Self-Selection and Information Role of Online Product Reviews

By Xinxin Li, Lorin M. Hitt. 2008

1,174 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Marketing, Sociology and Political Science

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Citations in the corpus

Averaging Gone Wrong: Using Time-Aware Analyses to Better Understand Behavior (2016, background): “One useful way to understand the evolution of a community and its users is through time, as it provides a linear account of the growth (or decay) of overall activity, types of content, and social norms and structure.”
The role of electronic word of mouth in reducing information asymmetry: an empirical investigation of online hotel booking. (2018, background): “This is by no means a trivial question: while eWOM may accurately represent the preferences of consumers, it is potentially exposed to manipulation by sellers motivated to maximize profits at the expense of indulging in unethical behavior (Li & Hitt, 2008).”
Research Commentary - Too Big to Fail: Large Samples and the p-Value Problem (2013, methodology): “…a categorical variable can be studied by splitting the data into the separate categories and ﬁtting separate models (Asvanund et al. 2004, Forman et al. 2008, Gefen and Carmel 2008, Ghose 2009, Gordon et al. 2010, Li and Hitt 2008, Mithas and Lucas 2010, Overby and Jap 2009, Yao et al. 2009).”
Ratings lead you to the product, reviews help you clinch it? The mediating role of online review sentiments on product sales (2014, background): “While Chintagunta et al. [10] did not find significant effect of variance on sales, Clemons, Gao and Hitt [6] and Godes and Mayzlin [19] found the effect to be negative and significant.”
Sequential and Temporal Dynamics of Online Opinion (2012, background): “Recall that the theory of temporal dynamics of Li and Hitt (2008) is”
When and how Managers' Responses to Online Reviews Affect Subsequent Reviews (2018, background): “Moreover, the computation of ~rijt excludes the focal review. cijt and fijt are controls prescribed by Godes and Silva (2012) for sequential and temporal effects documented in the review dynamics literature (Godes and Silva 2012; Li and Hitt 2008; Moe and Trusov 2011).”
Disconfirmation Effect on Online Rating Behavior: A Dynamic Analysis (2014, background): “Li and Hitt (2008) argue that predominant declining trend of book ratings can be attributed to consumers' " self-selection " bias, meaning that early buyers have higher perceived quality and therefore tend to give higher ratings than do later buyers.”
Estimating Aggregate Consumer Preferences from Online Product Reviews (2010, positive): “Li and Hitt (2008), for instance, explore the presence and implications of self-selection biases using online book reviews.”
What We Know and Don't Know about Online Word-of-Mouth: A Review and Synthesis of the Literature (2014, background): “Some studies (Chevalier and Mayzlin 2006; Li and Hitt 2008) find a positive relationship between valence and product sales and the external influence propensity of online reviews.”
Manipulation of online reviews: An analysis of ratings, readability, and sentiments (2012, background): “Also, We realize that review ratings might not follow a random distribution due to the self-selection processes suggested by Li and Hitt [26].”
Online Reputation Management: Estimating the Impact of Management Responses on Consumer Reviews (2015, background): “Prior empirical studies (e.g. Li and Hitt (2008)) find a positive association between average rating and subsequent reviews.”
Do I Follow My Friends or the Crowd? Information Cascades in Online Movie Ratings (2015, positive): “Consistent with prior work on online book sales (Chevalier and Mayzlin 2006, Li and Hitt 2008), average user rating ( CROWDRA ) is positively correlated with sales ( π 1 =0.185, p 0.05).”