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Table 5 Structural model estimation (PLSc)

From: The influence of CEO’s financial literacy on SMEs technological innovation: the mediating effects of MCS and risk-taking

Paths

Path

t-value

p-value

95% confidence interval

f2

VIF

CEO’s financial literacy (CFL) → Tech. Innovation

− 0.048

0.543

0.293

− 0.193

0.097

0.001

1.987

CEO’s financial literacy (CFL) → Risk-taking (RT)

− 0.009

0.083

0.467

− 0.182

0.160

0.000

1.987

Risk-taking (RT) → Tech. Innovation

0.359

5.278

0.000

0.247

0.471

0.157

1.282

CEO’s Financial Literacy (CFL) → Management Control System (MCS)

0.674

13.881

0.000

0.596

0.755

0.863

1.064

Management Control System (MCS) → Tech. Innovation

0.320

3.249

0.001

0.158

0.482

0.065

2.33

Management Control System (MCS) → Risk-taking (RT)

0.490

5.370

0.000

0.345

0.643

0.151

2.026

Control variables significant paths only

       

Size → Risk-taking (RT)

− 0.089

1.688

0.046

− 0.175

− 0.003

  

Construction → Tech. innovation

− 0.181

2.768

0.003

− 0.288

− 0.073

  

Indirect effects

Path

t-value

p-value

95% confidence interval

 

CFL → MCS → Innovation H1

0.216

3.197

0.001

0.103

0.329

Supported

CFL → MCS → Risk-taking H2

0.330

4.780

0.000

0.223

0.446

Supported

CFL → Risk-taking → Tech. Innovation H3

− 0.001

0.042

0.473

− 0.068

0.057

Not supported

CFL → MCS → Risk-taking → Tech. Innovation H4

0.118

3.47

0.000

0.072

0.181

Supported

Total effects

Path

t-value

p-value

95% confidence interval

 

CFL → Tech. innovation

0.283

3.966

0.000

0.171

0.411

 

CFL → Risk-taking

0.322

5.023

0.000

0.206

0.418

 

MCS → Tech. innovation

0.496

5.723

0.000

0.336

0.63

 

Endogenous variable

Adjusted R2

Q2

 

Technological Innovation

0.346

0.160

 

Risk-taking

0.202

0.102

 

SCI

0.498

0.225

 
  1. VIF inner model variance inflation factors. Q2 Stone-Geisser Q2
  2. Significance, t statistic and 95% bias-corrected confidence interval performed by 10,000 rep. Bootstrapping procedure