The three-way moderation of valence, linguistic similarity, and hedonic content in online reviews on purchase intention
Keywords:
Hedonic Content, Linguistic Style, Similarity, Online Systems, Online Reviews, Word-of-MouthAbstract
Objective: The aim of this study was to theoretically explore and empirically test the three-way moderation of online review valence, perceived linguistic similarity between the reviewer and the reader, and perceived hedonic content on purchase intention. Method: An experiment was conducted with a between-subjects design, manipulating the valence of online reviews (positive vs. negative). The moderating variables, linguistic style similarity and hedonic content, as well as the dependent variable, purchase intention, were measured. Participants were exposed to a scenario of purchasing a streaming service and randomly read either a positive or negative review. The questionnaire was created on the SurveyMonkey platform and distributed through social media. Main Results: Positive reviews have a stronger positive effect on purchase intention, especially at higher levels of similarity and hedonic content. In contrast, negative reviews decrease purchase intention only when similarity is low and increase purchase intention as hedonic content increases and linguistic similarity is high. Relevance / Originality: This study stands out by addressing a relatively unexplored approach in prior research: the three-way moderation effect of review valence, linguistic similarity, and hedonic content on purchase intention. We provide empirical evidence that as linguistic similarity increases, negative valence and hedonic content reduce the negative impact of the review on purchase intention. Theoretical / Methodological Contributions: Our findings advance knowledge by offering more comprehensive explanations of the effect of valence and hedonic content on purchase intention, theoretically incorporating perceived linguistic similarity as an additional moderating factor. Methodologically, the use of an experimental design provides a robust approach for testing the proposed relationships.
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