A Systematic Literature Review on System Dynamics

System Dynamics is a methodology for modeling and simulating dynamically complex systems, which are characterized by feedback loops, nonlinearity, and time delays. It uses Causal Loop Diagrams and Stock-and-Flow Diagrams to represent system structures and to analyze how these structures influence system behavior over time. The majority of reviews on System Dynamics use cases either focus on a single thematic domain or are not up to date. As a result, a comprehensive and up-to-date overview of System Dynamics use cases across all thematic domains is lacking. Furthermore, no Systematic Literature Review has yet examined whether and to what extent artificial intelligence has been employed to extend and enhance the System Dynamics approach in identified use cases. To address this research gap, we conducted a Systematic Literature Review. The identified studies are classified within a sociotechnical system framework consisting of User-Machine Interaction, Value Chain-related Domains, and Social Factors. Additionally, we examine the role of artificial intelligence in advancing the System Dynamics approach within the identified use cases. We identified 41 relevant publications covering 19 thematic domains. Most studies fall within the Value Chain-related Domains system, followed by Social Factors and User-Machine Interaction. The integration of artificial intelligence into System Dynamics use cases remains rare. Our findings highlight the broad applicability of System Dynamics across various thematic domains while simultaneously revealing a gap in the complementary use of artificial intelligence.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3571620
Citations
3
Primary Topic
Complex Systems and Decision Making
Type
article
Field-Weighted Citation Impact
6.32
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article

A Systematic Literature Review on System Dynamics

Christopher Mai, Ricardo Buettner, Bo Hu, Juliano Leônidas Hoffmann
3 citations
IEEE Access
Complex Systems and Decision Making
6.32
article

A Systematic Literature Review on System Dynamics

Christopher Mai, Ricardo Buettner, Bo Hu, Juliano Leônidas Hoffmann
article en
3 citations

Abstract

System Dynamics is a methodology for modeling and simulating dynamically complex systems, which are characterized by feedback loops, nonlinearity, and time delays. It uses Causal Loop Diagrams and Stock-and-Flow Diagrams to represent system structures and to analyze how these structures influence system behavior over time. The majority of reviews on System Dynamics use cases either focus on a single thematic domain or are not up to date. As a result, a comprehensive and up-to-date overview of System Dynamics use cases across all thematic domains is lacking. Furthermore, no Systematic Literature Review has yet examined whether and to what extent artificial intelligence has been employed to extend and enhance the System Dynamics approach in identified use cases. To address this research gap, we conducted a Systematic Literature Review. The identified studies are classified within a sociotechnical system framework consisting of User-Machine Interaction, Value Chain-related Domains, and Social Factors. Additionally, we examine the role of artificial intelligence in advancing the System Dynamics approach within the identified use cases. We identified 41 relevant publications covering 19 thematic domains. Most studies fall within the Value Chain-related Domains system, followed by Social Factors and User-Machine Interaction. The integration of artificial intelligence into System Dynamics use cases remains rare. Our findings highlight the broad applicability of System Dynamics across various thematic domains while simultaneously revealing a gap in the complementary use of artificial intelligence.

IEEE AccessVol. 13
Helmut Schmidt University (DE), Universität der Bundeswehr München (DE)
Openalex Percentile: Top 4%
Complex Systems and Decision Making
6.32
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A Systematic Literature Review on System Dynamics — Christopher Mai, Ricardo Buettner, et al. · IEEE Access (2025) | TGRS Research Map | TGRS