Model building, variable types and determination of hypotheses

Points to consider in scale adaptation and data collection processes

Cleaning the collected data, determining the commands (prompts) and performing practical analysis with Artificial Intelligence

Factor loadings, Cronbach’s Alpha, Composite Reliability, AVE

Correlation Analyses (Fornell-Larcker, HTMT criterion)

Testing of hypotheses, path coefficients, t-statistics, p-values, R² values

Formatting SEM results, tables and figures

Interpretation of SEM results