Exploring an incongruence frame for online reviews

Given the growth in the internet and e-retailing, consumers are extremely reliant on online user-generated reviews (“reviews”) for decision-making. Reviews often combine informational cues such as numeric (i.e., star) ratings and qualitative text, and these may not always be in alignment. To understand conflicting informational cues, this research conceptualizes and tests an incongruence frame that captures the inconsistency between a review's textual and numeric message cue components. Incongruence occurs when the valence of the review text is not in alignment with the product star rating given by the reviewer. To further qualify the findings, the paper introduces two types of incongruences: Type A (Type B) is categorized as involving low (high) star ratings alongside a positive (negative) review text. The research findings shed light on an underexplored dimension of review processing based on inconsistency between the textual and numeric components of a single review. Using primary and secondary data across four studies, the incongruence effect is shown to undermine review usage. Incongruence is found to influence both review diagnosticity and review authenticity. The initial heuristics of review evaluation generate differential effects between Type A and Type B. Incongruence in the review is also shown to influence product purchases. The incongruence frame, therefore, helps reconcile some of the inconsistencies in the extant literature and offers fruitful avenues of future research for both academics and practitioners.