Modeling the Regeneration of Smart Urban Governance through a Data-Driven and Participatory Approach: The Case of Tabriz Metropolis

Abstract

The transformation of urban governance patterns in the data-driven era requires the regeneration of structures, processes, and interactions among urban institutions and citizens. In this study, with the aim of modeling the regeneration of smart urban governance in the metropolis of Tabriz, an integrated approach based on data-driven systems and citizen participation was adopted. To this end, structural equation modeling (SEM) was used to explain the relationships among the technological, institutional, and social components of governance. The research data were collected through questionnaires and spatial data analysis (GIS), and were modeled in three dimensions: “data and technology infrastructure,” “institutional and policy capacity,” and “citizen and networked interactions.” The analysis showed that the data-driven dimension has the strongest direct effect on urban governance efficiency (β = 0.57, p < 0.001) and, through enhancing transparency and evidence-based decision-making, plays an intermediary role in strengthening citizen participation. Moreover, the participatory dimension, with its indirect effect on urban sustainability, has led to increased public trust and institutional accountability. The findings confirm that smart governance is not merely a technological phenomenon, but rather an institutional–social framework for synergy among data, institutions, and citizens. Ultimately, the proposed model can serve as a localized framework for regenerating urban governance in Iran’s metropolitan areas and facilitate the transition toward a sustainable smart city.