Table 4.
Working/studying | Grocery shopping | Non-grocery shopping | Eating | Recreation | Social | |
---|---|---|---|---|---|---|
Socio-demographics | ||||||
Age | −0.191(−1.80)⁎⁎⁎ | −0.316 (−2.91)⁎ | −0.421 (−3.97)⁎ | −0.318 (−3.10)⁎ | −0.560 (−5.31)⁎ | |
Gender | ||||||
Education level | ||||||
Income | ||||||
Studentsa | ||||||
Full-time workersa | ||||||
Part-time workersa | 0.479 (1.71)⁎⁎⁎ | |||||
Household characteristics | ||||||
No. of cars | 0.146 (1.66)⁎⁎⁎ | |||||
No. of motorcycles | 0.238 (2.75)⁎ | 0.153 (1.84)⁎⁎⁎ | ||||
No. of family members | ||||||
Spatial characteristic | ||||||
Big citiesb | −0.427 (−1.67)⁎⁎⁎ | |||||
Medium and small citiesb | ||||||
Perception of COVID-19 | 0.205 (1.73)⁎⁎⁎ | |||||
Virtual activities during the outbreak | ||||||
e-Learning/e-working | 0.109 (2.25)⁎⁎ | N/A | N/A | N/A | N/A | N/A |
Grocery e-shopping | N/A | N/A | N/A | N/A | N/A | |
Non-grocery e-shopping | N/A | N/A | 0.292 (4.43)⁎ | N/A | N/A | N/A |
Fresh food delivery | N/A | N/A | N/A | 0.107 (2.10)⁎⁎ | N/A | N/A |
Movies streaming | N/A | N/A | N/A | N/A | 1.25 (2.37)⁎⁎ | N/A |
Threshold | ||||||
τ1 | −0.650 | −0.089 | −0.499 | −0.058 | −0.351 | −0.991 |
τ2 | 1.290 | 2.301 | 2.251 | 1.442 | 1.119 | 0.219 |
Statistics | ||||||
No. of data | 834 | 834 | 834 | 834 | 834 | 834 |
No. of estimated parameters | 16 | 16 | 16 | 16 | 16 | 15 |
Rho-square | 0.149 | 0.231 | 0.353 | 0.225 | 0.148 | 0.143 |
Final log-likelihood | −884.965 | −833.895 | −764.09 | −870.812 | −903.311 | −880.021 |
AIC | 1799.929 | 1697.790 | 1558.179 | 1771.624 | 1836.622 | 1788.041 |
BIC | 1870.823 | 1768.684 | 1629.073 | 1842.518 | 1907.515 | 1854.209 |
Means non-workers are a reference category.
Means the Greater Jakarta is a reference category.
Means p < 0.01.
Means 0.01 ≤ p < 0.05.
Means 0.05 ≤ p < 0.1; values in parentheses are t-test values; empty cells mean p ≥ 0.1; N/A means a variable is not considered in the model.