Table 2.
Predictors of interest
| ID | Predictor name | Value(s) | Type |
|---|---|---|---|
| P_Q1_3C | Gender | female (1), male (2), other (3) | ℤ |
| P_Q2_s | Team size | 0,...,41 | ℕ |
| P_Q3_5C | Team constellation | exactly same (1), mostly same (2), changed team but same employment (3), changed employment (4), not part of a team (5) | ℤ |
| P_Q4_3C | Domain | IT (1), Embedded Systems (2), Others (3) | ℤ |
| P_Q5_3C | Continent | Europe (1) , North America (2) , Asia (3) | ℤ |
| P_Q6_3C | Role | Technical (1), Management (2), Agile (3) | ℤ |
| P_Q7_s | Years of experience | 0,...,30 | ℕ |
| moP_Q9_1_5L | Remote work before | never remotely (1),..., never at office (5) | O |
| moP_Q10_1_5L | Remote work now | never remotely (1),..., never at office (5) | O |
| P_Q11_7C | Reason | Recommendation from company (1), government (2), company & government (3); Enforcement by company (4), government (5), company & government (6); My own choice (7) | ℤ |
| moP_Q12_1_7L | Forced | strongly disagree (1),..., strongly agree (7) | O |
From left to right, ID (encoding used in our model), predictor name, the values that can be used, and type. For type, ℕ indicates a natural number, O indicates ordered (categorical) data, and ℤ indicates an integer for categorical data