Antecedents and Consequents of Information Usefulness in User-generated Online Reviews: A Multi-group Moderation Analysis of Review Valence

Abstract

Online reviews have become a critical component of consumers’ Web-based search queries and help them minimize uncertainty and risk associated with purchase decisions. Not only do customers perceive online reviews to be more “real”, but also online reviews enable opportunities for interactivity between consumers, which makes them a popular source of information when consumers make (online) purchase decisions. In this study, we examine the impact of online reviews on consumers’ beliefs, brand attitudes, and purchase intention by theoretically extending the information adoption model (IAM) with constructs from consumer research. To do so, we used data from a scenario- based online experiment and manipulated three review characteristics (currency, accuracy, and credibility) using carefully selected TripAdvisor reviews. Using a partial-least squares approach (PLS) to structural equation model (SEM), we found strong empirical support for our hypotheses that review quality and reviewer credibility drive information usefulness and that information usefulness, in turn, drives consumers’ attitudes toward and their intention to purchase from a brand. Using PLS multi-group analysis, we further explored the moderating role of review valence—positive versus negative—and found significant differences in the importance of the drivers of information usefulness and its consequents. We discuss our study’s implications for theory and practice