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AI anxiety and knowledge payment: the roles of perceived value and self-efficacy
Jinsong Chen1, Miao He1, Jinhua Sun2
1Guizhou University of Finance and Economics, Guiyang, China.
Background:
The integration of Artificial Intelligence (AI) into daily life raises significant challenges and uncertainties, notably concerning job security and skill relevance. This has led to the emergence of 'AI anxiety'-a stress response to potential impacts of AI on individuals' futures. This study examines AI anxiety's effects on individuals' willingness to pay for knowledge, focusing on the roles of perceived value and self-efficacy.
Methods:
This study consisted of two experiments. Study 1 utilized a one-factor between-subjects design (AI anxiety vs. neutral emotion) with 297 participants to examine the mediating role of perceived value in the relationship between AI anxiety and willingness to pay for knowledge. Study 2 employed a 2 × 2 between-subjects design (AI anxiety vs. neutral emotion )×self-efficacy (high vs. low) with 506 participants to investigate the moderating effect of self-efficacy on this relationship.
Results:
Study 1 showed that AI anxiety significantly increases the willingness to pay for knowledge, with perceived value partially mediating this effect. Study 2 demonstrated that self-efficacy moderates the influence of AI anxiety: higher self-efficacy levels weaken, whereas lower levels strengthen, the willingness to pay for knowledge. Furthermore, self-efficacy also negatively moderates the effect of AI anxiety on perceived value.
Conclusions:
AI anxiety positively influences payment for knowledge, with critical roles for perceived value and self-efficacy. These findings offer a new framework for understanding AI anxiety's impact on consumer behavior and provide actionable insights for platforms and policymakers.
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