Volume 12, Issue 2 (9-2025)
Human Information Interaction 2025, 12(2): 114-128 |
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Andayesh S, kianrad Z. Examining the Relationship Between Artificial Intelligence Capabilities and Organizational Creativity: The Mediating Role of Knowledge Sharing (Librarians of Medical Sciences University Libraries). Human Information Interaction 2025; 12 (2)
URL: http://hii.khu.ac.ir/article-1-3211-en.html
URL: http://hii.khu.ac.ir/article-1-3211-en.html
Knowledge and Information Science, Persian Gulf University, Bushehr, Iran.
Abstract: (741 Views)
Introduction
This study examines the relationship between artificial intelligence (AI) utilization and organizational creativity, with knowledge sharing as a mediating variable, among librarians working in medical sciences university libraries in Tehran. AI, as a transformative technology of the Fourth Industrial Revolution, plays a growing role in enhancing organizational performance through automation, decision support, and improved information management. Literature indicates that AI positively influences creativity and that knowledge sharing reinforces this effect by facilitating exchange, collaboration, and innovative behaviors. Despite increasing global attention to AI capabilities, research in knowledge-intensive environments such as academic libraries remains limited. Addressing this gap, the present study uses a structural equation modeling approach to explore how AI adoption contributes to creativity and how knowledge sharing fully mediates this relationship within library settings.
Methods and Materoal
This applied and quantitative study examines the relationship between artificial intelligence and organizational creativity, considering the mediating role of knowledge sharing among librarians in medical sciences universities in Tehran. Using a census sampling approach, data were collected from 214 librarians between October and December 2024. Validated instruments were employed to assess AI utilization, organizational creativity, and knowledge sharing. Reliability and validity were confirmed through Cronbach’s alpha and convergent/discriminant validity analyses. Structural equation modeling (SEM) using SmartPLS was applied to test the conceptual model and hypotheses, enabling simultaneous evaluation of latent variables, path coefficients, and model fit indices.
Resultss and Discussion
Based on the statistical evidence, the Z-value exceeded the threshold of 1.96, confirming with 95% confidence that knowledge sharing plays a significant mediating role between artificial intelligence (AI) and organizational creativity (P ≤ 0.05). The Variance Accounted For (VAF) index, used to assess the strength of the mediation effect, was calculated as 0.894, indicating full mediation. Structural Equation Modeling (SEM) results further demonstrated that AI has a positive and significant effect on organizational creativity (β = 0.501, t = 11.909, P ≤ 0.05), meaning that a one-unit increase in AI utilization results in an average increase of 0.501 standard deviations in creativity. Additionally, AI positively influences knowledge sharing (β = 0.537, t = 9.672, P ≤ 0.05), implying that higher AI adoption leads to improved knowledge sharing. Finally, knowledge sharing itself positively and significantly impacts organizational creativity (β = 0.618, t = 9.853, P ≤ 0.05), suggesting that a one-unit increase in knowledge sharing contributes to a 0.618 standard deviation growth in creativity.
Conclusion
The study highlights the strategic role of artificial intelligence (AI) in enhancing organizational creativity through the mediating effect of knowledge sharing among librarians in medical sciences university libraries. The findings indicate that AI capabilities positively influence both knowledge sharing and organizational creativity, reinforcing previous research and demonstrating that AI functions not only as a technological tool but also as a cognitive and cultural infrastructure that strengthens communication, decision-making, and innovation. Knowledge sharing also significantly promotes creativity by fostering the exchange of experiences, ideas, and expertise, thereby enabling collaborative problem-solving and the generation of novel solutions. Despite its contributions, the research is limited by its focus on a specific population, the use of self-reported data, and its cross-sectional design. The study recommends investing in AI infrastructure, cultivating a strong knowledge-sharing culture, and implementing supportive managerial practices to promote innovation, enhance learning, and achieve sustainable organizational competitiveness.
This study examines the relationship between artificial intelligence (AI) utilization and organizational creativity, with knowledge sharing as a mediating variable, among librarians working in medical sciences university libraries in Tehran. AI, as a transformative technology of the Fourth Industrial Revolution, plays a growing role in enhancing organizational performance through automation, decision support, and improved information management. Literature indicates that AI positively influences creativity and that knowledge sharing reinforces this effect by facilitating exchange, collaboration, and innovative behaviors. Despite increasing global attention to AI capabilities, research in knowledge-intensive environments such as academic libraries remains limited. Addressing this gap, the present study uses a structural equation modeling approach to explore how AI adoption contributes to creativity and how knowledge sharing fully mediates this relationship within library settings.
Methods and Materoal
This applied and quantitative study examines the relationship between artificial intelligence and organizational creativity, considering the mediating role of knowledge sharing among librarians in medical sciences universities in Tehran. Using a census sampling approach, data were collected from 214 librarians between October and December 2024. Validated instruments were employed to assess AI utilization, organizational creativity, and knowledge sharing. Reliability and validity were confirmed through Cronbach’s alpha and convergent/discriminant validity analyses. Structural equation modeling (SEM) using SmartPLS was applied to test the conceptual model and hypotheses, enabling simultaneous evaluation of latent variables, path coefficients, and model fit indices.
Resultss and Discussion
Based on the statistical evidence, the Z-value exceeded the threshold of 1.96, confirming with 95% confidence that knowledge sharing plays a significant mediating role between artificial intelligence (AI) and organizational creativity (P ≤ 0.05). The Variance Accounted For (VAF) index, used to assess the strength of the mediation effect, was calculated as 0.894, indicating full mediation. Structural Equation Modeling (SEM) results further demonstrated that AI has a positive and significant effect on organizational creativity (β = 0.501, t = 11.909, P ≤ 0.05), meaning that a one-unit increase in AI utilization results in an average increase of 0.501 standard deviations in creativity. Additionally, AI positively influences knowledge sharing (β = 0.537, t = 9.672, P ≤ 0.05), implying that higher AI adoption leads to improved knowledge sharing. Finally, knowledge sharing itself positively and significantly impacts organizational creativity (β = 0.618, t = 9.853, P ≤ 0.05), suggesting that a one-unit increase in knowledge sharing contributes to a 0.618 standard deviation growth in creativity.
Conclusion
The study highlights the strategic role of artificial intelligence (AI) in enhancing organizational creativity through the mediating effect of knowledge sharing among librarians in medical sciences university libraries. The findings indicate that AI capabilities positively influence both knowledge sharing and organizational creativity, reinforcing previous research and demonstrating that AI functions not only as a technological tool but also as a cognitive and cultural infrastructure that strengthens communication, decision-making, and innovation. Knowledge sharing also significantly promotes creativity by fostering the exchange of experiences, ideas, and expertise, thereby enabling collaborative problem-solving and the generation of novel solutions. Despite its contributions, the research is limited by its focus on a specific population, the use of self-reported data, and its cross-sectional design. The study recommends investing in AI infrastructure, cultivating a strong knowledge-sharing culture, and implementing supportive managerial practices to promote innovation, enhance learning, and achieve sustainable organizational competitiveness.
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