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Artificial Intelligence and Knowledge Sharing: Contributing Factors to Organizational Performance

Olan, Femi; Arakpogun, Emmanuel; Suklan, Jana; Nakpodia, Franklin; Damij, Nadja; Jayawickrama, Uchitha

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Authors

Femi Olan

Emmanuel Arakpogun

Jana Suklan

Nadja Damij

Uchitha Jayawickrama



Abstract

The evolution of organizational processes and performance over the past decade has been largely enabled by cutting-edge technologies such as data analytics, artificial intelligence (AI), and business intelligence applications. The increasing use of cutting-edge technologies has boosted effectiveness, efficiency and productivity, as existing and new knowledge within an organization continues to improve AI abilities. Consequently, AI can identify redundancies within business processes and offer optimal resource utilization for improved performance. However, the lack of integration of existing and new knowledge makes it problematic to ascertain the required nature of knowledge needed for AI’s ability to optimally improve organizational performance. Hence, organizations continue to face reoccurring challenges in their business processes, competition, technological advancement and finding new solutions in a fast-changing society. To address this knowledge gap, this study applies a fuzzy set-theoretic approach underpinned by the conceptualization of AI, knowledge sharing (KS) and organizational performance (OP). Our result suggests that the implementation of AI technologies alone is not sufficient in improving organizational performance. Rather, a complementary system that combines AI and KS provides a more sustainable organizational performance strategy for business operations in a constantly changing digitized society.

Citation

Olan, F., Arakpogun, E., Suklan, J., Nakpodia, F., Damij, N., & Jayawickrama, U. (2022). Artificial Intelligence and Knowledge Sharing: Contributing Factors to Organizational Performance. Journal of Business Research, 145, 605-615. https://doi.org/10.1016/j.jbusres.2022.03.008

Journal Article Type Article
Acceptance Date Mar 5, 2022
Online Publication Date Mar 20, 2022
Publication Date 2022-06
Deposit Date Mar 11, 2022
Publicly Available Date Mar 28, 2022
Journal Journal of Business Research
Print ISSN 0148-2963
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 145
Pages 605-615
DOI https://doi.org/10.1016/j.jbusres.2022.03.008
Public URL https://durham-repository.worktribe.com/output/1212403

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