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Argument quality and review adoption: Interaction effect of product and review typeoa mark
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Publication Year
2021-01-01
Publisher
Asia Business Research Corporation
Citation
Asian Journal of Business Research, Vol.11, pp.22-42
Keyword
Argument qualityOnline shoppingProduct typeReview adoptionReview type
All Science Classification Codes (ASJC)
Business and International ManagementSociology and Political SciencePolitical Science and International RelationsStrategy and ManagementMarketing
Abstract
Argument quality has become an important variable that promotes consumers’ decision-making based on online reviews. It has two dimensions, perceived informativeness and perceived persuasiveness. Adopting dual-process theory, this study examines the effect of these two dimensions of argument quality on review adoption. Moreover, it investigates whether the relationships between argument quality and review adoption differ based on product type and review type. According to the multi-group analysis result, for attribute-centric reviews, search products have a better fit than experience products in the relationship of perceived informativeness and perceived persuasiveness, also for the relationship of perceived informativeness on review adoption, while experience products have a better fit than search products for the relationship of perceived persuasiveness on review adoption. For benefit-centric reviews, search products and experience products have no significant difference in any of the relationships. Furthermore, the result reveals that perceived persuasiveness mediates perceived informativeness and review adoption. The findings contribute to the understanding of the information adoption model with different review types and product types and help shopping websites develop better strategies for product recommendation reviews.
Language
eng
URI
https://dspace.ajou.ac.kr/dev/handle/2018.oak/32371
DOI
https://doi.org/10.14707/ajbr.210105
Fulltext

Type
Review
Funding
This work was supported by the Ajou University research fund.
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Kang, Mincheol Image
Kang, Mincheol강민철
Department of Business Intelligence
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