Table 5.
Results of hierarchical multiple regression analysis with task proactivity at T2 as Dependent Variable (Study 2).
| Dependent variable: task proactivity T2 | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| EOE as moderator | LST as moderator | AES as moderator | |||||||
| B | SE | β | B | SE | β | B | SE | β | |
| Step 1: controls | |||||||||
| Age | −0.02 | 0.01 | −0.17 | −0.02 | 0.01 | −0.17 | −0.02 | 0.01 | −0.17 |
| Gender | −0.10 | 0.19 | −0.05 | −0.10 | 0.19 | −0.05 | −0.10 | 0.19 | −0.05 |
| R 2 | 0.031 | 0.031 | 0.031 | ||||||
| Step 2: main effects | |||||||||
| Job complexity T1 | 0.12 | 0.09 | 0.12 | 0.12 | 0.09 | 0.12 | 0.12 | 0.09 | 0.12 |
| EOE T1 | 0.00 | 0.13 | 0.00 | 0.00 | 0.13 | 0.00 | 0.00 | 0.13 | 0.00 |
| LST T1 | −0.06 | 0.10 | −0.06 | −0.06 | 0.10 | −0.06 | −0.06 | 0.10 | −0.06 |
| AES T1 | 0.17 | 0.12 | 0.13 | 0.17 | 0.12 | 0.13 | 0.17 | 0.12 | 0.13 |
| R 2 | 0.068 | 0.068 | 0.068 | ||||||
| Step 3: interaction | |||||||||
| Job complexity T1 * EOE T1 | −0.21 | 0.12 | −0.16 | ||||||
| Job complexity T1 * LST T1 | 0.16 | 0.09 | 0.16 | ||||||
| Job complexity T1 * AES T1 | 0.26 | 0.11 | 0.22* | ||||||
| R 2 | 0.090 | 0.092 | 0.114 | ||||||
N = 126. T1 = time 1, T2 = time 2. Gender was coded 0 = male, 1 = female. The predictors were mean-centered. B, unstandardized regression coefficient and SE, standard error. R2 = proportion of variance explained in the criterion.
*
p ≤ 0.05.