The Link Between Complex Systems Theory and Smart Learning in Management
Keywords:
Complex systems theory, smart learning, management, self-organization, feedback, adaptive decision-makingAbstract
This study aims to examine and conceptualize the connection between the principles of complex systems theory and the mechanisms of smart learning in management to provide a theoretical framework for understanding adaptive learning and decision-making in contemporary organizations. This research employed a qualitative design based on a systematic literature review. Data were collected from reputable databases including Scopus, Web of Science, ScienceDirect, and Google Scholar. Out of 45 identified sources, 12 articles meeting the inclusion criteria were selected and analyzed using NVivo version 14. Data were coded through open, axial, and selective coding processes, and main themes were derived until theoretical saturation was achieved. The results revealed three main themes: the dynamics of complex systems theory in management, the mechanisms of smart learning in organizations, and the integration of these two frameworks into a unified conceptual model. The findings indicate that principles such as self-organization, feedback, and emergence in complex systems theory align with data-driven learning, adaptive decision-making, and organizational intelligence in smart learning. The integration of these concepts enhances organizational agility, resilience, and innovation. The study concludes that complex systems theory provides a robust theoretical foundation for understanding and developing smart learning in organizations. Recognizing nonlinear interactions, multilevel feedback, and self-regulating mechanisms enables intelligent decision-making and sustainable adaptability in management. In the digital era, this synergy fosters the creation of organizations that not only adapt to change but also transform it into opportunities for innovation.
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References
Alavi, M., & Leidner, D. E. (2001). Review: Knowledge management and knowledge management systems: Conceptual foundations and research issues. MIS Quarterly, 25(1), 107–136.
Anderson, P. (1999). Complexity theory and organization science. Organization Science, 10(3), 216–232.
Baker, R. S., & Siemens, G. (2014). Educational data mining and learning analytics. In Learning analytics (pp. 253–274). Springer.
Boisot, M., & Child, J. (1999). Organizations as adaptive systems in complex environments: The case of China. Organization Science, 10(3), 237–252.
Brynjolfsson, E., & McAfee, A. (2017). Machine, platform, crowd: Harnessing our digital future. W. W. Norton & Company.
Capra, F., & Luisi, P. L. (2014). The systems view of life: A unifying vision. Cambridge University Press.
Chen, H., Chiang, R. H. L., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), 1165–1188.
Choi, Y. (2019). Adaptive learning systems as complex adaptive systems: A conceptual framework. Computers & Education, 136, 85–95.
Choo, C. W. (2006). The knowing organization: How organizations use information to construct meaning, create knowledge, and make decisions. Oxford University Press.
Cilliers, P. (1998). Complexity and postmodernism: Understanding complex systems. Routledge.
Davis, B., & Sumara, D. (2006). Complexity and education: Inquiries into learning, teaching, and research. Lawrence Erlbaum Associates.
Dooley, K. J. (2002). Organizational complexity. International Encyclopedia of Business and Management, 6(5010), 5013–5022.
Holland, J. H. (2014). Complexity: A very short introduction. Oxford University Press.
Ifenthaler, D., & Yau, J. Y.-K. (2020). Utilising learning analytics for study success: Reflections on current empirical findings. Computers in Human Behavior, 107, 105–118.
Luckin, R. (2017). Machine learning and human intelligence: The future of education for the 21st century. UCL Institute of Education Press.
McMillan, E. (2008). Complexity, management and the dynamics of change. Routledge.
Mitleton-Kelly, E. (2003). Complex systems and evolutionary perspectives on organisations: The application of complexity theory to organisations. Pergamon.
Morin, E. (2008). On complexity. Hampton Press.
Nonaka, I., & Takeuchi, H. (1995). The knowledge-creating company: How Japanese companies create the dynamics of innovation. Oxford University Press.
Senge, P. M. (2006). The fifth discipline: The art and practice of the learning organization. Doubleday.
Siemens, G. (2013). Learning analytics: The emergence of a discipline. American Behavioral Scientist, 57(10), 1380–1400.
Stacey, R. D. (2011). Strategic management and organisational dynamics: The challenge of complexity. Pearson Education.
Uhl-Bien, M., & Marion, R. (2009). Complexity leadership in bureaucratic forms of organizing: A meso model. The Leadership Quarterly, 20(4), 631–650.
Uhl-Bien, M., Marion, R., & McKelvey, B. (2007). Complexity leadership theory: Shifting leadership from the industrial age to the knowledge era. The Leadership Quarterly, 18(4), 298–318.
