Mike Kagioglou

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About

Mike Kagioglou is a leading researcher in operations management, with a particular focus on the intersection of learning curve theory and Industry 4.0. His work explores how organizations can optimize performance through the systematic analysis of production and process improvements. His most-cited paper, a 2022 scoping review on learning curve applications in Industry 4.0, has garnered 13 citations and provides a foundational framework for understanding how individual, group, and organizational learning evolves within smart manufacturing environments. By systematically mapping the literature, Kagioglou identifies critical gaps and opportunities for leveraging data-driven technologies to accelerate learning and efficiency. His contributions are vital for practitioners and scholars seeking to integrate traditional industrial engineering concepts with modern digital transformations. Kagioglou’s research is characterized by rigorous methodological approaches, including systematic reviews, which ensure his findings are both reliable and actionable. His work not only advances academic understanding but also offers practical insights for industries aiming to harness the full potential of Industry 4.0.