Smart cities, smart systems: A comprehensive review of system dynamics model applications in urban studies in the big data era

Abstract

• This study reviews system dynamics (SD) models for urban sustainability, emphasizing big data. • We identify gaps in urban SD modeling and highlight big data for better accuracy. • We propose methods for real-time data processing to enhance predictive modeling. • We recommend cross-discipline efforts to further urban sustainability analyses. • We stress the need for data-rich, real-time models for complex urban challenges. This paper addresses urban sustainability challenges amid global urbanization, emphasizing the need for innovative approaches aligned with the Sustainable Development Goals. While traditional tools and linear models offer insights, they fall short in presenting a holistic view of complex urban challenges. System dynamics (SD) models that are often utilized to provide holistic, systematic understanding of a research subject, like the urban system, emerge as valuable tools, but data scarcity and theoretical inadequacy pose challenges. The research reviews relevant papers on recent SD model applications in urban sustainability since 2018, categorizing them based on nine key indicators. Among the reviewed papers, data limitations and model assumptions were identified as major challenges in applying SD models to urban sustainability. This led to exploring the transformative potential of big data analytics, a rare approach in this field as identified by this study, to enhance SD models’ empirical foundation. Integrating big data could provide data-driven calibration, potentially improving predictive accuracy and reducing reliance on simplified assumptions. The paper concludes by advocating for new approaches that reduce assumptions and promote real-time applicable models, contributing to a comprehensive understanding of urban sustainability through the synergy of big data and SD models.

Topics & Concepts