Effect Of Online Product Reviews Research Articles

On the Spillover Effects of Online Product Reviews on Purchases: Evidence from Clickstream Data

We study the spillover effects of the online reviews of other covisited products on the purchases of a focal product using clickstream data from a large retailer. The proposed spillover effects are moderated by (a) whether the related (covisited) products are complementary or substitutive, (b) the choice of media channel (mobile or personal computer (PC)) used, (c) whether the related products are from the same or a different brand, (d) consumer experience, and (e) the variance of the review ratings. To identify complementary and substitutive products, we develop supervised machine-learning models based on product characteristics, such as product category and brand, and novel text-based similarity measures. We train and validate the machine-learning models using product pair labels from Amazon Mechanical Turk. Our results show that the mean rating of substitutive (complementary) products has a negative (positive) effect on purchasing of the focal product. Interestingly, the magnitude of the spillover effects of the mean ratings of covisited (substitutive and complementary) products is significantly larger than the effects on the focal product, especially for complementary products. The spillover effect of ratings is stronger for consumers who use mobile devices versus PCs. We find the negative effect of the mean ratings of substitutive products across different brands on purchasing of a focal product to be significantly higher than within the same brand. Lastly, the effect of the mean ratings is stronger for less experienced consumers and for ratings with lower variance. We discuss implications on leveraging the spillover effect of the online product reviews of related products to encourage online purchases.

Effect of online product reviews on third parties’ selling on retail platforms

Abstract Online retailers open their platforms to invite third-party sellers to sell directly on their platforms for commissions. Considering that most consumers make purchase decisions using online product reviews (OPRs) as a reference, we develop a game-theoretic model to explore how OPRs impact a third-party seller’s decision to sell on an open retail platform and the platform retailer’s profit. Based on two product attributes—quality and fit—we distinguish two cases, quality dominates fit and fit dominates quality. We find that, under symmetric reviews (i.e., reviews favoring neither the retailer’s nor the third party’s product), higher credibility reviews homogenize (heterogenize) products, thus intensifying (relieving) competition between the retailer and the third party in the quality-dominates-fit (fit-dominates-quality) case. However, even under asymmetric reviews, the third party cannot be induced to sell on the retail platform until considering the quality of the retailer’s review systems, which may lead to a platform effect on OPRs. The platform effect strengthens the importance of reviews, so it may enlarge the product differentiation created by asymmetric reviews. Particularly, when the platform effect and the review asymmetry are high enough, the retailer can not only induce the third party to sell on its platform but also benefit in both the quality-dominates-fit and the fit-dominates-quality cases.

The Effects of Online Product Reviews on Sales Performance: Focusing on Number, Extremity, and Length

The Effects of Online Product Reviews on Sales Performance: Focusing on Number, Extremity, and Length

The Dark Side of Reviews: The Swaying Effects of Online Product Reviews on Attribute Preference Construction

Based on the wisdom of the crowd effect, consumer-generated online reviews are supposed to help consumers make more accurate product evaluations. However, the large amount of information in the r...

On the Spillover Effects of Online Product Reviews on Purchases: Evidence from Clickstream Data

We analyze the spillover effect of the online reviews of related products on the purchases of a focal product using clickstream data from a large retailer by investigating (a) whether the related, co-visited products are complementary or substitutive; (b) whether the related products are from the same or a different brand, and (c) the choice of media channel (mobile or PC) used. To identify complementary and substitutive products, we used a text-mining approach of topic modeling on the product descriptions to quantify the functional similarity of pairwise products. Our empirical analysis shows that the mean rating of the online reviews of substitutive products has a negative effect on the purchasing of the focal product, while the mean rating of complementary products has a positive effect. Moreover, we find that the negative spillover effect of the online reviews of substitutive products across different brands on the purchasing of a focal product is significantly higher than those of the same brand, and for consumers who viewed online product reviews on mobile devices versus traditional PCs. Our study has theoretical and managerial implications on leveraging the spillover effects of the online product reviews of related products on purchases.

The Effects of Online Product Reviews on Online Users' Shopping Process

The Effects of Online Product Reviews on Online Users' Shopping Process

Online Product Reviews: Implications for Retailers and Competing Manufacturers

This paper studies the effect of online product reviews on different players in a channel structure. We consider a retailer selling two substitutable products produced by different manufacturers, and the products differ in both their qualities and fits to consumers' needs. Online product reviews provide additional information for consumers to mitigate the uncertainty about the quality of a product and about its fit to consumers' needs. We show that the effect of reviews on the upstream competition between the manufacturers is critical in understanding which firms gain and which firms lose. The upstream competition is affected in fundamentally different ways by quality information and fit information, and each information type has different implications for the retailer and manufacturers. Quality information homogenizes consumers' perceived utility differences between the two products and increases the upstream competition, which benefits the retailer but hurts the manufacturers. Fit information heterogenizes consumers' estimated fits to the products and softens the upstream competition, which hurts the retailer but benefits the manufacturers. Furthermore, reviews may also alter the nature of upstream competition from one in which consumers' own assessment on the quality dimension plays a dominant role in consumers' comparative evaluation of products to one in which fit dimension plays a dominant role. If manufacturers do not respond strategically to reviews and keep the same wholesale prices regardless of reviews (i.e., the upstream competition is assumed to be unaffected by reviews), then, we show that reviews never hurt the retailer and the manufacturer with favorable reviews, and never benefit the manufacturer with unfavorable reviews, a finding that demonstrates why reviews' effect on upstream competition is critical for firms in online marketplaces.

Modeling Consumer Learning from Online Product Reviews

We propose a structural model to study the effect of online product reviews on consumer purchases of experiential products. Such purchases are characterized by limited repeat purchase behavior of the same product item (such as a book title), but significant past usage experience with other products of the same type (such as books of the same genre). To cope with the uncertainty in quality of the product item, we posit that consumers may learn from their experience with the same type of product, and others’ experiences with the product item. We model the credibility of product reviews and how it evolves over time. We apply the model to a panel dataset of 1,919 book purchases by 243 consumers. We find that consumers learn more from online reviews of book titles than from their own experience with other books of the same genre. We estimate the profit impact of product reviews and how it varies with the number of reviews. We find evidence of diminishing returns to increasing number of reviews. Under certain conditions, additional reviews might even lead to lower profits. We estimate the optimum number of reviews for a representative product.

Online Product Reviews: Implications for Retailers and Competing Manufacturers

This paper studies the effect of online product reviews on different players in a channel structure. We consider a retailer selling two substitutable products produced by different manufacturers, and the products differ in both their qualities and the fits to consumers' needs. Online product reviews provide additional information for consumers to mitigate the uncertainty about the quality of a product and about its fit to consumers' needs. We show that the effect of reviews on the upstream competition between the manufacturers is critical in understanding which firms gain and which firms lose. The upstream competition is affected in fundamentally different ways by quality information and fit information, and each information type has different implications for the retailer and manufacturers. The quality information homogenizes consumers' perceived utility differences between the two products and increases the upstream competition, which benefits the retailer but hurts the manufacturers. The fit information heterogenizes consumers' estimated fits to the products and softens the upstream competition, which hurts the retailer but benefits the manufacturers. Furthermore, reviews may also alter the the nature of upstream competition from one in which consumers' own assessment on the quality dimension plays a dominant role in consumers' comparative evaluation of products to one in which fit dimension plays a dominant role. If manufacturers do not respond strategically to reviews and keep the same wholesale prices regardless of reviews (i.e., the upstream competition is assumed to be unaffected by reviews), then, we show that reviews never hurt the retailer and the manufacturer with favorable reviews, and never benefit the manufacturer with unfavorable reviews, a finding that demonstrates why reviews' effect on upstream competition is critical for firms in online marketplaces.

Computer-mediated persuasion in online reviews: Statistical versus narrative evidence

The current study examined the effects of online product reviews on individuals’ credibility perceptions of the reviews and their attitudes about the product targeted in the reviews. Study 1 used a 2 (review type: statistical and narrative)×2 (review valence: negative and positive) design, and study 2 used a 2 (statistical review valence: positive and negative)×2 (narrative review valence: positive and negative) design. The findings of study 1 were consistent with those of study 2 and indicated that negative statistical reviews were perceived as more credible than negative narrative reviews, while the credibility of positive statistical reviews did not differ from that of positive narrative reviews. On the other hand, statistical reviews and narrative reviews did not differ in terms of affecting individuals’ attitudes about the product. The current study also found that the vividness and valence of each review type had varying effects on review credibility and attitudes about the product. The implications of these and other findings are discussed in detail in the paper.

Modeling Consumer Learning from Online Product Reviews

We propose a structural model to study the effect of online product reviews on consumer purchases of experiential products. Such purchases are characterized by limited repeat purchase behavior of the same product item (such as a book title) but significant past usage experience with other products of the same type (such as books of the same genre). To cope with the uncertainty in quality of the product item, we posit that consumers may learn from their experience with the same type of product and others' experiences with the product item. We model the review credibility as the precision with which product reviews reflect the consumer's own product evaluation. The higher the precision, the more credible the information obtained from product reviews for the consumer, and the larger the effect of reviews on the consumer's choice probabilities. We extend the Bayesian learning framework to model consumer learning on both product quality and review credibility. We apply the model to a panel data set of 1,919 book purchases by 243 consumers. We find that consumers learn more from online reviews of book titles than from their own experience with other books of the same genre. In the counterfactual analysis, we illustrate the profit impact of product reviews and how it varies with the number of reviews. We also study the phenomenon of fake reviews. We find that fake reviews increase consumer uncertainty. The effects of more positive reviews and more numerous reviews on consumer choice are smaller on online retailing platforms that have fake product reviews.

How perceived quality of online reviews affects consumer purchase intention

The effect of online product reviews on product sales has become a central interest of marketing and information systems researchers because of the popularity of such type of reviews. However, most previous studies were conducted at the product level, rather than at the website level. Analysing the influence of online reviews on consumer intention to purchase on websites is necessary because websites are more concerned about the aggregate effect of online reviews on sales, rather than sales from individual products. Using word-of-mouth literature and information quality theory as bases, we examine whether and how online reviews affect consumer purchase intention on a specific website. We identify four online review attributes, namely, intrinsic quality of online reviews, number of online reviews, reviewer reputation, and review timeliness, and assess their effects on consumer purchase intention. The findings of this study reveal the positive effects of the first two factors on consumer purchase intention, whereas the remaining two attributes show no such influence.