Table 3 Measurement model results.

From: Understanding college students’ acceptance of machine translation in foreign language learning: an integrated model of UTAUT and task-technology fit

Latent constructs

Items

Cronbach’s α

Factor loadings

VIF

CR

AVE

Performance expectancy

PE1

0.872

0.897

2.622

0.919

0.794

PE2

0.898

2.108

PE3

0.878

1.965

Effort expectancy

EE1

0.839

0.887

2.079

0.944

0.757

EE2

0.872

2.087

EE3

0.850

1.826

Social influence

SI1

0.812

0.920

2.005

0.859

0.715

SI2

0.890

2.061

SI3

0.712

1.548

Attitude

ATT1

0.807

0.981

2.029

0.856

0.642

ATT2

0.703

1.631

ATT3

0.774

1.762

Experience

Experience 1

0.825

0.871

2.423

0.906

0.732

Experience 2

0.881

1.611

Experience 3

0.813

2.090

Task-technology fit

TTF1

0.869

0.915

2.295

0.894

0.790

TTF2

0.887

2.282

TTF3

0.863

2.284

Behavioral intention

BI1

0.855

0.898

2.496

0.939

0.772

BI2

0.856

2.265

BI3

0.882

1.862

Use behavior

UB1

0.848

0.891

2.845

0.935

0.764

UB2

0.894

2.068

UB3

0.894

1.935

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