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EMAC 2021 Annual Conference


Different Facets of Online Reviews
(A2021-102336)

Published: May 25, 2021

AUTHORS

Andreas Bayerl, University Mannheim; Verena Schoenmueller, Bocconi University; Marton Varga, INSEAD; Sungtak Hong, Bocconi University

ABSTRACT

"Since online review began showing up in 1999, marketing research about eWOM has developed from its early work showing that they matter to more recent studies better understanding their role in predicting customer decisions and sales and even extracting latent information embedded in the reviews’ content. In this special session we will go into additional and new facets of online reviews. “The Impact of a Single Negative Customer Review on Online Search and Purchase Decisions” by Marton Varga (INSEAD) and Paulo Albuquerque (INSEAD): We measure how negative reviews affect purchase and browsing decisions. Using data from a large online retailer of durable goods, we find that a single negative review is enough to reduce the probability of purchase. We also show that a negative review discourages consumers to paginate or sort the product’s reviews but motivates them to search for alternative products. We illustrate the vulnerability of products to reviews on two-dimensional product maps. “Quality Competition in the Fast-Food Chain Industry: Evidence from Online Reviews” by Sungtak Hong(Bocconi University), Prasad Vana (Dartmouth College) and Dirk Hovy (Bocconi University): We use online restaurant reviews from Yelp to explore how restaurants compete in a domain of product and service quality. By focusing on fast-food restaurants, which offer a similar menu of products with varying food quality, we document how fast-food restaurants adjust their service quality in the presence of three hipster mega chains (Five Guys, In-N-Out, and Shake Shack) in the local markets.  “The “Oracles” of Online Reviews”  by Yael Karlinsky (Northeastern University) and Verena Schoenmueller (Bocconi University): In a crowd of reviewers, we identify “oracle reviewers” whose opinions have a higher-than-average predictive power for product success. We find that the mere appearance of a review and a favorable opinion by an oracle reviewer are predictive of product success. While previous research focused mostly on predicting product success based on individual or aggregate characteristics of a product’s reviews, we use heterogeneity in the individual reviewer’s behavior to identify the sources of wisdom in the crowd. This allows companies to better assess the potential product success in the market. “The interplay between wages and online reviews on the labor market” by Andreas Bayerl (Uni Mannheim), Jacob Goldenberg (IDC Herzliya), Daniel Shapira (Ben-Gurion University), and Florian Stahl (Uni Mannheim): Studying a large-scale dataset of online employer reviews, we find that wage level is not always positively correlated with ratings as might be expected. In the extremes (i.e., very high & very low wage levels) it even turns to be negative. We investigate factors that generate this phenomenon using bootstrapped mediation analysis. Using rich field data, we also show that employer reviews matter for companies."