Measuring the Value of Social Dynamics in Online Product Ratings Forums

By Wendy W. Moe, Michael Trusov. 2010

705 citations recorded by the source corpus.

Subfields: Marketing, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/158fc478b3b9be5a205a880256579fdb15a7160f

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Citations in the corpus

Digital marketing: A framework, review and research agenda (2017, neutral): “Moe and Trusov (2011) examined consumer product ratings and developed a model to tease apart the variation in ratings due to personal product experience from variation due to social influences, which allowed them to quantify the impact of social dynamics on sales. There is an evolving stream of rese”
eWOM: Extant Research Review and Future Research Avenues (2016, background): “In contrast, Moe and Trusov (2011) show that although ratings behaviour is significantly influenced by previously posted ratings and can directly improve sales, the effects are relatively shortlived once indirect effects of social dynamic and idiosyncratic errors are considered.”
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).”
How credibility affects eWOM reading: The influences of expertise, trustworthiness, and similarity on utilitarian and social functions (2014, background): “…results confirm that product-related eWOM influences attitudes, intentions, and behavior, including both online and offline purchases (Sénécal and Nantel 2004; Chevalier and Mayzlin 2006; Huang and Chen 2006; Amblee and Bui 2008; Hu, Liu, and Zhang 2008; Li and Hitt 2008; Moe and Trusov 2011).”
Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User- and Marketer-Generated Content (2013, neutral): “2006) and beauty products (Moe and Trusov 2011).”
Online Consumer Review Factors Affecting Offline Hotel Popularity: Evidence from Tripadvisor (2016, background): “A burgeoning academic body of literature has emerged to study how online consumer reviews affect offline business performance (Moe & Trusov, 2011; Xie et al., 2014).”
Decision Difficulty in the Age of Consumer Empowerment (2014, background): “However, an average rating based on a large number of reviewers is not necessarily a reliable signal, as reviewer ratings are not independent and social dynamics lead initial reviewer ratings to influence subsequent reviewer ratings (Moe & Trusov, 2011; Sridhar & Srinivasan, 2012).”
Does Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance (2012, background): “…studies examine the interaction among consumers or the impact of UGC on demand/sales (e.g., Dellarocas et al. 2007, Dhar and Chang 2009, Liu 2006, Chintagunta et al. 2010, Chevalier and Mayzlin 2006, Trusov et al. 2009, Moe and Trusov 2011) but not the impact of UGC on stock market performance.”
Social Media Metrics — A Framework and Guidelines for Managing Social Media (2013, background): “Additionally, social media metrics and subsequently dashboards would need to cover the states, dynamics (e.g., Moe and Trusov 2011; Tirunillai and Tellis 2012), and heterogeneity (e.g., Sun 2012; Zhang, Li, and Chen 2012) in all three aspects.”
App Popularity: Where in the World are Consumers Most Sensitive to Price and User Ratings? (2018, background): “S. settings in the sales elasticity of user reviews, which are a key source of information for many customers (Chevalier and Mayzlin 2006; Moe and Trusov 2011).”
What Drives Immediate and Ongoing Word of Mouth? (2011, methodology): “Similarly, product ratings and reviews have been shown to increase sales in several contexts (Chevalier and Mayzlin 2006; Liu 2006; Moe and Trusov 2011).”