Table 3

Results of the hierarchical regression analysis

VariableInnovative work behavior
Model 1Model 2Model 3Model 4Model 5Model 6
β (SE)β (SE)β (SE)β (SE)β (SE)β (SE)
Gender0.073 (0.052)0.087* (0.044)0.083** (0.039)0.085** (0.039)0.092** (0.038)0.093** (0.038)
Age−0.018 (0.034)0.049 (0.029)0.011 (0.026)0.014 (0.026)0.006 (0.025)0.008 (0.025)
Education0.074 (0.035)0.025 (0.030)0.005 (0.027)0.010 (0.026)0.012 (0.026)0.016 (0.026)
Job Position0.041 (0.034)0.041 (0.028)0.036 (0.025)0.038 (0.025)0.036 (0.025)0.038 (0.025)
Tenure−0.007 (0.023)0.001 (0.019)−0.046 (0.017)−0.049 (0.017)−0.035 (0.017)−0.038 (0.017)
Experience0.264*** (0.052)0.158*** (0.045)0.121*** (0.041)0.115*** (0.041)0.140*** (0.039)0.128*** (0.040)
AIL 0.526*** (0.043)0.302*** (0.045)0.313*** (0.045)0.143*** (0.051)0.154*** (0.051)
OE  0.439*** (0.040)0.433*** (0.040)  
AIL x OE   0.083** (0.056)  
MC    0.559*** (0.057)0.558*** (0.057)
AIL x MC     0.086** (0.065)
R20.0860.3430.4760.4830.5040.512
ΔR20.0860.2570.1330.0070.1610.007
F9.252***44.161***67.140***61.201***75.201***68.684***

Note(s): n = 621; *p < 0.05, **p < 0.01, ***p < 0.001; Experience = Experience of AI related training, AIL = AI Literacy, IB=Innovative Behavior, OE=Occupational Expertise, MC = Metacognition

Source(s): Authors’ own work

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