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Table 4 Pattern matrix of the service quality attribute perceptions included as the indicators for the latent variables in structural equation model

From: Which factors affect willingness-to-pay for automated vehicle services? Evidence from public road deployment in Stockholm, Sweden

Pattern Matrixa
  Factor
1 2 3 4 5
SafetyWithoutSteward    0.579   
Safety_Pedestrian    0.758   
Safety_OnRoad    0.836   
Cybersecurity_Hacked     1.004  
Cybersecurity_GPS     0.663  
RideComfort_Tech      0.865
RideComfort_Facilities      0.726
OverallRideComfort      0.411
Time_RegularPublicBus   0.522    
Time_Metro   0.903    
Time_Train   0.802    
Time_Car   0.601    
Fare_RegularPublicBus 0.803     
Fare_Metro 0.904     
Fare_Train 0.854     
  1. Extraction Method: Maximum Likelihood
  2. Rotation Method: Promax with Kaiser Normalization
  3. aRotation converged in 5 iterations