Impact of online reviews in virtual communities on cross-border e-commerce platform reputation
Shenglin Ma et al.
What the paper says
Purpose: This article aims to reveal how online reviews in virtual communities affect the reputation of platform sellers. Through research, consumers are encouraged to make effective use of online reviews, and it also provides enlightenment for the marketing management of cross-border e-commerce platform sellers. Design/methodology/approach: Based on the stimulus-organism-response (SOR) theoretical framework, this article uses structural equation modelling (SEM) to empirically investigate how online reviews in virtual communities affect the perceived reputation of cross-border e-business (CBEB) platform sellers. Findings/results: The results of the study show that online reviews significantly influence the perceived reputation of CBEB platform sellers. Among them, platform market institution trust and platform shopping efficacy play a chain mediating role in the influence of online reviews on the perceived reputation of platform sellers, and customer stickiness plays a significant moderating effect in the influence of online reviews on the perceived reputation of CBEB platform sellers. Practical implications: The study provides actionable strategies for e-commerce platforms to incentivise user review participation while enhancing market institutional frameworks and customer shopping efficiency. Originality/value: Based on the SOR theory, this study examines the impact of online reviews on the reputation of platform sellers within the context of a virtual community, from the perspective of reviewer characteristics. It explores the moderating effect of customer stickiness and the mediating role of platform market institution trust and platform shopping efficiency.
2 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.25 × 0.4 = 0.10 |
| M · momentum | 0.55 × 0.15 = 0.08 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.