The power of trust: How does consumer trust impact satisfaction and loyalty in Indonesian digital business?

  • Received March 6, 2023;
    Accepted May 25, 2023;
    Published June 22, 2023
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/im.19(2).2023.19
  • Article Info
    Volume 19 2023, Issue #2, pp. 236-249
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This work is licensed under a Creative Commons Attribution 4.0 International License

The study aims to explore how consumer satisfaction influences consumer trust and, ultimately, builds strong consumer loyalty in the dynamic world of Indonesian e-commerce. The relevance of this study is determined by how e-commerce businesses can improve customer loyalty by enhancing consumer trust and satisfaction. The study used a quantitative research design and surveyed 230 consumers from Jakarta, Indonesia. The data analysis involved utilizing validation and descriptive statistics in MS Excel and inferential statistics through SmartPLS to draw meaningful conclusions. The results showed a positive, significant, and direct relationship between consumer satisfaction and consumer loyalty. The R2 for consumer loyalty indicates that consumer satisfaction and consumer trust explain 56.6% of the variances in consumer loyalty, whereas consumer satisfaction explains 37.4% of the variances in consumer trust. Furthermore, the findings showed that this relationship is strengthened when consumer trust is included as a mediator, demonstrating a complementary partial mediation indicating that trust enhances consumer loyalty. Thus, the study concludes that consumers are more likely to feel loyal to e-commerce websites when their satisfaction is combined with trust. It provides considerable insights into the determinants of consumer loyalty and emphasizes the importance of establishing trust in e-commerce websites as a critical strategy to enhance customer loyalty. This paper also contributes to the broader literature on consumer behavior and loyalty in the context of digital business, providing new insights and perspectives that can help shape future research in this area.

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    • Figure 1. Conceptual model
    • Figure 2. Structural model output (SEM-PLS)
    • Table 1. Descriptive analysis
    • Table 2. Reliability, validity, and collinearity of the latent variables
    • Table 3. Discriminant validity
    • Table 4. Indicator analysis, discriminant validity, and collinearity
    • Table 5. Results (summarized)
    • Table 6. Structural path model
    • Table 7. Mediation analysis
    • Conceptualization
      Hadi Kurniadi, Junaid Ali Saeed Rana
    • Data curation
      Hadi Kurniadi, Junaid Ali Saeed Rana
    • Formal Analysis
      Hadi Kurniadi, Junaid Ali Saeed Rana
    • Investigation
      Hadi Kurniadi, Junaid Ali Saeed Rana
    • Methodology
      Hadi Kurniadi, Junaid Ali Saeed Rana
    • Project administration
      Hadi Kurniadi, Junaid Ali Saeed Rana
    • Resources
      Hadi Kurniadi, Junaid Ali Saeed Rana
    • Software
      Hadi Kurniadi, Junaid Ali Saeed Rana
    • Validation
      Hadi Kurniadi, Junaid Ali Saeed Rana
    • Writing – original draft
      Hadi Kurniadi, Junaid Ali Saeed Rana
    • Funding acquisition
      Junaid Ali Saeed Rana
    • Supervision
      Junaid Ali Saeed Rana
    • Visualization
      Junaid Ali Saeed Rana
    • Writing – review & editing
      Junaid Ali Saeed Rana