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Byung‐Jik Kim

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Open access Jul 2026

“When artificial intelligence (AI) meets perfectionism”: examining how responsible AI influences knowledge exchanges

As artificial intelligence (AI) permeates modern workplaces, the need for ethical governance, specifically corporate-responsible AI (CRAI), has become paramount. However, empirical research has been hampered by the lack of a validated instrument to assess CRAI from the perspective of employees. To bridge this gap, this study first creates and validates a novel measurement scale for CRAI through a rigorous multi-stage development process. Using this newly developed instrument, we subsequently investigate how CRAI fosters employees’ knowledge-sharing behavior (KSB) by integrating organizational behavior theories and knowledge-based perspectives. Data were collected using a three-wave, time-lagged design from 405 working professionals in South Korea. The findings indicate that CRAI positively influences KSB, with psychological safety serving as a partial mediator. This outcome suggests that employees’ sense of psychological safety acts as a key mechanism for translating ethical AI governance into collaborative knowledge exchange. Furthermore, the results reveal that organizationally prescribed perfectionism (OPP) moderates the relationship between CRAI and psychological safety; specifically, rigid performance demands undermine the trust-building potential of responsible AI practices. This study contributes to the literature by providing a psychometrically sound tool for future CRAI research and by demonstrating that ethical AI encourages knowledge sharing most effectively when synchronized with a supportive, rather than perfectionistic, work culture.

Byung‐Jik Kim, Yeon-Jun Choi, Julak Lee · 0 citations
Open access Jul 2026

“Overdependence on algorithms?”: how artificial intelligence ethical leadership can safeguard self-efficacy and spur innovation

It is found that AI dependence does not have a significant direct negative effect on innovative behavior, and inhibits innovation exclusively through a full mediation pathway by eroding employee self-efficacy, indicating that the suppression of innovation is caused not by the technology itself, but by the “deprivation of mastery experiences” that accompanies over-dependence.

Byung‐Jik Kim, Yeon-Jun Choi, Julak Lee · 0 citations