Table 3 Results for hypothesized direct and indirect effects.

From: Generative AI adoption and employee outcomes: a conservation of resources perspective on job crafting, career commitment, and the moderating role of liking of AI

Paths

Effect

SE

95% CI

Direct effects (in AMOS)

 GenAI adoption → seeking resources

0.213

0.039

[0.134, 0.295]

 GenAI adoption → seeking challenges

0.207

0.049

[0.117, 0.297]

 GenAI adoption → optimizing demands

0.241

0.043

[0.141, 0.344]

Indirect effects (in SPSS)

 GenAI adoption → seeking resources → career commitment

0.049

0.014

[0.026, 0.079]

 GenAI adoption → seeking challenges → career commitment

0.042

0.013

[0.018, 0.070]

 GenAI adoption → optimizing demands → career commitment

0.033

0.013

[0.012, 0.063]

Sequentially indirect effects (in SPSS)

 GenAI adoption → seeking resources → career commitment → voice quality

0.020

0.008

[0.007, 0.038]

 GenAI adoption → seeking challenges → career commitment → voice quality

0.017

0.007

[0.006, 0.033]

 GenAI adoption → optimizing demands → career commitment → voice quality

0.011

0.006

[0.003, 0.025]

 GenAI adoption → seeking resources → career commitment → employee cyberloafing

−0.026

0.008

[−0.044, −0.012]

 GenAI adoption → seeking challenges → career commitment → employee cyberloafing

−0.021

0.008

[−0.039, −0.008]

 GenAI adoption → optimizing demands → career commitment → employee cyberloafing

−0.019

0.008

[−0.037, −0.007]

 GenAI adoption → seeking resources → career commitment → cheating behavior

−0.013

0.006

[−0.027, −0.004]

 GenAI adoption → seeking challenges → career commitment → cheating behavior

−0.011

0.004

[−0.019, −0.004]

 GenAI adoption → optimizing demands → career commitment → cheating behavior

−0.009

0.004

[−0.018, −0.003]

  1. N = 291.
  2. SE standard error, CI confidence interval. Direct or indirect effect was significant if the confidence interval did not contain zero.
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