Table 8.
Configural effects for predicting high and low usage behaviour of m-health
| Configural Models for predicting high usage behaviour of m-health | Configural Models for predicting low usage behaviour of m-health | ||||||
|---|---|---|---|---|---|---|---|
| UB = f (BI, SQ, QL and HA) | ~ UB = f (BI, SQ, QL and HA) | ||||||
| Configural Models (Sufficient causal recipes) | Raw coverage | Unique Coverage | Consistency | Configural Models (Sufficient causal recipes) | Raw coverage | Unique Coverage | Consistency |
| Model 1: BIN*HA*QL | 0.913 | 0.287 | 0.879 | Model 1: ~ BIN* ~ SQ* ~ HA | 0.450 | 0.010 | 0.972 |
| Model 2: BIN*HA*SQ | 0.616 | 0.042 | 0.766 | ||||
| Solution coverage: 0.971 | Solution coverage: 0.711 | ||||||
| Solution consistency: 0.854 | Solution consistency: 0.907 | ||||||
BI: Behavioural intention towards m-health, SQ: Service quality, QL: Quality of life, HA: Habit and UB: Use behaviour of m-health