Digital Twins and MIS Integration for Urban Resilience: A Strategic Approach to Smart City Evolution

The evolution of smart cities has accelerated the adoption of real-time digital infrastructures capable of sensing, processing, and simulating urban dynamics. Digital Twin technology, defined as a virtual replica of physical city systems, offers significant potential for predictive scenario modeling and resilience planning. However, most Digital Twin implementations remain fragmented and limited to technical or engineering layers, lacking integration with Management Information Systems (MIS), which are essential for strategic decision-making, interdepartmental coordination, and governance intelligence. This paper proposes a novel MIS–Digital Twin integration framework designed to enhance urban resilience and predictive governance in smart city ecosystems. The study applies a systematic literature synthesis to identify gaps in the current deployment of digital urban platforms and develops a multi-layered architecture that connects Digital Twin data layers with MIS-driven governance dashboards. A scenario-based application in urban resilience management is conceptualized to demonstrate how MIS-enabled Digital Twins can support proactive policy formulation, resource allocation, and risk monitoring. The conceptual analysis suggests that embedding Digital Twin simulations within MIS structures enables a shift from reactive city management towards intelligent, simulation-driven decision systems that improve transparency, preparedness, and adaptive governance. The proposed model contributes academically by positioning MIS as a strategic layer in Digital Twin research and offers municipal authorities a scalable blueprint for implementing data-informed resilience strategies. Drawing on sociotechnical systems theory, the framework distinguishes five linked layers: physical sensing, data integration, Digital Twin computation, MIS governance, and decision intelligence. The illustrative flood scenario follows sensor inputs through simulation, dashboard interpretation, early warning, and coordinated municipal action. Because the study develops a conceptual architecture rather than testing a deployed system, its proposed performance and resilience benefits require empirical validation in municipal settings.