Enforcement of consumer rights protection laws and intention to reuse digital financial services among Generation Z youth: Empirical evidence from Vietnamese commercial banks

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Digital financial services are crucial in boosting the competitive edge of businesses and economies in numerous developing nations. This study aims to explore the factors that affect consumers’ perceptions of the implementation of consumer protection laws and their willingness to continue using digital financial services. Data were collected through interviews with 689 Gen Z consumers (born after 1996) who have used digital financial services in Vietnamese commercial banks. The results of the partial least square – structural equation modeling indicate that six factors influence attitudes toward the enforcement of consumer protection laws, in descending order: perceived benefits, understanding of legal regulations, perceived asymmetry, perceived risk, understanding of technology and digital finance, and understanding of dispute resolution. Additionally, attitudes toward law enforcement, as well as understanding of technology and digital finance, positively impact consumers’ intention to reuse digital financial services, while perceived risk has the opposite effect. Furthermore, all six independent factors impact the intention to reuse digital financial services through the mediating role of attitudes toward the enforcement of consumer protection laws. The study’s findings also lay the groundwork for policy recommendations for legislative authorities and strategic guidance for service providers and consumers in emerging markets in the future.

Acknowledgment
This study is the result of collaboration between researchers from the University of Law, Hue University, and School of Business and Economics, Duy Tan University. The authors would like to thank both institutions for their support and facilitation in the publication of this research. This study was conducted under project code DHH2024-12-85, Decision No. 298/QĐ-ĐHH dated March 27, 2024, issued by the Director of Hue University.

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    • Figure 1. Model and hypotheses
    • Figure 2. PLS-SEM results
    • Table 1. Statistics of indicators measuring model reliability
    • Table 2. Discriminant reliability
    • Table 3. Inner VIF test results
    • Table 4. Statistics of the model’s predictive ability
    • Table 5. Results of testing hypotheses with direct effects
    • Table 6. Results of testing the hypotheses with indirect effects
    • Table A1. Descriptive statistics about the samples
    • Table B1. Measurement summary
    • Conceptualization
      Lanh Cao Dinh, Hai Phan Thanh
    • Data curation
      Lanh Cao Dinh, Hai Phan Thanh
    • Formal Analysis
      Lanh Cao Dinh, Hai Phan Thanh
    • Investigation
      Lanh Cao Dinh, Hai Phan Thanh
    • Methodology
      Lanh Cao Dinh, Hai Phan Thanh
    • Project administration
      Lanh Cao Dinh, Hai Phan Thanh
    • Resources
      Lanh Cao Dinh, Hai Phan Thanh
    • Software
      Lanh Cao Dinh, Hai Phan Thanh
    • Supervision
      Lanh Cao Dinh, Hai Phan Thanh
    • Validation
      Lanh Cao Dinh, Hai Phan Thanh
    • Visualization
      Lanh Cao Dinh, Hai Phan Thanh
    • Writing – original draft
      Lanh Cao Dinh, Hai Phan Thanh
    • Writing – review & editing
      Lanh Cao Dinh, Hai Phan Thanh