TABLE 2.
Multiple linear regression analysis for work from home (WFH) predicting higher productivity in WFH compared to work on-site (H1).
| Variable | B | SE B | β | t | p |
| Age (years) | –0.008 | 0.008 | –0.066 | –1.019 | 0.309 |
| Gender (1 = female, 2 = male) | –0.384 | 0.167 | −0.154* | –2.302 | 0.022 |
| Partnership (0 = no, 1 = yes) | 0.034 | 0.197 | 0.011 | 0.170 | 0.865 |
| Leadership (0 = no, 1 = yes) | –0.060 | 0.233 | –0.018 | –0.259 | 0.796 |
| Part-time work (%FTE) | 0.005 | 0.006 | 0.061 | 0.786 | 0.433 |
| Children | 0.078 | 0.081 | 0.070 | 0.955 | 0.340 |
| Qualitative work demands | –0.059 | 0.088 | –0.048 | –0.675 | 0.500 |
| Quantitative work demands | 0.146 | 0.087 | 0.122 | 1.683 | 0.094 |
| WFH (# days/month) | 0.063 | 0.015 | 0.267*** | 4.113 | <0.001 |
| Total R2 | 0.141*** | <0.001 | |||
| F(9,224) = 4.094 |
N = 234; *p < 0.05, ***p < 0.001.