the rich grow richer? , 2017, Comput. Hum. Behav..

[23]  G. Reeder.  Mindreading: Judgments About Intentionality and Motives in Dispositional Inference , 2009 .

[24]  Neil Salkind,et al.  Encyclopedia of research design , 2010 .

[25]  Nathaniel J. Evans,et al.  Going Native: Effects of Disclosure Position and Language on the Recognition and Evaluation of Online Native Advertising , 2016 .

[26]  J. Colliander.  Socially acceptable? : exploring consumer responses to marketing in social media , 2012 .

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

[28]  K. Ruyter,et al.  Unveiling What Is Written in the Stars: Analyzing Explicit, Implicit, and Discourse Patterns of Sentiment in Social Media , 2017 .

[29]  Peter Wright,et al.  Persuasion Knowledge , 2022 .

[30]  Wenqi Zhou,et al.  An Empirical Study of How Third-Party Websites Influence the Feedback Mechanism between Online Word-of-Mouth and Retail Sales , 2015 .

[31]  Amna Kirmani,et al.  Consumers' Use of Persuasion Knowledge: The Effects of Accessibility and Cognitive Capacity on Perceptions of an Influence Agent , 2000 .

[32]  S. C. Boerman,et al.  “This Post is Sponsored” Effects of Sponsorship Disclosure on Persuasion Knowledge and Electronic Word of Mouth in the Context of Facebook , 2017 .

[33]  Qing Cao,et al.  Exploring determinants of voting for the "helpfulness" of online user reviews: A text mining approach , 2011, Decis. Support Syst..

[34]  Ling Liu,et al.  Manipulation of online reviews: An analysis of ratings, readability, and sentiments , 2012, Decis. Support Syst..

[35]  Martin Wetzels,et al.  More than Words: The Influence of Affective Content and Linguistic Style Matches in Online Reviews on Conversion Rates , 2013 .

[36]  James W. Pennebaker,et al.  Linguistic Inquiry and Word Count (LIWC2007) , 2007 .

[37]  Ale Smidts,et al.  Interpersonal Relationships Moderate the Effect of Faces on Person Judgments , 2008 .

[38]  M. Forehand,et al.  When Is Honesty The Best Policy? The Effect of Stated Company Intent on Consumer Skepticism , 2002 .

[39]  Cynthia M. Webster,et al.  Word-Of-Mouth Communications: a Motivational Analysis , 1998 .

[40]  Paul A. Pavlou,et al.  Overcoming the J-shaped distribution of product reviews , 2009, CACM.

[41]  Peter C. Neijens,et al.  "Highly Recommended!" The Content Characteristics and Perceived Usefulness of Online Consumer Reviews , 2011, J. Comput. Mediat. Commun..

[42]  M. Coleman,et al.  A computer readability formula designed for machine scoring. , 1975 .

[43]  Richard E Petty,et al.  Thought confidence as a determinant of persuasion: the self-validation hypothesis. , 2002, Journal of personality and social psychology.

[44]  Kesha K. Coker,et al.  Buzzing with disclosure of social shopping rewards , 2015 .

[45]  Veronica Liljander,et al.  Young consumers' responses to suspected covert and overt blog marketing , 2015, Internet Res..

[46]  Snehasish Banerjee,et al.  Don't be deceived: Using linguistic analysis to learn how to discern online review authenticity , 2017, J. Assoc. Inf. Sci. Technol..

[47]  A. Stephen,et al.  When in Doubt, Elaborate? : How Elaboration on Uncertainty Influences the Persuasiveness of Consumer-Generated Product Reviews When Reviewers Are Incentivized , 2016 .

[48]  Indranil Bose,et al.  Whose online reviews to trust? Understanding reviewer trustworthiness and its impact on business , 2017, Decis. Support Syst..

[49]  E A Smith,et al.  Automated readability index. , 1967, AMRL-TR. Aerospace Medical Research Laboratories.

[50]  Sangwon Park,et al.  What makes a useful online review? Implication for travel product websites. , 2015 .

[51]  W. J. Carl.  The role of disclosure in organized word‐of‐mouth marketing programs , 2008 .

[52]  Juan Luis Nicolau,et al.  Asymmetric effects of online consumer reviews , 2015 .

[53]  Jan Breitsohl,et al.  E-business complaint management: perceptions and perspectives of online credibility , 2010, J. Enterp. Inf. Manag..

[54]  Wilmar B. Schaufeli,et al.  Reciprocity in Interpersonal Relationships: An Evolutionary Perspective on Its Importance for Health and Well-being , 1999 .

[55]  Weiguo Fan,et al.  Understanding the determinants of online review helpfulness: A meta-analytic investigation , 2017, Decis. Support Syst..

[56]  L. J. Abendroth,et al.  Honesty is the best policy: The effects of disclosure in word-of-mouth marketing , 2013 .

[57]  Robert B. Cialdini,et al.  Influence : how and why people agree to things , 1985 .

[58]  Mary Walker,et al.  Teen perceptions of disclosure in buzz marketing , 2007 .

[59]  Darren W. Dahl,et al.  Deliberative and Automatic Bases of Suspicion: Empirical Evidence of the Sinister Attribution Error , 2007 .

[60]  R. Petty,et al.  When credibility attacks: The reverse impact of source credibility on persuasion , 2006 .

[61]  Ching-man Au Yeung,et al.  "Popularity Effect" in User-Generated Content: Evidence from Online Product Reviews , 2014, Inf. Syst. Res..

[62]  Brandon Van Der Heide,et al.  Evaluating the Wisdom of Strangers: The Perceived Credibility of Online Consumer Reviews on Yelp , 2015, J. Comput. Mediat. Commun..

[63]  Su Jung Kim,et al.  Understanding and overcoming biases in online review systems , 2017, Decis. Support Syst..

[64]  Peeter W. J. Verlegh,et al.  Can Disclosures Lead Consumers to Resist Covert Persuasion? The Important Roles of Disclosure Timing and Type of Response , 2012 .

[65]  S. C. Boerman,et al.  Sponsorship Disclosure: Effects of Duration on Persuasion Knowledge and Brand Responses , 2012 .

[66]  Phillip E. Pfeifer,et al.  Marketing Metrics: The Manager's Guide to Measuring Marketing Performance , 2015 .

[67]  Shimi Naurin Ahmad,et al.  Analyzing electronic word of mouth: A social commerce construct , 2017, Int. J. Inf. Manag..

[68]  T. W. Leigh,et al.  Selling financial services: the effect of consumer product knowledge and salesperson commission on consumer suspicion and intentions , 2013 .

[69]  Soo-Min Kim,et al.  Automatically Assessing Review Helpfulness , 2006, EMNLP.

[70]  P. Chatterjee,et al.  Drivers of new product recommending and referral behaviour on social network sites , 2011 .