2022/03/20 by Femi Olan, Emmanuel Ogiemwonyi Arakpogun, Jana Suklan +3 · 5 citations
Business, Management and Accounting · Engineering · #Collaboration in agile enterprises #Digital Transformation in Industry #Supply Chain Resilience and Risk Management
paper · pdf · doi:10.1016/j.jbusres.2022.03.008
openalex publication_date 2022/03/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/02
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.