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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
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