Consumer Responses to Positive and Negative Online Reviews
Date: 12 December 2013
Venue: University of Antwerp, Promotiezaal Grauwzusters - Lange Sint-Annastraat 7 - 2000 Antwerp
Organization / co-organization: Faculty of Applied Ecomics
PhD candidate: Nathalia A. Purnawirawan
Principal investigator: Prof. Patrick De Pelsmacker
Co-principal investigator: Nathalie Dens
Short description: PhD defence Nathalia A. Purnawirawan - Faculty of Applied Ecomics
Abstract: With the evolving new media technologies, traditional word-of-mouth (WOM) has been transformed and extended to electronic word-of-mouth (eWOM). Stories and experiences related to people, brands or organizations are instantly shared and spread on the Internet. This dissertation focuses on online reviews, product information and evaluations generated by users or experts, based on their personal experience.
The objective of this thesis is threefold. First, to provide an overview of the state of the art of research regarding the effect of positive versus negative online reviews. A meta-analysis fulfills this objective and shows that recommendation direction (positive, negative) indeed matters. When the majority of people post negative (positive) reviews about a certain object or post negative (positive) feedback regarding a certain seller (e.g., on eBay or Amazon), the reader would be less (more) inclined to buy that particular object or from that particular seller.
The second objective is to examine how the majority's opinion affects consumers responses and which variables moderate this effect. Based on several experiments, the results show a strong and consistent effect of the majority's opinion. In addition, the effect of this majority's opinion on consumer responses appears to be moderated by sequence (presentation order), the source of the review (expert versus consumer), and the content of the review (coherent, discussing the same attribute as the majority, versus incoherent, discussing another attribute). A wrap sequence (positive-negative-positive or negative-positive-negative) can bias evaluations when the majority's opinion is not available, or strengthen the usefulness of the reviews when the majority's opinion is available. Furthermore, a review seems more likely to be discounted when it comes from an expert or when it discusses an incoherent content.
Finally, this thesis investigates whether and how service providers should respond to negative online reviews. The more negative the majority is, the more effort the service provider needs to do to recover prospect customers. While offering a compensation, in addition to apology and promise (it won't happen again), is unnecessary when the majority of reviews is positive or neutral, it is essential when the majority is negative.