Brand love and customer loyalty in digital banking: The mediating role of online brand experience and the moderating role of digital information overload

  • 22 Views
  • 2 Downloads

Creative Commons License DMCA.com Protection Status
This work is licensed under a Creative Commons Attribution 4.0 International License

Type of the article: Research Article

Abstract
The shift toward digital banking has transformed how consumers build relationships with financial brands. As banking inter-actions increasingly occur through mobile applications and online platforms, understanding how emotional attachment is converted into customer loyalty has become important in digital banking research. This study aims to examine how the three dimensions of brand love – intimacy, passion, and commitment – influence customer loyalty through online brand experience, and how digital information overload moderates the relationship between online brand experience and customer loyalty. Data were collected from Vietnamese digital banking users through online and offline surveys conducted in June and July 2025. Respondents were required to have used their current digital banking brand for at least one year. After screening 593 responses, 527 valid questionnaires were analyzed using partial least squares structural equation modeling. The results show that intimacy and passion positively affect commitment, with path coefficients of 0.423 and 0.362, respectively. Intimacy, passion, and commitment positively influence online brand experience, with coefficients of 0.342, 0.314, and 0.280, respectively. Online brand experience strongly predicts customer loyalty (β = 0.637) and mediates the effects of intimacy, passion, and commitment on loyalty, with indirect effects of 0.218, 0.200, and 0.178. Digital information overload negatively moderates the online brand experience and loyalty relationship (β = –0.049). The findings confirm that emotional attachment strengthens customer loyalty through online brand experience, whereas excessive digital information weakens this process.

Acknowledgment
This research is partly funded by Industrial University of Ho Chi Minh City and University of Finance – Marketing.

view full abstract hide full abstract
    • Figure 1. Proposed research model
    • Table 1. Research sample structure (n = 527)
    • Table 2. Outer loadings, Cronbach’s Alpha, CR, and AVE
    • Table 3. Discriminant validity assessment using the Fornell-Larcker criterion
    • Table 4. Collinearity variance inflation factors (VIFs) test
    • Table 5. Hypotheses testing
    • Table A1. Survey measurements
    • Conceptualization
      Pham Thi Kim Thanh, Nguyen Ha Thach, Nguyen Thi Minh Thuy, Luong Thi Thanh Viet
    • Funding acquisition
      Pham Thi Kim Thanh, Nguyen Ha Thach, Nguyen Thi Minh Thuy, Luong Thi Thanh Viet, Phan Thi Huyen, Pham Thi Ngoc Dung
    • Investigation
      Pham Thi Kim Thanh, Nguyen Ha Thach, Luong Thi Thanh Viet, Phan Thi Huyen, Pham Thi Ngoc Dung
    • Methodology
      Pham Thi Kim Thanh, Nguyen Ha Thach, Luong Thi Thanh Viet, Phan Thi Huyen
    • Project administration
      Pham Thi Kim Thanh
    • Resources
      Pham Thi Kim Thanh, Nguyen Ha Thach, Nguyen Thi Minh Thuy
    • Validation
      Pham Thi Kim Thanh, Nguyen Ha Thach, Nguyen Thi Minh Thuy, Luong Thi Thanh Viet, Phan Thi Huyen, Pham Thi Ngoc Dung
    • Writing – original draft
      Pham Thi Kim Thanh, Nguyen Ha Thach, Nguyen Thi Minh Thuy, Luong Thi Thanh Viet, Phan Thi Huyen, Pham Thi Ngoc Dung
    • Writing – review & editing
      Pham Thi Kim Thanh, Nguyen Ha Thach
    • Data curation
      Nguyen Ha Thach, Nguyen Thi Minh Thuy, Luong Thi Thanh Viet, Phan Thi Huyen, Pham Thi Ngoc Dung
    • Software
      Nguyen Ha Thach, Phan Thi Huyen, Pham Thi Ngoc Dung
    • Supervision
      Nguyen Ha Thach
    • Visualization
      Nguyen Ha Thach
    • Formal Analysis
      Nguyen Thi Minh Thuy, Luong Thi Thanh Viet, Phan Thi Huyen, Pham Thi Ngoc Dung