Factors affecting Gen Z’s intention to use QR Pay in Vietnam after Covid-19


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The objective of this study was to examine the determinants that impact the inclination of Generation Z individuals to use QR Pay in the context of Vietnam following the COVID-19 pandemic. In order to gather the necessary data, this study conducted a survey among a sample of 415 individuals who were customers of the relevant service or product. The survey was conducted using the Google Forms platform from September 2022 to January 2023, employing a convenience sampling approach. This paper constructed a research model utilizing the technology acceptance model (TAM) and unified theory of acceptance and use of technology (UTAUT) frameworks. Then, it analyzed the data using partial least squares structural equation modeling (PLS-SEM). Principal findings indicate that attitude, COVID-19 impact, personal innovativeness, perceived compatibility, perceived ease of use, perceived usefulness, and social influence are significant determinants of Vietnamese Gen Z’s intention to adopt QR Pay. This study provides valuable insights into the factors affecting Gen Z customers’ behavior toward technology adoption in Vietnam under the shadow of the COVID-19 pandemic. The findings can benefit business managers and policymakers, as they can better understand the factors that influence customers’ technology adoption and develop effective strategies to enhance customers’ acceptance of technology.

The author wishes to convey heartfelt gratitude to all consumers who took the time to complete the survey. Furthermore, heartfelt gratitude is extended to all parties involved, as well as the Ho Chi Minh City University of Banking, for their incredible support and help, which contributed considerably to the completion of this study.

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    • Figure 1. Research model
    • Figure 2. Results of PLS-SEM model analysis
    • Table 1. Demographic characteristics of Gen Z customers participating in the survey
    • Table 2. Descriptive statistics of nine variables
    • Table 3. Testing the reliability level of variables in detail
    • Table 4. Testing the reliability, stability, and discriminant validity of variables
    • Table 5. Hypotheses testing results
    • 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