DIGITAL TWINS OF COMMUNITIES FOR MODELING THE PROCESSES OF FINANCIAL AND SOCIO-PSYCHOLOGICAL REINTEGRATION OF IDPs AND VETERANS
Year: 2026
Type: article
Abstract: The large-scale displacement of the population caused by the full-scale war in Ukraine and the increasing number of veterans returning to civilian life have significantly intensified the management challenges faced by territorial communities. Local governments must efficiently allocate financial resources, coordinate social services, support employment, provide psychological assistance, and evaluate the long-term effects of reintegration policies. Under these conditions, fragmented information systems and traditional monitoring methods do not provide sufficient analytical support for evidence-based decision-making. This study aims to substantiate a conceptual model of a territorial community digital twin for modelling financial and socio-psychological reintegration processes of internally displaced persons (IDPs) and veterans, creating an integrated information and analytical foundation for local governance. The research applies a systems approach to conceptualize the community digital twin as a multi-level analytical system integrating financial, socio-psychological, demographic, migration, and infrastructure data. Analysis of scientific publications on digital twins and digital public governance enabled the development of the model architecture. Structural-functional and comparative analyses were used to define module functions and assess the advantages of the proposed approach over conventional monitoring systems. Synthesis, abstraction, induction, and deduction supported the formation of the conceptual framework. The proposed model consists of five interconnected modules: financial, socio-psychological, demographic and migration, infrastructure, and monitoring with feedback. Their integration enables comprehensive assessment of financial capacity, demographic changes, social adaptation, and public service accessibility. The digital twin supports continuous data updating, scenario modelling, and forecasting of management outcomes before decisions are implemented. It allows assessment of reintegration programme costs, identification of vulnerable groups, prediction of demand for social, employment, housing, and psychological services, and evaluation of policy effectiveness under different scenarios. Unlike traditional monitoring based mainly on retrospective reporting, the digital twin provides real-time analytical support, integrated data exchange, personalized assessment of needs, and predictive identification of social risks. Its practical value lies in improving strategic planning, optimizing local budget allocation, strengthening coordination among institutions, and enhancing evidence-based decision-making. Implementation of the model can contribute to more effective reintegration programmes and sustainable development of territorial communities during post-war recovery.
Source: Economic scope
Author: Tetiana Fursa
Institution: West Ukrainian National University
Language: English
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7204188342