Reviews, trust, and customer experience in online marketplaces: the case of Mercado Libre Colombia
Nathalie Peña-García, Mauricio Losada-Otálora, David Pérez Auza, María Paula Cruz
Colegio de Estudios Superiores de Administración Pontificia Universidad Javeriana
内容与影响
Purpose The research focuses on the crucial role of online reviews in shaping consumer trust in e-commerce platforms, examining the impact of perceived authentic and fake reviews on purchasing decisions and platform reputation. It assesses how consumers perceive review authenticity and quality and their effects on trust levels in reviews, marketplaces, and reputation systems. It also explores the relationship between trust forms and overall experiences. Design/methodology A quantitative approach is employed, utilizing a questionnaire distributed to recent Mercado Libre buyers. To test hypotheses, data from 326 valid responses are analyzed using confirmatory factor analysis and Partial Least Squares Structural Equation Modeling (PLS-SEM). Findings Findings reveal that fake review perception negatively affects trust in rating systems, while high-quality reviews positively influence all trust forms. Customer experience is directly impacted by trust in marketplaces and rating systems, indicating a mediation effect of trust in the rating system on the relationship between fake review perception and customer experience. Research limitations/implications Limitations include using a convenience sample and focusing on trust in the rating system rather than reviews or the marketplace, suggesting avenues for future research. Practical implications include recommendations to ensure review quality, enhance rating system controls, and promote review usage in the purchase process. Originality The study addresses a timely and relevant gap in understanding the impact of reviews on e-commerce trust, particularly within the context of Latin America and Mercado Libre’s dominance in the region’s e-commerce landscape.
逐年被引趋势
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
回答优先基于摘要、文献信息与可获取全文;依据不足时会明确说明。
学术脉络
学科主题
社会科学Digital Marketing and Social Media
Technology Adoption and User Behaviour · Digital Communication and Language
参考文献 97
此处列出前 3 条
施引文献 32
按被引量排序,此处列出前 3 条