An Investigation of Free Product Sampling and Rating Bias in E-Commerce

Free product sampling has increasingly become a popular promotional strategy, and served as a new mechanism of product review generation in e-commerce. We empirically analyze how a product’s engagement in free product sampling affects the product’s review rating, and also examine important contingent factors of product pricing and product popularity. Using a rich data set from Taobao.com and multiple identification strategies and estimation methods, we find that engaging in free product sampling increases product rating by 1.1%. We argue that it is consumers’ reciprocal behavior of giving higher ratings as a return to retailers’ beneficial actions that causes rating bias. We further find that the bias would be larger with higher original price, but smaller with higher price discount and higher product popularity. Our empirical findings provide important contributions to the literature on product sampling and word-of-mouth, and offer critical managerial implications to online retailers, rating system designers, and consumers.

[1]  Lorin M. Hitt,et al.  Self Selection and Information Role of Online Product Reviews , 2007, Inf. Syst. Res..

[2]  Werner Antweiler,et al.  Is All that Talk Just Noise? The Information Content of Internet Stock Message Boards , 2001 .

[3]  D. J. Wu,et al.  Economics of Free Under Perpetual Licensing: Implications for the Software Industry , 2014, Inf. Syst. Res..

[4]  K. Goh,et al.  Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User- and Marketer-Generated Content , 2013 .

[5]  Ann E. Schlosser Posting versus Lurking: Communicating in a Multiple Audience Context , 2005 .

[6]  Wendy W. Moe,et al.  Measuring the Value of Social Dynamics in Online Product Ratings Forums , 2010 .

[7]  David Zilberman,et al.  Learning and Forgetting: Modeling Optimal Product Sampling Over Time , 2001, Manag. Sci..

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

[9]  R. Oliver Effect of expectation and disconfirmation on postexposure product evaluations: An alternative interpretation. , 1977 .

[10]  E. Fehr,et al.  Fairness and Retaliation: The Economics of Reciprocity , 2000, SSRN Electronic Journal.

[11]  David Godes,et al.  Sequential and Temporal Dynamics of Online Opinion , 2012, Mark. Sci..

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

[13]  Lorin M. Hitt,et al.  Price Effects in Online Product Reviews: An Analytical Model and Empirical Analysis , 2010, MIS Q..

[14]  David Godes,et al.  Firm-Created Word-of-Mouth Communication: Evidence from a Field Test , 2009, Mark. Sci..

[15]  Mike Y. Chen,et al.  Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web , 2001 .

[16]  Dipayan Biswas,et al.  How the Order of Sampled Experiential Products Affects Choice , 2010 .

[17]  Chrysanthos Dellarocas,et al.  The Digitization of Word-of-Mouth: Promise and Challenges of Online Feedback Mechanisms , 2003, Manag. Sci..

[18]  Hsing Kenneth Cheng,et al.  Optimal Software Free Trial Strategy: The Impact of Network Externalities and Consumer Uncertainty , 2012, Inf. Syst. Res..

[19]  Bin Gu,et al.  Do online reviews matter? - An empirical investigation of panel data , 2008, Decis. Support Syst..

[20]  Zhijie Lin,et al.  The Paradoxes of Word of Mouth in Electronic Commerce , 2015, J. Manag. Inf. Syst..

[21]  Lauren I. Labrecque,et al.  Making Choices While Smelling, Tasting, and Listening: The Role of Sensory (Dis)similarity When Sequentially Sampling Products , 2014 .

[22]  Chong Wang,et al.  Socially Nudged: A Quasi-Experimental Study of Friends' Social Influence in Online Product Ratings , 2018, Inf. Syst. Res..

[23]  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..

[24]  P. Austin American Journal of Epidemiology Practice of Epidemiology Statistical Criteria for Selecting the Optimal Number of Untreated Subjects Matched to Each Treated Subject When Using Many-to-one Matching on the Propensity Score , 2022 .

[25]  S. Pokharel Wisdom of Crowds: The Value of Stock Opinions Transmitted through Social Media , 2014 .

[26]  Shivendu Shivendu,et al.  Managing Piracy: Pricing and Sampling Strategies for Digital Experience Goods in Vertically Segmented Markets , 2003, Inf. Syst. Res..

[27]  Gerard J. Tellis,et al.  Does Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance , 2011, Mark. Sci..

[28]  Zhijie Lin,et al.  An empirical investigation of user and system recommendations in e-commerce , 2014, Decis. Support Syst..

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

[30]  Bin Gu,et al.  Research Note - The Impact of External Word-of-Mouth Sources on Retailer Sales of High-Involvement Products , 2012, Inf. Syst. Res..

[31]  Anindya Ghose,et al.  Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets , 2008, Inf. Syst. Res..

[32]  Lawrence J. Marks,et al.  The Use of Product Sampling and Advertising: Effects of Sequence of Exposure and Degree of Advertising Claim Exaggeration on Consumers’ Belief Strength, Belief Confidence, and Attitudes , 1988 .

[33]  Petra E. Todd,et al.  Matching As An Econometric Evaluation Estimator , 1998 .

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

[35]  Dina Mayzlin,et al.  1 PROMOTIONAL CHAT ON THE INTERNET * , 2001 .

[36]  Yubo Chen,et al.  Online Consumer Review: Word-of-Mouth as a New Element of Marketing Communication Mix , 2004, Manag. Sci..

[37]  S. Nowlis,et al.  The Effect of Distractions While Tasting a Food Sample: The Interplay of Informational and Affective Components in Subsequent Choice , 2004 .

[38]  Stephen M. Nowlis,et al.  The Influence of Consumer Distractions on the Effectiveness of Food-Sampling Programs , 2005 .

[39]  Stephen M. Nowlis,et al.  A Bite to Whet the Reward Appetite: The Influence of Sampling on Reward-Seeking Behaviors , 2008 .

[40]  E. Clemons,et al.  When Online Reviews Meet Hyperdifferentiation: A Study of the Craft Beer Industry , 2006 .

[41]  Yong Tan,et al.  Effects of Different Types of Free Trials and Ratings in Sampling of Consumer Software: An Empirical Study , 2013, J. Manag. Inf. Syst..

[42]  D. Rubin,et al.  The central role of the propensity score in observational studies for causal effects , 1983 .

[43]  Fang Wu,et al.  How Public Opinion Forms , 2008, WINE.

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

[45]  R. Oliver A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions , 1980 .

[46]  R. Cialdini Influence: The Psychology of Persuasion , 1993 .

[47]  Angelika Dimoka,et al.  The Nature and Role of Feedback Text Comments in Online Marketplaces: Implications for Trust Building, Price Premiums, and Seller Differentiation , 2006, Inf. Syst. Res..