Table 4.

Hypothesis testing

HypothesesRelationshipsPath coefficientst-StatisticsR2Q2p-ValuesDecision
Direct effect      
H1IQSM → RSM0.2093.626**  0.001**Supported
H2IQSM → T0.3235.737**  0.001**Supported
H3RSM → T0.1442.281**  0.023**Supported
H4IQSM → PI0.0090.095ns  0.924nsNot supported
H5SMPMA → T0.3725.229**  0.001**Supported
H6SMPMA → PI0.2684.497**  0.001**Supported
H7T → PI0.2845.330**  0.001**Supported
Indirect effect      
 IQSM → RSM → T0.0402.018**  0.002**Supported
 IQSM → T → PI0.0924.247**  0.001**Supported
 SMPMA → T → PI0.1063.157**  0.002**Supported
 RSM  0.1440.024  
 T  0.2830.149  
 PI  0.2110.103  
Total effect      
 IQSM → RSM0.2093.416**  0.001** 
 IQSM → T0.3636.527**  0.001** 
 RSM → T0.1442.290**  0.022** 
 IQSM → PI0.1011.112**  0.266ns 
 SMPMA → T0.3725.652**  0.001** 
 SMPMA → PI0.3745.908**  0.001** 
 T → PI0.2845.136**  0.001** 

Notes:

**statistically significant at the 5%; nsnot significant. The rule of thumb for R2 values is as follows: 0.75 for the strong category; 0.50 for the moderate category and 0.25 for the weak category. The rule of thumb value for Q2 > 0 indicates that the model has predictive relevance and the rule of thumb for Q2 < 0 indicates that the model lacks predictive relevance

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