Testing the Moderator Effect in the Structural Model of Usage Intention


Parameter

SE

SE-SE

Mean

Bias

SE-Bias

TL1

<---

Tien_Loi

.029

.001

.823

-.001

.001

YD1

<---

Health

.019

.000

.798

.000

.001

YD2

<---

Health

.017

.000

.808

.001

.001

YD3

<---

Health

.021

.000

.803

.000

.001

DK4

<---

Condition

.030

.001

.766

.000

.001

DK3

<---

Condition

.035

.001

.788

-.002

.001

DK2

<---

Condition

.023

.001

.857

-.001

.001

DK1

<---

Condition

.021

.000

.840

-.001

.001

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Testing the Moderator Effect in the Structural Model of Usage Intention

APPENDIX 11: TESTING THE EFFECT OF MODERATORS IN THE SEM STRUCTURAL MODEL OF USE INTENTION

Intention model using Estimates (Group number 1 - Default model)

Scalar Estimates (Group number 1 - Default model) Maximum Likelihood Estimates

Regression Weights: (Group number 1 - Default model)



Estimate

SE

CR

P

Label

Health

<---

Effective

,102

,025

4,123

***

Health

<---

No_Luc

,168

,026

6,541

***

Health

<---

Society

,151

,022

6,974

***

Health

<---

Mask

,214

,025

8,622

***

Health

<---

Condition

,158

,025

6,397

***

Health

<---

Advantages

,201

,023

8,798

***

Health

<---

GiT_HQ

,014

,007

-1,995

,046

Health

<---

GiT_NL

-,017

,007

2,308

,021

Health

<---

GiT_XH

-,022

,008

-2,855

,004

Health

<---

GiT_BM

-,001

,007

-,189

,850

Health

<---

Age_HQ

-,025

,007

3,398

***

Health

<---

Age

,021

,007

-2,883

,004

Health

<---

Age_DK

,014

,007

1,949

,051

Health

<---

Age

-,009

,007

-1,300

,194

Health

<---

Age

-,003

,007

-,439

,661

Health

<---

KN_DK

-,002

,008

,273

,785

Health

<---

KN_XH

,013

,008

-1,519

,129

Health

<---

KN_NL

-,013

,008

1,727

,084

HQ5

<---

Effective

1,000




HQ4

<---

Effective

1,004

,048

20,864

***

HQ3

<---

Effective

1,030

,045

23,039

***

HQ2

<---

Effective

,909

,047

19,525

***



Estimate

SE

CR

P

Label

HQ1

<---

Effective

,966

,048

20,072

***

NL5

<---

No_Luc

1,000




NL4

<---

No_Luc

,972

,052

18,704

***

NL3

<---

No_Luc

1,020

,054

18,975

***

NL2

<---

No_Luc

,997

,052

19,331

***

NL1

<---

No_Luc

1,022

,052

19,821

***

XH5

<---

Society

1,000




XH4

<---

Society

,967

,040

23,996

***

XH3

<---

Society

,895

,037

24,317

***

XH2

<---

Society

,960

,037

25,803

***

XH1

<---

Society

,940

,037

25,064

***

DK4

<---

Condition

1,000




DK3

<---

Condition

,955

,050

19,010

***

DK2

<---

Condition

1,001

,048

20,822

***

DK1

<---

Condition

1,056

,052

20,393

***

BM4

<---

Mask

1,000




BM3

<---

Mask

,954

,052

18,461

***

BM2

<---

Mask

1,066

,052

20,524

***

BM1

<---

Mask

1,056

,052

20,276

***

TL4

<---

Advantages

1,000




TL3

<---

Advantages

,879

,040

21,857

***

TL2

<---

Advantages

,920

,038

24,363

***

TL1

<---

Advantages

,952

,040

24,017

***

YD1

<---

Health

1,000




YD2

<---

Health

1,043

,048

21,639

***

YD3

<---

Health

1,046

,049

21,505

***

Standardized Regression Weights: (Group number 1 - Default model)



Estimate

Health

<---

Effective

,138

Health

<---

No_Luc

,213

Health

<---

Society

,225

Health

<---

Mask

,271

Health

<---

Condition

,199

Health

<---

Advantages

,291

Health

<---

GiT_HQ

-,045

Health

<---

GiT_NL

,052

Health

<---

GiT_XH

-,064

Health

<---

GiT_BM

-,004

Health

<---

Age_HQ

,076

Health

<---

Age

-,064

Health

<---

Age_DK

,044

Health

<---

Age

-,029

Health

<---

Age

-,010

Health

<---

KN_DK

,006

Health

<---

KN_XH

-,034

Health

<---

KN_NL

,039

HQ5

<---

Effective

,821

HQ4

<---

Effective

,789

HQ3

<---

Effective

,849

HQ2

<---

Effective

,751

HQ1

<---

Effective

,767

NL5

<---

No_Luc

,764

NL4

<---

No_Luc

,778

NL3

<---

No_Luc

,788

NL2

<---

No_Luc

,802

NL1

<---

No_Luc

,820



Estimate

XH5

<---

Society

,880

XH4

<---

Society

,802

XH3

<---

Society

,808

XH2

<---

Society

,836

XH1

<---

Society

,822

DK4

<---

Condition

,766

DK3

<---

Condition

,790

DK2

<---

Condition

,859

DK1

<---

Condition

,842

BM4

<---

Mask

,783

BM3

<---

Mask

,760

BM2

<---

Mask

,835

BM1

<---

Mask

,826

TL4

<---

Advantages

,871

TL3

<---

Advantages

,776

TL2

<---

Advantages

,831

TL1

<---

Advantages

,824

YD1

<---

Health

,800

YD2

<---

Health

,810

YD3

<---

Health

,807


Covariances: (Group number 1 - Default model)



Estimate

SE

CR

P

Label

Effective

<-->

No_Luc

,301

,033

9,180

***

Effective

<-->

Society

,361

,037

9,703

***

Effective

<-->

Condition

,164

,029

5,700

***

Effective

<-->

Mask

,194

,030

6,550

***

Effective

<-->

Advantages

,294

,035

8,453

***

No_Luc

<-->

Society

,310

,035

8,915

***

No_Luc

<-->

Condition

,192

,028

6,792

***



Estimate

SE

CR

P

Label

No_Luc <-->

Mask

,177

,028

6,320

***

No_Luc <-->

Advantages

,222

,032

6,975

***

Society <-->

Condition

,254

,033

7,659

***

Society <-->

Mask

,233

,033

7,104

***

Society <-->

Advantages

,273

,037

7,447

***

Condition <-->

Mask

,215

,029

7,374

***

Condition <-->

Advantages

,287

,034

8,546

***

Mask <-->

Advantages

,281

,034

8,392

***


Correlations: (Group number 1 - Default model)



Estimate

Effective <-->

No_Luc

,529

Effective <-->

Society

,536

Effective <-->

Condition

,289

Effective <-->

Mask

,341

Effective <-->

Advantages

,452

No_Luc <-->

Society

,492

No_Luc <-->

Condition

,361

No_Luc <-->

Mask

,331

No_Luc <-->

Advantages

,363

Society <-->

Condition

,403

Society <-->

Mask

,368

Society <-->

Advantages

,377

Condition <-->

Mask

,402

Condition <-->

Advantages

,470

Mask <-->

Advantages

,459

Model 2


Estimates (Group number 1 - Default model) Scalar Estimates (Group number 1 - Default model)

Maximum Likelihood Estimates


Regression Weights: (Group number 1 - Default model)



Estimate

SE

CR

P

Label

Health

<---

Effective

,105

,025

4,211

***

Health

<---

No_Luc

,172

,026

6,655

***

Health

<---

Society

,142

,022

6,615

***

Health

<---

Mask

,212

,025

8,550

***

Health

<---

Condition

,165

,025

6,670

***

Health

<---

Advantages

,201

,023

8,802

***

Health

<---

GiT_HQ

,017

,007

-2,350

,019

Health

<---

GiT_NL

-,020

,007

2,666

,008

Health

<---

GiT_XH

-,023

,008

-3,000

,003

Health

<---

Age_HQ

-,026

,007

3,608

***

Health

<---

Age

,023

,007

-3,037

,002

HQ5

<---

Effective

1,000




HQ4

<---

Effective

1,004

,048

20,863

***

HQ3

<---

Effective

1,030

,045

23,039

***

HQ2

<---

Effective

,909

,047

19,525

***

HQ1

<---

Effective

,966

,048

20,074

***

NL5

<---

No_Luc

1,000




NL4

<---

No_Luc

,972

,052

18,707

***

NL3

<---

No_Luc

1,020

,054

18,980

***

NL2

<---

No_Luc

,997

,052

19,335

***

NL1

<---

No_Luc

1,022

,052

19,825

***

XH5

<---

Society

1,000




XH4

<---

Society

,967

,040

23,994

***

XH3

<---

Society

,895

,037

24,317

***

XH2

<---

Society

,960

,037

25,797

***

XH1

<---

Society

,939

,037

25,064

***

DK4

<---

Condition

1,000






Estimate

SE

CR

P

Label

DK3

<---

Condition

,955

,050

19,017

***

DK2

<---

Condition

1,001

,048

20,828

***

DK1

<---

Condition

1,056

,052

20,399

***

BM4

<---

Mask

1,000




BM3

<---

Mask

,954

,052

18,453

***

BM2

<---

Mask

1,066

,052

20,522

***

BM1

<---

Mask

1,056

,052

20,275

***

TL4

<---

Advantages

1,000




TL3

<---

Advantages

,879

,040

21,855

***

TL2

<---

Advantages

,920

,038

24,368

***

TL1

<---

Advantages

,952

,040

24,017

***

YD1

<---

Health

1,000




YD2

<---

Health

1,043

,048

21,639

***

YD3

<---

Health

1,046

,049

21,497

***


Standardized Regression Weights: (Group number 1 - Default model)



Estimate

Health

<---

Effective

,141

Health

<---

No_Luc

,217

Health

<---

Society

,213

Health

<---

Mask

,269

Health

<---

Condition

,208

Health

<---

Advantages

,291

Health

<---

GiT_HQ

-,053

Health

<---

GiT_NL

,060

Health

<---

GiT_XH

-,067

Health

<---

Age_HQ

,081

Health

<---

Age

-,068

HQ5

<---

Effective

,821

HQ4

<---

Effective

,789

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