Online Product Opinions: Incidence, Evaluation and Evolution

Moe, Wendy W.; Schweidel, David A.

doi:10.2139/ssrn.1525205

Cited by 114 publications

(174 citation statements)

References 28 publications

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“…The results clearly supported the social influence bias hypothesis, that is, extremely positive ratings affected subjects more than moderate opinions. In line with the results from the previous research (Moe and Schweidel, 2012; Ma et al ., 2013), the authors also found that frequent reviewers are less affected by prior ratings. Repeat customers were also less influenced – as they have more solid opinions about the hotel they had to rate.…”

Section: Behavioral Dimensionsupporting

confidence: 93%

“…These results built on the conclusion by Schlosser (2005), who found self‐presentational concerns in posters – those whose opinion would have been made public. The authors also found that “[i]ndividuals with either high or low postpurchase evaluations are more likely to contribute, whereas individuals with moderate postpurchase evaluations are less likely to contribute” (Moe and Schweidel, 2012, p. 383), which therefore provides support to underreporting bias, as theorized by Hu et al . (2009).…”

Section: Behavioral Dimensionmentioning

confidence: 69%

“…Using data from Yelp, the authors demonstrated that reviewers who are geographically mobile socially connected and females are less likely to be influenced by previous reviews. Further, more experienced reviewers, given their knowledge of rating platforms, are less affected by prior feedback, confirming (Moe and Schweidel, 2012; Cicognani et al ., 2016). Interestingly, the authors also found that the longer the time since the last review, the more independent the next review is.…”

Section: Behavioral Dimensionmentioning

confidence: 71%

“…Using reviews from BazaarVoice on cosmetics and home products, Moe and Schweidel (2012) analyzed the influence of prior reviews on the rating behavior, differentiating between infrequent and frequent posters. First, they demonstrated that consumers are more likely to write a review when the valence is high.…”

Section: Behavioral Dimensionmentioning

confidence: 99%

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The Economic and Behavioral Consequences of Online User Reviews

Magnani

2020

Journal of Economic Surveys

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Online user reviews have become an increasingly relevant informational tool during product search and adoption. Recent surveys have shown that consumers trust and rely on online reviews more than they do on website recommendations and experts opinions. As a new way of driving consumer purchasing intentions, online user reviews have therefore come under scrutiny by researchers. The objective of this paper is to offer an overview of the literature regarding the impact of online user reviews on economic indicators (e.g., sales, marketing strategies) and on consumer behavior. Furthermore, following the growing interest of academics and professionals alike on the topic, the present work provides an exploratory analysis of the consequences of online reviews on individual rating behavior – empirical regularities showed that online rating distributions tend to be concentrated on extreme values, possibly because of rating biases. As consumers and firms incorporate the heuristic cues from such distributions into their decision‐making processes, biased ratings might lead to suboptimal choices. This overview presents established results (e.g., the impact of volume on product sales) and insights as issues for future research.

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Section: Behavioral Dimensionsupporting

confidence: 93%

Section: Behavioral Dimensionmentioning

confidence: 69%

Section: Behavioral Dimensionmentioning

confidence: 71%

Section: Behavioral Dimensionmentioning

confidence: 99%

See 2 more Smart Citations

The Economic and Behavioral Consequences of Online User Reviews

Magnani

2020

Journal of Economic Surveys

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“…Whether a poster writes a positive or negative message is affected by consumption experience, forum environment, and goals. For instance, message valence could reflect product satisfaction (Anderson, 1998), the presence of other reviews on the website (Moe & Schweidel, 2012), or self‐enhancement goals (Schlosser, 2005). Our focus is on where the poster chooses to target a positive or negative message.…”

Section: Conceptual Frameworkmentioning

confidence: 99%

Posting strategically: The consumer as an online media planner

Chen¹,

Kirmani

2015

J Consum Psychol

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How do consumers choose to post their brand reviews online? Whereas prior research examines what people say online, we investigate where consumers post their brand‐related consumption experience on an online discussion forum. Using the framework of the Persuasion Knowledge Model, we suggest that consumers act as intuitive media planners to assess the extent to which they can reach their specific goals when targeting online audiences. Specifically, we examine the effects of posters' motives, message valence, and audience similarity on posting behavior. We propose and find that persuasion‐motivated consumers focus on whether the message is effective in generating interest and emotion from the audience; therefore, they are more likely to post positive messages on a brand‐general forum, such as a product forum, and negative messages on a brand‐specific forum. In contrast, affiliation‐motivated posters primarily focus on audience similarity, preferring to post on a forum where they perceive the audience as similar to them. Three experiments show the different posting patterns under the two motives and demonstrate the mediating role of message effectiveness under a persuasion motive.

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How online word‐of‐mouth impacts receivers

Moore

Lafreniere

2019

Consumer Psychology Review

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Online word‐of‐mouth (WOM) can impact consumers’ product evaluations, purchase intentions, and choices—but when does it do so? How do those receiving WOM know whether to rely on a particular message? This article suggests that the multiple players involved in online WOM (receivers, senders, sellers, platforms, and other consumers) each have their own interests, which are often in conflict. Thus, receivers of WOM are faced with a judgment task in deciding what information to rely on: They must make inferences about the product in question and about the players who provide or present WOM. To do so, they use signals embedded in various components of WOM, such as average star ratings, message content, or sender characteristics. The product and player information provided by these signals shapes the impact of WOM by allowing receivers to make inferences about (a) their likelihood of product satisfaction, and (b) the trustworthiness of WOM players, and therefore the trustworthiness of their content. This article summarizes how each player changes the impact of online WOM, providing a lens for understanding the current literature in online WOM, offering insights for theory in this context, and opening up pathways for future research.

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Online Product Opinions: Incidence, Evaluation and Evolution

Cited by 114 publications

References 28 publications

The Economic and Behavioral Consequences of Online User Reviews

The Economic and Behavioral Consequences of Online User Reviews

Posting strategically: The consumer as an online media planner

How online word‐of‐mouth impacts receivers

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