Organizations are increasingly leveraging the ability of artificial intelligence to analyze and resolve complex problems. This can potentially reshape the interdependencies and interactions of complex systems, leading to our research question: To what extent and in which direction is the literature on Artificial Intelligence (AI) and System Dynamics (SD) converging within the business and management landscape? We conducted an extensive literature review using bibliometric and topic modeling methods to address this question. Through a bibliometric analysis, we identified the areas in which academic papers referred to both SD and AI literature. However, bibliometrics do not show a clear path towards convergence. The top modeling analysis highlights more details on how convergence is structured, providing insights into how SD and AI may be integrated. Two trajectories are identified. In the “soft convergence,” AI supports system dynamics analysis and modeling more deeply characterized by social interaction. In the “hard convergence,” AI shapes innovative ways of rethinking system design, dynamics, and interdependencies. Our analysis suggests that while soft convergence is more visible in the business and management landscape, hard convergence may well represent a new frontier in studying system dynamics with the potential to reshape the landscape

Zooming in and out the landscape. Artificial intelligence and system dynamics in business and management / Armenia, Stefano; Franco, Eduardo; Iandolo, Francesca; Maielli, Giuliano; Vito, Pietro. - In: TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE. - ISSN 0040-1625. - 200:(2024). [10.1016/j.techfore.2023.123131]

Zooming in and out the landscape. Artificial intelligence and system dynamics in business and management

Stefano Armenia;Eduardo Franco;Francesca Iandolo
;
Giuliano Maielli;Pietro Vito
2024

Abstract

Organizations are increasingly leveraging the ability of artificial intelligence to analyze and resolve complex problems. This can potentially reshape the interdependencies and interactions of complex systems, leading to our research question: To what extent and in which direction is the literature on Artificial Intelligence (AI) and System Dynamics (SD) converging within the business and management landscape? We conducted an extensive literature review using bibliometric and topic modeling methods to address this question. Through a bibliometric analysis, we identified the areas in which academic papers referred to both SD and AI literature. However, bibliometrics do not show a clear path towards convergence. The top modeling analysis highlights more details on how convergence is structured, providing insights into how SD and AI may be integrated. Two trajectories are identified. In the “soft convergence,” AI supports system dynamics analysis and modeling more deeply characterized by social interaction. In the “hard convergence,” AI shapes innovative ways of rethinking system design, dynamics, and interdependencies. Our analysis suggests that while soft convergence is more visible in the business and management landscape, hard convergence may well represent a new frontier in studying system dynamics with the potential to reshape the landscape
2024
System dynamics; artificial intelligence; bibliometrics; topic modeling; technology; forecasting
01 Pubblicazione su rivista::01a Articolo in rivista
Zooming in and out the landscape. Artificial intelligence and system dynamics in business and management / Armenia, Stefano; Franco, Eduardo; Iandolo, Francesca; Maielli, Giuliano; Vito, Pietro. - In: TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE. - ISSN 0040-1625. - 200:(2024). [10.1016/j.techfore.2023.123131]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1698895
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