Urban futures under geopolitical instability: Aligning sustainability and SDGs in the age of global megatrends

Abstract

Rapid urbanization is increasing pressure on infrastructure, natural resources, social well-being, and institutional capacity, while climate change, demographic shifts, migration, technological disruption, and geopolitical instability are further complicating paths to sustainable urban development. This study develops a conceptual, SDG-aligned framework to examine the interactions between six major global megatrends and their associated sub-trends, with a particular emphasis on their cascading effects, interdependencies, and impact on urban resilience. Drawing on existing scholarly and policy literature, this study synthesizes case-based evidence from diverse urban contexts to demonstrate how global trends translate into locally distinct sustainability challenges. Within this framework, the study proposes an Extended Composite Sustainability Index (ECSI) that conceptually integrates six interconnected dimensions namely urbanization, demographic shift, climate change, technological transformation, spatial change, and geopolitical instability to provide a multidimensional framework for assessing sustainable urban development. This framework conceptualizes resilience and SDG progress as outcomes of interactions between these dimensions, rather than as independent variables. The proposed ECSI and its associated formulations are presented as conceptual constructs. The analysis shows that technological innovations, such as artificial intelligence, big data, blockchain, and the Internet of Things, can contribute to resource efficiency, safety, and inclusive urban development, but without proper governance and institutional safeguards, they can also reinforce privileged and digital inequalities. Overall, this study highlights the need for an integrated assessment approach that simultaneously evaluates sustainability dimensions, while also providing a conceptual basis for future empirical calibration, sensitivity testing, and validation using real-world urban datasets.