e-WOM, brand image, and e-purchase intention on Shopee: Reassessing e-trust as mediator

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Type of the article: Research Article

Abstract
Although conventional digital marketing literature positions electronic trust (e-trust) as a key mediator of online purchase intention, its role in mature social-commerce environments in developing countries remains uncertain. This study aims to assess the influence of electronic word-of-mouth (e-WOM) and brand image on e-purchase intention, with e-trust as a mediating variable, in the context of local products on the Shopee platform in Indonesia. A quantitative cross-sectional survey was administered to 246 Shopee consumers who had purchased or intended to purchase local products on the platform, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicate that e-WOM and brand image positively and significantly influence both e-trust and e-purchase intention; however, e-trust, operationalized as ability, integrity, and benevolence, does not function as a significant direct predictor of purchase intention, nor as a mediating mechanism. The model explains 72.8% of the variance in e-purchase intention. These findings suggest that seller-level e-trust may not occupy the central mediating role assumed by conventional models in this context. Because the study does not measure platform-level trust or specific heuristic-processing mechanisms, explanations invoking social-affective heuristics or platform trust are offered as directions for future research rather than as direct empirical results. Practically, sellers of local products should prioritize active management of digital word-of-mouth and emotional brand narratives alongside, rather than instead of, trust-building efforts.

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    • Figure 1. Conceptual framework
    • Figure 2. Graphical output of the structural model
    • Table 1. Average achievement of research variable dimensions
    • Table 2. Outer loadings
    • Table 3. Composite reliability and AVE
    • Table 4. Heterotrait-monotrait ratio (HTMT)
    • Table 5. Hypothesis testing (direct effects)
    • Table 6. Mediation test (indirect effects)
    • Table 7. Model fit and explained variance
    • Table 8. F-square effect sizes
    • Table 9. Predictive relevance (PLSpredict)
    • Table 10. Full collinearity VIF
    • Conceptualization
      Prasetyo Hartanto, Vanessa Gaffar
    • Funding acquisition
      Prasetyo Hartanto
    • Investigation
      Prasetyo Hartanto, Kurniawan Kurniawan
    • Methodology
      Prasetyo Hartanto, Mokh Adib Sultan, Kurniawan Kurniawan
    • Project administration
      Prasetyo Hartanto
    • Resources
      Prasetyo Hartanto
    • Software
      Prasetyo Hartanto
    • Writing – original draft
      Prasetyo Hartanto
    • Writing – review & editing
      Prasetyo Hartanto, Kurniawan Kurniawan
    • Data curation
      Vanessa Gaffar, Lili Adi Wibowo, Kurniawan Kurniawan
    • Formal Analysis
      Vanessa Gaffar, Lili Adi Wibowo, Mokh Adib Sultan
    • Supervision
      Vanessa Gaffar, Lili Adi Wibowo, Mokh Adib Sultan, Kurniawan Kurniawan
    • Validation
      Vanessa Gaffar, Lili Adi Wibowo, Mokh Adib Sultan, Kurniawan Kurniawan
    • Visualization
      Lili Adi Wibowo, Mokh Adib Sultan, Kurniawan Kurniawan