Machine Learning-Based Bibliometric Analysis of Systems Thinking Research

Systems Thinking is a transdisciplinary field for addressing complex systemic issues. However, a unified theory and definition for Systems Thinking do not exist yet. This paper explores the thematic structure of research in this field. Understanding the thematic structure of Systems Thinking research can provide a strategic research agenda. A bibliometric analysis of Systems Thinking research published in journal articles over the past 40 years, using machine learning, extracted the main research topics in the field. Topic modelling and keywords support thematic structure and directions for future research findings. The thematic structure is presented in a network diagram derived from the co-occurrence of the central thematic topics per article. This paper identified that Systems Thinking research focuses on complexity, systems engineering, systems thinking practice, and system dynamics modelling, indicating that research still aims to guide the practical application of Systems Thinking to address complex problems.