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innovative and transformative, they are more motivated to adopt it meaningfully (Bonzanini
et al., 2020; Kottara et al., 2024). From the above arguments, the following hypothesis is
proposed:
H6: Perceived digital innovation positively affects teaching quality.
2.4. Research methodology
This study employed a quantitative research design to examine the factors influencing
the teaching quality of accounting lecturers in the context of digital transformation. The
target population consisted of accounting lecturers working at universities, colleges, and
other educational institutions offering accounting programs in Ho Chi Minh City. However,
due to the absence of a comprehensive sampling frame and practical constraints in
accessing respondents, a convenience sampling method was adopted through professional
networks and academic communication channels. While this approach is appropriate for
exploratory research, it may limit the generalizability of the findings. The questionnaire was
designed using Google Forms and distributed via email and other relevant communication
channels. A total of 159 valid responses were collected and used for the final analysis. This
sample size is considered adequate for PLS-SEM analysis and consistent with previous
studies in accounting education research.
The research model includes six independent variables: attitude toward technology,
technology experience, perceived digital innovation, perceived ease of use, perceived
usefulness, and institutional support. The dependent variable is teaching quality. Teaching
quality was measured using lecturers’ self-reported perceptions of their teaching
effectiveness in technology-enhanced environments. Although this approach is widely used
in behavioral research, potential self-report bias is acknowledged. Future studies are
recommended to incorporate multiple data sources, such as student evaluations or learning
outcomes, to improve measurement validity.
The measurement scales were developed based on the Technology Acceptance Model
(TAM) and the Theory of Planned Behavior (TPB), and adapted from prior studies related to
digital technology and accounting education, including Rodrigues (2022), Dangi et al. (2023),
Bonzanini et al. (2020), Hruska (2018), Fachrurrozie et al. (2025), Abdo-Salloum and Al-
Mousawi (2025), and Alshammari and Alkhwaldi (2025). All constructs were measured using
a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).
Data were analyzed using SmartPLS with Partial Least Squares Structural Equation
Modeling (PLS-SEM). This method was selected because the study aims to predict and
explore relationships among latent variables, and it is suitable for models with multiple
constructs and moderate sample sizes. The analysis procedure included descriptive statistics,
measurement model evaluation, and structural model assessment. The measurement model
was evaluated based on reliability, convergent validity, and discriminant validity, while the
structural model was assessed using path coefficients, coefficient of determination (R²),
effect size, and predictive relevance.
The sample size satisfies the commonly recommended ten-times rule for PLS-SEM.
Since the dependent variable is influenced by six structural paths, a minimum of 60
observations is required (Hair etal., 2019). With 159 valid responses, the sample size is
considered adequate for the analysis. Furthermore, the use of PLS-SEM is appropriate for
exploratory research in the context of accounting education in Vietnam, where empirical
studies on digital transformation remain limited.
3. Results and discussion
3.1. Sample characteristics
Among the 159 respondents, 40.9% were male and 59.1% were female. The largest
age group was 30–40 years old, accounting for 49.1% of the sample, followed by
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