Discriminant validity, convergent validity, and tests of model fit
| Mode A composite constructs assessment | Individual drivers | Age | Sector | Gender | |
|---|---|---|---|---|---|
| Individual drivers | Mode A | n.a | −0.129 | 0.058 | −0.001 |
| Age | 0.140 | n.a | −0.064 | 0.044 | |
| Sector | 0.068 | 0.064 | n.a | −0.009 | |
| Gender | 0.018 | 0.044 | 0.009 | n.a | |
| Mode A composite constructs assessment | Individual drivers | Age | Sector | Gender | |
|---|---|---|---|---|---|
| Individual drivers | Mode A | −0.129 | 0.058 | −0.001 | |
| Age | 0.140 | −0.064 | 0.044 | ||
| Sector | 0.068 | 0.064 | −0.009 | ||
| Gender | 0.018 | 0.044 | 0.009 | ||
| Mode B composite construct assessment convergent validity | |
|---|---|
| Construct (≥0.8)* | Path coefficient |
| Behavioral intention | 0.7999 |
| Attitude | 0.6557 |
| Mode B composite construct assessment convergent validity | |
|---|---|
| Construct (≥0.8)* | Path coefficient |
| Behavioral intention | 0.7999 |
| Attitude | 0.6557 |
| Estimated model | ||
|---|---|---|
| Value | HI99 | |
| SRMR | 0.052 | 0.072 |
| dULS | 0.246 | 0.878 |
| dG | 0.127 | 0.317 |
| Saturated model | ||
| SRMR | 0.044 | 0.067 |
| dULS | 0.179 | 0.277 |
| dG | 0.177 | 0.285 |
| Estimated model | ||
|---|---|---|
| Value | HI99 | |
| SRMR | 0.052 | 0.072 |
| dULS | 0.246 | 0.878 |
| dG | 0.127 | 0.317 |
| SRMR | 0.044 | 0.067 |
| dULS | 0.179 | 0.277 |
| dG | 0.177 | 0.285 |
Note(s): SRMR stands for standardized root mean squared residual. dULS stands for unweighted least squares discrepancy. dG stands for geodesic discrepancy. HI99 stands for the 99th percentile bootstrap base. Fornell-Larker criterion for all constructs below the diagonal (included). HTMT ratio for Mode A constructs above the diagonal. n.a.: non-applicable. HTMT inference confidence intervals (2.5%–97.5%) underneath HTMT values, extracted from a two-tailed bootstrapping procedure. * (Hair et al., 2017)
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