The influence of social media marketing on brand loyalty and intention to use among young Vietnamese consumers of digital banking

  • Received August 13, 2023;
    Accepted September 20, 2023;
    Published October 2, 2023
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/im.19(4).2023.01
  • Article Info
    Volume 19 2023, Issue #4, pp. 1-13
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This work is licensed under a Creative Commons Attribution 4.0 International License

Digital banks must promote on social media to attract tech-savvy young consumers who use social media extensively. Creating brand loyalty among digital banking customers is necessary to increase retention and motivate them to spend more with the preferred financial brand. This study investigates the impact of social media marketing on brand loyalty and continued usage intentions among young Vietnamese digital banking service consumers. This study employed a quantitative methodology, with a five-point Likert scale questionnaire administered online via non-probability sampling. The sample comprised 244 Vietnamese consumers aged 18 to 35, representing the young consumer segment. The data were analyzed using partial least squares structural equation modeling (PLS-SEM). The results indicate that exposure to social media marketing substantially positively impacts brand loyalty. It was discovered that brand loyalty positively influences the intention to continue using the same digital banking provider. However, social media marketing did not influence continued usage intentions directly. Instead, brand loyalty mediated the positive relationship between social media marketing and future digital banking service usage intentions. The findings have important implications for digital banks’ customer engagement and branding strategies to establish long-lasting relationships with the crucial youth demographic via social media platforms.

Acknowledgment
The author wishes to express sincere appreciation to all respondents who completed the survey. In addition, profound appreciation is extended to all involved parties, as well as the Ho Chi Minh University of Banking, for their tremendous support and assistance, which contributed significantly to the completion of this research.

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    • Figure 1. Conceptual model
    • Figure 2. PLS-SEM algorithm analysis
    • Table 1. Demographic variable descriptive statistics
    • Table 2. Cronbach’s alpha
    • Table 3. Scale’s components
    • Table 4. Hypotheses testing
    • Conceptualization
      Nguyen Minh Sang
    • Data curation
      Nguyen Minh Sang
    • Formal Analysis
      Nguyen Minh Sang
    • Methodology
      Nguyen Minh Sang
    • Visualization
      Nguyen Minh Sang
    • Writing – original draft
      Nguyen Minh Sang
    • Writing – review & editing
      Nguyen Minh Sang