Examining Interaction Effects of Online Review Type and Product Type on Argument Quality and Review Adoption：Multi-group Analysis in Partial Least Squares (PLS) Path Modeling
Argument quality has become an important variable that promotes consumers’ decision making in online reviews, which has two dimensions are perceived informativeness and perceived persuasiveness. This study is to understand the effect of two dimensions of argument quality on review adoption. Moreover, there has been little research assessing the impact the interaction effect of review type by product type on message processing. Based on these constructs, this paper investigates the interaction impact of different product type by different review type on argument quality and review adoption with cognitive fit theory. We conducted an experiment design to compare the influence of online reviews displayed in four types of information: attribute-centric reviews with search products, attribute-centric reviews with experience products, benefit-centric reviews with search products, and benefit-centric reviews with experience products. Based on the multi-group analysis result, we found that for the attribute-centric reviews, search products have a better fit than experience products between the relationship of perceived informativeness and perceived persuasiveness, as well betweent the relationship of perceived informativeness and review adoption; Experience products have a better fit than search products between the relationship of perceived persuasiveness and review adoption. While for the benefit-centric reviews, search products and experience products have no significant difference for any relationship. The results make a contribution to understand the information adoption model with different review types and product types. We found perceived persuasiveness has a mediating effect between perceived informativeness and review adoption. In addition, we provide helpful evidence for the management of shopping websites using product recommendation reviews.
