Consumer-generated product reviews have proliferated online, driven by the notion that consumers' decision to purchase or not purchase a product is based on the positive or negative information about that product they obtain from fellow consumers. Using research on information processing (Chaiken 1980) as a foundation, we suggest that in the context of an online community, reviewer disclosure of identity-descriptive information is used by consumers to supplement or replace product information when making purchase decisions and evaluating the helpfulness of online reviews. Using a unique dataset based on both chronologically compiled ratings as well as reviewer characteristics for a given set of products and geographical location-based purchasing behavior from Amazon, we provide evidence that community norms are an antecedent to reviewer disclosure of identity-descriptive information. Amazon members rate reviews containing identity-descriptive information more positively, and the prevalence of reviewer disclosure of identity information is associated with increases in subsequent online product sales. In addition, we show that when reviewers are from a particular geographic location, subsequent product sales are higher in that region, thus highlighting the important role of geography in electronic commerce. Taken together, our results suggest that identity-relevant information about reviewers shapes community members' judgment of products and reviews. Implications for research on the relationship between online reviews and sales, peer recognition systems, and conformity to online community norms are discussed.

/pdf/examining-the-relationship-between-reviews-and-sales-the-jp34uv1l20.pdf

Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets

Consumer-generated product reviews have proliferated online, driven by the notion that consumers' decision to purchase or not purchase a product is based on the positive or negative information about that product they obtain from fellow consumers. Using research on information processing as a foundation, we suggest that in the context of an online community, reviewer disclosure of identity-descriptive information is used by consumers to supplement or replace product information when making purchase decisions and evaluating the helpfulness of online reviews. Using a unique data set based on both chronologically compiled ratings as well as reviewer characteristics for a given set of products and geographical location-based purchasing behavior from Amazon, we provide evidence that community norms are an antecedent to reviewer disclosure of identity-descriptive information. Online community members rate reviews containing identity-descriptive information more positively, and the prevalence of reviewer disclosure of identity information is associated with increases in subsequent online product sales. In addition, we show that shared geographical location increases the relationship between disclosure and product sales, thus highlighting the important role of geography in electronic commerce. Taken together, our results suggest that identity-relevant information about reviewers shapes community members' judgment of products and reviews. Implications for research on the relationship between online word-of-mouth WOM and sales, peer recognition and reputation systems, and conformity to online community norms are discussed.

The Internet has provided IS researchers with the opportunity to conduct studies with extremely large samples, frequently well over 10,000 observations. There are many advantages to large samples, but researchers using statistical inference must be aware of the p-value problem associated with them. In very large samples, p-values go quickly to zero, and solely relying on p-values can lead the researcher to claim support for results of no practical significance. In a survey of large sample IS research, we found that a significant number of papers rely on a low p-value and the sign of a regression coefficient alone to support their hypotheses. This research commentary recommends a series of actions the researcher can take to mitigate the p-value problem in large samples and illustrates them with an example of over 300,000 camera sales on eBay. We believe that addressing the p-value problem will increase the credibility of large sample IS research as well as provide more insights for readers.

https://www.galitshmueli.com/system/files/Print%20Version.pdf

Research Commentary---Too Big to Fail: Large Samples and the p-Value Problem

User-Generated Content in online platforms or chatter for short provides a valuable source of consumer feedback on market performance of firms. This study examines whether chatter can predict stock market performance, which metric of chatter has the strongest relationship, and what the dynamics of the relationship are. The authors aggregate chatter (in the form of product reviews) from multiple websites over a four year period across six markets and fifteen firms. They derive multiple metrics of chatter (volume, positive chatter, negative chatter, and 5-start ratings) and use multivariate time series models to assess the short and long term relationship between chatter and stock market performance. They use three measures of stock market performance: abnormal returns, risk, and trading volume.The findings reveal that two metrics of chatter can predict abnormal returns with a lead of a few days. Of four metrics of chatter, volume shows the strongest relationship with returns and trading volume, followed by negative chatter. Whereas negative chatter has a strong effect on returns and trading volume with a short “wearin” and long “wearout,” positive chatter has no effect on these metrics. Negative chatter also increases volatility (risk) in returns.A portfolio analysis of trading stocks based on their chatter provides a return of 8% over and above normal market returns. In addition to the investing opportunities, the results show managers that chatter is an important metric to follow to gauge the performance of their brands and products. Because chatter is available daily and hourly, it 2 can provide an immediate pulse of performance that is not possible with infrequent sales and earnings reports. The fact that negative chatter is more important than positive, indicates that negatives are more diagnostic than positives. The negatives suggest what aspects of the products managers should focus on.

Does Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance

Companies have increasingly advocated social media technologies to transform businesses and improve organizational performance. This study scrutinizes the predictive relationships between social media and firm equity value, the relative effects of social media metrics compared with conventional online behavioral metrics, and the dynamics of these relationships. The results derived from vector autoregressive models suggest that social media-based metrics (web blogs and consumer ratings) are significant leading indicators of firm equity value. Interestingly, conventional online behavioral metrics (Google searches and web traffic) are found to have a significant yet substantially weaker predictive relationship with firm equity value than social media metrics. We also find that social media has a faster predictive value, i.e., shorter “wear-in” time, than conventional online media. These findings are robust to a consistent set of volume-based measures (total blog posts, rating volume, total page views, and search intensity). Collectively, this study proffers new insights for senior executives with respect to firm equity valuations and the transformative power of social media.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID2162167_code412577.pdf?abstractid=2162167&mirid=1

Social Media and Firm Equity Value

Consumer-generated product reviews have proliferated online, driven by the notion that consumers' decision to purchase or not purchase a product is based on the positive or negative information abo...

FormanChris

Papers

Examining the Relationship Between Reviews and Sales