Developing an indexing framework based on actor network theory (ANT) to analyze, evaluate, and realize success in sustainable smart city - Khosravi, Faramarz (Springer, 2025)
The current research aims to create a framework for sustainable smart cities in developing nations, focusing on Tehran, the capital of Iran, as a representative case. This study utilizes a mixed-methods approach, integrating literature review and the Best-Worst Method (BWM) to extract criteria and sub-criteria. It identifies key enablers for smart city advancement based on existing literature. The BWM methodology assesses the influence of these enablers on smart city development initiatives. Six criteria and twenty-six sub-criteria were weighted using BWM, informed by insights from four expert groups aligned with Actor Network Theory (ANT). Findings suggest that experts from various sectors prioritize data and analytics, technological advancement, and urban sustainability, with intelligent mobility, carbon neutrality, and waste management as significant sub-criteria. A sensitivity analysis confirmed the robustness of the weightings, and various applications were thoroughly discussed. This research is expected to be a crucial resource for policymakers and practitioners aiming to enhance smart city sustainability by focusing on essential factors. The paper furthermore refines ANT by using empirical findings from Tehran to contextualize and quantify stakeholder dynamics.
Keywords: Actor network theory (ANT); Smart cities (SC); Cluster analysis; Pearson analysis; Sensitivity analysis; City stakeholders