How Online Product Reviews Affect Retail Sales: A Meta-analysis

Do different kinds of user-generated content in online brand communities really work?

“…Briefly, the main improvements of the new version are: Before considering this editors' suggestion, we would like to indicate that we have corrected two erroneous references included in the last version of the paper. In particular, they are: -An error in the year of publication in Floyd et al (2015), which has been replaced by Floyd et al (2014). -An error in the surname of the author in Hyesun et al (2016), which has been replaced by Jeon et al (2016).…”

“…From the perspective of vividness and richness of online UGC, reviews and comments are only text messages and are characterised as low level of vividness and richness (Coursaris et al, 2016;Luarn et al, 2015). Previous research obtains mixed results regarding the influence of valence of users' reviews (i.e., whether comments are positive or negative) on sales (Floyd et al, 2014;You et al, 2015) and other psychological outcomes (Purnawirawan et al, 2015). Despite this fact, some authors underscore the significance of online customers' reviews by showing that positive/negative information encountered online can be a triggering factor to modify customer behaviour (i.e., buy/not buy, respectively) (Adjei et al, 2010;Chevalier and Mayzlin, 2006;Veloutsou et al, 2017).…”

“…Despite the importance of understanding the effects of different types of UGC in OBCs on brand/product success, this topic has received limited attention in academic literature Yadav and Pavlou, 2014). Previous research is mainly focused on volume and/or valence of customers' reviews (i.e., only text based), obtaining mixed results on their influence on sales (Floyd et al, 2014;You et al, 2015) and other psychological outcomes (Purnawirawan et al, 2015). Moreover, previous research focused on the analysis of different types of UGC merely examines their influence on brand popularity and brand engagement (Coursaris et al, 2016;Luarn et al, 2015).…”

The value of empirical generalizations in marketing

“…For example, a specialist on the modeling of advertising response effects may want to know that a different driver, product reviews, has a sales elasticity about six times that of advertising. Indeed, Sethuraman et al (2011) reported an average advertising elasticity of 0.12, whereas Floyd et al (2014) listed an average product-review valence elasticity of 0.68. Comparisons such as these are important as technology evolution makes the management of the marketing mix increasingly siloed, i.e., focused on a narrower and narrower subset of the entire marketing mix.…”

Impact of reviewer social interaction on online consumer review fraud detection

“…Another study [3] documents that approximately 5% of reviews posted on websites are by users who have no records of purchasing that product or anything on that particular website. A meta-analysis on online reviews [11] focuses on understanding the effect of online reviews on retailers' performance and revenue using sales elasticity. An analysis on online review elasticity [43] present that volume and valence elasticity is higher for lesser known products which are sold by a couple of online retailers and that volume elasticity is higher on the product market whereas valence elasticity is higher on community markets.…”